Holmeister/AAID-clone · Datasets at Hugging Face

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Task: Gauge the level of intensity for emotion E in the tweet, assigning it a score between 0 and 1. A score of 0 indicates the lowest intensity, while a score of 1 indicates the highest intensity.	Tweet: Boys Dm me pictures of your cocks! The best one will get uploaded! ☺️💦💦 #Cumtribute #dm #snapchat #snapme #nudes #dickpic #cocktribute Emotion: anger Intensity score:	0.396
Task: Classify the tweet into one of four ordinal intensity levels, indicating the degree of emotion E experienced by the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.	Tweet: Overtime... #TeamNA #WCH2016 Emotion: fear Intensity class:	0: no fear can be inferred
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E).	Tweet: @NFLonFOX @TheDoctorCarson @FOXSports Easy, breezy, beautiful... Emotion: joy Intensity score:	0.604
Task: Evaluate the tweet for emotional cues and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that indicate the tweeter's state of mind.	Tweet: ... flat party and I instantly get bollocked about it. This tweet contains emotions:
Task: Analyze the tweet's sentiment and assign it to either 'neutral or no emotion' or one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).	Tweet: @OniLink86 @DarekMeridian lmao awe... #sad This tweet contains emotions:	sadness
Task: Classify the tweet into one of four ordinal classes of intensity of emotion E that best represents the mental state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.	Tweet: @andreasarahco do you actually heely on campus bc this should scare you Emotion: fear Intensity class:	1: low amount of fear can be inferred
Task: Determine the prevailing emotional tone of the tweet, categorizing it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that most accurately represent the tweeter's mental state.	Tweet: I forgot about this nice area down here with the fiery hearths This tweet contains emotions:	anticipation, joy, optimism
Task: Assign the tweet to one of seven ordinal classes, each representing a distinct level of positive or negative sentiment intensity, reflecting the mental state of the tweeter. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred.	Tweet: @Ginger_Naylor Connie came back in Hey you seem a bit more lively Intensity class:	0: neutral or mixed emotional state can be inferred
Task: Estimate the strength of emotion E in the tweet by assigning it a real-valued score between 0 and 1, where 0 signifies the least intensity and 1 signifies the greatest intensity.	Tweet: @RonMexico760 The guy who calls people 'cuck' and is anti-BLM is offended by idea that he might not be pro-policing reform? That's amazing. Emotion: anger Intensity score:	0.625
Task: Assign one of four ordinal intensity classes of emotion E to a given tweet based on the emotional state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.	Tweet: @_stfukohle it's ok champ you'll make it I'm cheering you on from a far Emotion: joy Intensity class:	2: moderate amount of joy can be inferred
Task: Evaluate the strength of emotion E in the tweet, providing a real-valued score from 0 to 1. A score of 0 denotes the absence of the emotion, while a score of 1 indicates the highest degree of intensity.	Tweet: Be #happy. Be #bright. Be YOU :) #identity #TimelessTips #friendship #family #forest #water #family #TrueLove #God #RoadSoFar #you #LifeTrip Emotion: joy Intensity score:	0.708
Task: Determine the appropriate intensity class for the tweet, reflecting the level of emotion E experienced by the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.	Tweet: When it comes to Syria, I get very fucking annoyed at pessimism, like I get full on triggered. Optimism or gtfo. Emotion: sadness Intensity class:	2: moderate amount of sadness can be inferred
Task: Categorize the tweet into one of seven ordinal classes, representing different degrees of positive and negative sentiment intensity, that most accurately reflects the emotional state of the Twitter user. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred.	Tweet: @amychozick @jswatz Not a word about terrorism. Intensity class:	0: neutral or mixed emotional state can be inferred
Task: Rate the intensity of emotion E in the tweet on a scale of 0 to 1, with 0 indicating the least intensity and 1 indicating the highest intensity.	Tweet: Kik me I want to swap pics I will post on my account anonymously if you wish Kik: vsvplou #Kik #kikme #nudes #tits #snapchat Emotion: anger Intensity score:	0.188
Task: Rate the intensity of emotion E in the tweet on a scale of 0 to 1, with 0 indicating the least intensity and 1 indicating the highest intensity.	Tweet: You dont have to feel grateful to be grateful, for it is written ' all things work together for good' for those who love God. #cheerful Emotion: joy Intensity score:	0.623
Task: Determine the appropriate intensity class for the tweet, reflecting the level of emotion E experienced by the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.	Tweet: 10 page script due Friday for class. Who said I could do this MFA thing? #panic #GradSchoolProblems #someonetelltinafeytohireme Emotion: fear Intensity class:	3: high amount of fear can be inferred
Task: Estimate the strength of emotion E in the tweet by assigning it a real-valued score between 0 and 1, where 0 signifies the least intensity and 1 signifies the greatest intensity.	Tweet: @cazzrhughes its reflective of the current political debate #awful Emotion: fear Intensity score:	0.508
Task: Classify the tweet into one of four ordinal intensity levels, indicating the degree of emotion E experienced by the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.	Tweet: Isaiah 40:31\nthose who trust in the Lord will find new strength.\nThey will soar high on wings like eagles.\nThey will run and not grow weary. Emotion: sadness Intensity class:	0: no sadness can be inferred
Task: Classify the tweet's emotional intensity into one of four ordinal levels of emotion E, providing insights into the mental state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.	Tweet: Ready for that nice, breezy, calm, sunshine weather.🍂🍁 #Autumn Emotion: joy Intensity class:	2: moderate amount of joy can be inferred
Task: Evaluate the strength of emotion E in the tweet, providing a real-valued score from 0 to 1. A score of 0 denotes the absence of the emotion, while a score of 1 indicates the highest degree of intensity.	Tweet: @RealJeffsdomain Wolfpack theme and trons and sting wore the wolf shirt Emotion: anger Intensity score:	0.312
Task: Identify the primary emotion conveyed in the tweet and assign it to either 'neutral or no emotion' or one or more of the provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best capture the tweeter's mental state.	Tweet: If you really care like you state @flyfrontier @FrontierCare then I would seriously address sensitivity training to your employees This tweet contains emotions:	anticipation, optimism
Task: Classify the tweet into one of four ordinal classes of intensity of emotion E that best represents the mental state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.	Tweet: @mylittlepwnies3 \n> #terrorism coffee addict\n> blocks cats, writers, artists and hedonists Emotion: fear Intensity class:	0: no fear can be inferred
Task: Gauge the level of intensity for emotion E in the tweet, assigning it a score between 0 and 1. A score of 0 indicates the lowest intensity, while a score of 1 indicates the highest intensity.	Tweet: Being alone is better than being lonely. Know what is worse than being lonely? Being empty; that's right!\n#Loneliness #aloneinthecity #fear Emotion: fear Intensity score:	0.729
Task: Rate the intensity of emotion E in the tweet on a scale of 0 to 1, with 0 indicating the least intensity and 1 indicating the highest intensity.	Tweet: @SeanUnfiltered Texans are scared of this bunch! Emotion: fear Intensity score:	0.600
Task: Measure the level of emotion E in the tweet using a real-valued score between 0 and 1, where 0 represents the lowest intensity and 1 represents the highest intensity.	Tweet: @LucidBurrito Doesnt do it to anyone else, he literally pulled me into the office cause someone complained I spit in the sink yesterday Emotion: sadness Intensity score:	0.457
Task: Analyze the tweet's emotional connotations and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best portray the tweeter's mental state.	Tweet: #Gratitude - recovery health love God conscious drive hope perseverance wealthy home kids SoCal #recoveryfit youthful #sober This tweet contains emotions:	joy, optimism
Task: Determine the appropriate intensity category of emotion E for the tweet, reflecting the emotional state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.	Tweet: Love takes off the masks that we fear we cannot live without and know we cannot live within. - James A. Baldwin Emotion: fear Intensity class:	0: no fear can be inferred
Task: Assign one of four ordinal intensity classes of emotion E to a given tweet based on the emotional state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.	Tweet: MC: what are you listen to these days?\nBogum: these days I feel gloomy, I listen to ccm (spiritual song) often.\n\nChurch oppa mode. :) Emotion: sadness Intensity class:	2: moderate amount of sadness can be inferred
Task: Assess the magnitude of emotion E in the tweet using a real number between 0 and 1, where 0 denotes the least intensity and 1 denotes the most intensity.	Tweet: So now... yeah. I'm home again.\nStill feeling mixed up inside & kinda gloomy. But a little more optimistic that I'll figure this out. Emotion: sadness Intensity score:	0.521
Task: Gauge the level of intensity for emotion E in the tweet, assigning it a score between 0 and 1. A score of 0 indicates the lowest intensity, while a score of 1 indicates the highest intensity.	Tweet: @SkyUK what a joke!! Cut our internet off early 'by mistake' and then don't reinstate it when we no longer need an engineer 😡 #fuming Emotion: anger Intensity score:	0.646
Task: Assign a suitable level of intensity of emotion E to the tweet, representing the emotional state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.	Tweet: @realDonaldTrump negative campaign of doom and gloom don't win elections Emotion: sadness Intensity class:	1: low amount of sadness can be inferred
Task: Determine the appropriate ordinal classification for the tweet, reflecting the tweeter's mental state based on the magnitude of positive and negative sentiment intensity conveyed. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred.	Tweet: You forever straight so fix that frown u good😇 @amayyaaag__ Intensity class:	1: slightly positive emotional state can be inferred
Task: Determine the appropriate intensity class for the tweet, reflecting the level of emotion E experienced by the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.	Tweet: @BjerkeDanielle @FunnySayings lol that's hilarious Emotion: joy Intensity class:	3: high amount of joy can be inferred
Task: Determine the degree of intensity for emotion E in the tweet, giving it a score between 0 and 1, where 0 signifies the least intensity and 1 signifies the greatest intensity.	Tweet: @LuluLemonLime83 wow , your right they do need help,so what I'm getting from the Laureliver fandom and bitter comic fandom and Emotion: anger Intensity score:	0.479
Task: Assess the emotional content of the tweet and classify it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best represent the tweeter's mental state.	Tweet: @megynkelly We should be ignoring these rioters like the current administration ignores #terrorism. This will obviously make it stop. This tweet contains emotions:	anger, disgust, fear
Task: Categorize the tweet into an intensity level of the specified emotion E, representing the mental state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.	Tweet: @eliroth ya know I love ya man, but #TheGreenInferno really fucked with my head....(giggle)..do it again. #epic #ineedtherapy Emotion: fear Intensity class:	0: no fear can be inferred
Task: Evaluate the tweet for emotional cues and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that indicate the tweeter's state of mind.	Tweet: @keithboykin unfortunately it won't end there... followers of whichever candidate isn't elected will throw tantrums. No winning this elec This tweet contains emotions:	anger, sadness
Task: Categorize the tweet into an ordinal class that best characterizes the tweeter's mental state, considering various degrees of positive and negative sentiment intensity. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred.	Tweet: Some Erykah Badu to sedate me 💕 Intensity class:	1: slightly positive emotional state can be inferred
Task: Classify the tweet into one of seven ordinal classes, corresponding to various levels of positive and negative sentiment intensity, that best represents the mental state of the tweeter. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred.	Tweet: @everycolorbot more like every color looks the same #triggered #colorblind #offended Intensity class:	-1: slightly negative emotional state can be inferred
Task: Categorize the tweet's emotional tone as either 'neutral or no emotion' or identify the presence of one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).	Tweet: On the last episode of #MakingAMurderer poor Brendan glad they #appeal it #shocking #crime #documentary #reallife This tweet contains emotions:	surprise
Task: Classify the tweet into one of seven ordinal categories, indicating the intensity of positive or negative sentiment expressed by the tweeter and reflecting their current mental state. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred.	Tweet: Take my kindness for weakness when you acting silly keeping it 100 ain't your forté #ChrisBrown #TeamBreezy Intensity class:	0: neutral or mixed emotional state can be inferred
Task: Evaluate the tweet for emotional cues and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that indicate the tweeter's state of mind.	Tweet: $FOGO max pessimism here and no bottom (yet). Has a solid PE ratio for a restaurant. Let's catch it at 8 level or 10 level if it comes. This tweet contains emotions:	joy, pessimism
Task: Categorize the tweet into one of seven ordinal classes, representing different degrees of positive and negative sentiment intensity, that most accurately reflects the emotional state of the Twitter user. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred.	Tweet: Scott Dann injured aka my worst nightmare Intensity class:	-3: very negative emotional state can be inferred
Task: Assess the emotional content of the tweet and classify it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best represent the tweeter's mental state.	Tweet: I only have to wave a fiery cross and we will f**kin' do this! This tweet contains emotions:	anger, anticipation, optimism
Task: Analyze the tweet's sentiment and assign it to either 'neutral or no emotion' or one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).	Tweet: I'm still laughing 'Bitch took my pillow' line #kurt This tweet contains emotions:	joy, optimism
Task: Measure the level of emotion E in the tweet using a real-valued score between 0 and 1, where 0 represents the lowest intensity and 1 represents the highest intensity.	Tweet: @XemitSellsMagic add tracking but resent them Emotion: anger Intensity score:	0.688
Task: Classify the mental state of the tweeter based on the tweet, determining if it is 'neutral or no emotion' or characterized by any of the provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).	Tweet: I'm really hitting all flavors of my sparkling water rap. But you know what's tripping me out? These half French and Spanish flavors. This tweet contains emotions:	joy, love
Task: Calculate the intensity of emotion E in the tweet as a decimal value ranging from 0 to 1, with 0 representing the lowest intensity and 1 representing the highest intensity.	Tweet: @SkySportsRL i would just get some decent referees #shocking Emotion: fear Intensity score:	0.312
Task: Classify the tweet into one of four ordinal intensity levels, indicating the degree of emotion E experienced by the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.	Tweet: SO many great pics from the show in Tokyo😍 I like all his outfits now except the lace one w those horrible pants....💁 Emotion: fear Intensity class:	0: no fear can be inferred
Task: Classify the mental state of the tweeter based on the tweet, determining if it is 'neutral or no emotion' or characterized by any of the provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).	Tweet: @BokuNoGio AND his momma was worse than Tony sopranos momma #wow #sad #history #major This tweet contains emotions:	disgust, sadness
Task: Determine the dominant emotion in the tweet and classify it as either 'neutral or no emotion' or one of the eleven provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).	Tweet: Always do sober what you said you'd do drunk. That will teach you to keep your mouth shut. \n― Ernest Hemingway #quote This tweet contains emotions:	optimism, trust
Task: Categorize the tweet based on the intensity of the specified emotion E, capturing the tweeter's mental state. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.	Tweet: @Docjp they unleashing God's wrath just as Cain did Emotion: anger Intensity class:	1: low amount of anger can be inferred
Task: Assign the tweet to a specific ordinal class that corresponds to the tweeter's mental state, considering various levels of positive and negative sentiment intensity. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred.	Tweet: Already plotting next steps if I get cut off by the same minivan in tomorrow's drop-off line. #preschoolpolitics #momthings Intensity class:	-2: moderately negative emotional state can be inferred
Task: Assess the emotional content of the tweet and classify it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best represent the tweeter's mental state.	Tweet: I'm not the type to flee from adversity nor does it discourage me. I'll always stand strong in the paint This tweet contains emotions:	joy, optimism, trust
Task: Analyze the tweet's emotional connotations and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best portray the tweeter's mental state.	Tweet: @caseycdutch @m_rath that's what some rioters are doing #terrorism This tweet contains emotions:	anger, anticipation, disgust, fear, sadness
Task: Categorize the tweet's emotional tone as either 'neutral or no emotion' or identify the presence of one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).	Tweet: When your rewatching glee and break down in tears all over again. 😭😢 This tweet contains emotions:	sadness
Task: Assign the tweet to a specific ordinal class that corresponds to the tweeter's mental state, considering various levels of positive and negative sentiment intensity. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred.	Tweet: Omg I actually thought she was going to jump. #SouthPark20 #southpark Intensity class:	-2: moderately negative emotional state can be inferred
Task: Analyze the tweet's sentiment and assign it to either 'neutral or no emotion' or one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).	Tweet: #GADOT please put a left turn signal at Williams and Ivan Allen Jr Blvd. This is absolutely ridiculous #ATLtraffic #horrible This tweet contains emotions:	anger, disgust, fear
Task: Rate the intensity of emotion E in the tweet on a scale of 0 to 1, with 0 indicating the least intensity and 1 indicating the highest intensity.	Tweet: @SomeonesAnIdiot @Sean10Lynagh due to hearty lawsuit NASCAR will raise beer prices $0.07 to accommodate for losses. Emotion: joy Intensity score:	0.167
Task: Classify the tweet into one of four ordinal classes of intensity of emotion E that best represents the mental state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.	Tweet: now im all alone and my joy's turned to moping Emotion: sadness Intensity class:	3: high amount of sadness can be inferred
Task: Analyze the tweet's sentiment and assign it to either 'neutral or no emotion' or one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).	Tweet: @chocorobos I have this one so I'm not so sad.. but wtf This tweet contains emotions:	anger, anticipation, disgust, optimism, sadness
Task: Determine the prevailing emotional tone of the tweet, categorizing it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that most accurately represent the tweeter's mental state.	Tweet: The 2nd step to beating #anxiety or #depression is realising that it's not about waiting for ...., Take action yourself now. This tweet contains emotions:	fear, joy, optimism, sadness
Task: Determine the appropriate intensity category of emotion E for the tweet, reflecting the emotional state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.	Tweet: @TauDeltaPhiDK THANK YOU FOR MY OBAMA CUT OUT!!!!!! I am elated that he's back home😍 Emotion: joy Intensity class:	3: high amount of joy can be inferred
Task: Classify the tweet into one of seven ordinal classes, corresponding to various levels of positive and negative sentiment intensity, that best represents the mental state of the tweeter. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred.	Tweet: Now I'm going to sulk again for a week until #OurGirl is back on! @michkeegan and @benaldridge07 are the best! @OurGirlWatch Intensity class:	0: neutral or mixed emotional state can be inferred
Task: Categorize the tweet based on the intensity of the specified emotion E, capturing the tweeter's mental state. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.	Tweet: The people that call in to POV on KX4 make my night. Emotion: joy Intensity class:	1: low amount of joy can be inferred
Task: Measure the intensity of sentiment or valence in the tweet, assigning it a score between 0 (highly negative) and 1 (highly positive).	Tweet: The amount of laughter ready to leave my body if United lose is unreal Intensity score:	0.703
Task: Evaluate the tweet for emotional cues and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that indicate the tweeter's state of mind.	Tweet: @Fra93_bruno wow I'm just really sadden by that. Terrible This tweet contains emotions:	disgust, sadness
Task: Determine the appropriate intensity category of emotion E for the tweet, reflecting the emotional state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.	Tweet: Lets get this Astros/A's game going already! We're going to need all 5 of you in attendance to cheer the A's to victory! Emotion: joy Intensity class:	2: moderate amount of joy can be inferred
Task: Estimate the strength of emotion E in the tweet by assigning it a real-valued score between 0 and 1, where 0 signifies the least intensity and 1 signifies the greatest intensity.	Tweet: one of the main things im doing w/ 13c is filling in the void of my empty bitter heart by making everything how i wanted it to be growing up Emotion: anger Intensity score:	0.333
Task: Estimate the strength of emotion E in the tweet by assigning it a real-valued score between 0 and 1, where 0 signifies the least intensity and 1 signifies the greatest intensity.	Tweet: her; i want a playful relationship\nme; kicks her off the couch Emotion: joy Intensity score:	0.375
Task: Classify the mental state of the tweeter based on the tweet, determining if it is 'neutral or no emotion' or characterized by any of the provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).	Tweet: @MaxiNutrition order 321073 parcel 15502922895987. #awful #customercare by @DPD_UK tried to view calling card online. black image #noshow This tweet contains emotions:	anger, disgust, sadness
Task: Classify the tweet into one of four ordinal classes of intensity of emotion E that best represents the mental state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.	Tweet: U know u have too much on ur mind when u find yourself cleaning a stove and kitchen by yourself at almost 3am... #pensive Emotion: sadness Intensity class:	2: moderate amount of sadness can be inferred
Task: Estimate the strength of emotion E in the tweet by assigning it a real-valued score between 0 and 1, where 0 signifies the least intensity and 1 signifies the greatest intensity.	Tweet: “When we give cheerfully and accept gratefully, everyone is blessed.”―Maya Angelou Emotion: joy Intensity score:	0.460
Task: Calculate the intensity of emotion E in the tweet as a decimal value ranging from 0 to 1, with 0 representing the lowest intensity and 1 representing the highest intensity.	Tweet: Forgot to plug the phone in overnight Emotion: fear Intensity score:	0.396
Task: Determine the appropriate intensity class for the tweet, reflecting the level of emotion E experienced by the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.	Tweet: He's mixing it up pretty well..using that slider pretty affective so far #thebabybombers #yankees #offense Emotion: anger Intensity class:	0: no anger can be inferred
Task: Categorize the tweet's emotional tone as either 'neutral or no emotion' or identify the presence of one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).	Tweet: @AmontanaW I nearly dropped my phone into the sink HAHAHAHA This tweet contains emotions:	fear, joy, optimism
Task: Identify the primary emotion conveyed in the tweet and assign it to either 'neutral or no emotion' or one or more of the provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best capture the tweeter's mental state.	Tweet: @josephperson Cam is still rattled from the backlash he received when he made the black QB comment and suffered the wrath of White America. This tweet contains emotions:	anger, disgust, sadness
Task: Classify the tweet into one of seven ordinal classes, corresponding to various levels of positive and negative sentiment intensity, that best represents the mental state of the tweeter. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred.	Tweet: @xiankiefer @TheLincoln Book 5! It's so sprightly & fun cuz he'd been reinvigorated by the Harry Potter series. I'm not kidding. Intensity class:	3: very positive emotional state can be inferred
Task: Assign a numerical value between 0 (least E) and 1 (most E) to represent the intensity of emotion E expressed in the tweet.	Tweet: @RapeseedOilFans \nWho nose where those scent roses went\nTo a spot in the Orient\nMummified\nIn rapeseed oil fried\nEating drinking & merriment. Emotion: joy Intensity score:	0.479
Task: Rate the intensity of emotion E in the tweet on a scale of 0 to 1, with 0 indicating the least intensity and 1 indicating the highest intensity.	Tweet: the sad moment when u hand in an exam knowing u failed and grieve by eating and sleeping Emotion: sadness Intensity score:	0.854
Task: Identify the primary emotion conveyed in the tweet and assign it to either 'neutral or no emotion' or one or more of the provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best capture the tweeter's mental state.	Tweet: @jamieyates That's what we strive for, Jamie! Please don't hesitate to reach out if you have any questions along the way. 🙂 This tweet contains emotions:	anticipation, joy, love, optimism, trust
Task: Evaluate the tweet for emotional cues and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that indicate the tweeter's state of mind.	Tweet: I don't get what point is made when reporting on Charlotte looting @CNNAshleigh. Why not explore what looting businesses symbolizes This tweet contains emotions:	anger, disgust
Task: Categorize the tweet based on the intensity of the specified emotion E, capturing the tweeter's mental state. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.	Tweet: having a pet store worker ask 'do you want to play with them?' is the most exhilarating feeling Emotion: joy Intensity class:	3: high amount of joy can be inferred
Task: Classify the mental state of the tweeter based on the tweet, determining if it is 'neutral or no emotion' or characterized by any of the provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).	Tweet: I lost my blinders .... #panic This tweet contains emotions:	fear
Task: Classify the tweet into one of four ordinal intensity levels, indicating the degree of emotion E experienced by the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.	Tweet: People you need to look up the definition of protest. What you are doing is not protesting is called vandalism. #stop Emotion: anger Intensity class:	3: high amount of anger can be inferred
Task: Categorize the tweet's emotional expression, classifying it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that reflect the tweeter's state of mind.	Tweet: Love how cheerful that woman is about storing someone else's furniture for an eternity. I'd have sold it by now. #GrandDesigns This tweet contains emotions:	joy, love, optimism
Task: Rate the intensity of emotion E in the tweet on a scale of 0 to 1, with 0 indicating the least intensity and 1 indicating the highest intensity.	Tweet: @rohan_connolly i think your high-profile female colleague would be one in yhat category... #massexodus #bitter Emotion: anger Intensity score:	0.396
Task: Evaluate the tweet for emotional cues and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that indicate the tweeter's state of mind.	Tweet: I should really study today for chemistry but playing madden is just way more fun. This tweet contains emotions:	anticipation, fear, joy, surprise
Task: Analyze the tweet's emotional connotations and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best portray the tweeter's mental state.	Tweet: I'm honestly upset that they rewarded Nicole 500k. #depressing #paulwasrobbed #rewardhardwork #bitterjury #bb18 This tweet contains emotions:	anger, disgust, pessimism, sadness
Task: Assign the tweet to a specific ordinal class that corresponds to the tweeter's mental state, considering various levels of positive and negative sentiment intensity. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred.	Tweet: but that was a mistake and a half assed excuse and now here i am burning in hell forever Intensity class:	-2: moderately negative emotional state can be inferred
Task: Analyze the tweet's emotional connotations and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best portray the tweeter's mental state.	Tweet: smh customers getting angry at me bc i aint got no marlboro lights in the gas hut. i called them in 2 hours ago, fuck you. This tweet contains emotions:	anger, disgust
Task: Measure the level of emotion E in the tweet using a real-valued score between 0 and 1, where 0 represents the lowest intensity and 1 represents the highest intensity.	Tweet: @JTregManc it's fair to say he's been a bit timid compared to what I've been known to see from him Emotion: fear Intensity score:	0.458
Task: Assign a suitable level of intensity of emotion E to the tweet, representing the emotional state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.	Tweet: Another loss to city in the cup next 🙈 😂😂 cmon united! Emotion: anger Intensity class:	0: no anger can be inferred
Task: Place the tweet into a specific intensity class, reflecting the intensity of the mentioned emotion E and the user's mental state. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.	Tweet: Quinn's short hair makes me sad. #glee Emotion: joy Intensity class:	0: no joy can be inferred
Task: Analyze the tweet's emotional connotations and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best portray the tweeter's mental state.	Tweet: I can't guess if you holding a grudge against the best' This tweet contains emotions:	anger, sadness
Task: Categorize the tweet based on the intensity of the specified emotion E, capturing the tweeter's mental state. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.	Tweet: @Cinestrong something a cyber bully would say Emotion: fear Intensity class:	0: no fear can be inferred
Task: Analyze the tweet's sentiment and assign it to either 'neutral or no emotion' or one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).	Tweet: That AK47 leave your spine with a frown This tweet contains emotions:	anger, disgust, fear, pessimism
Task: Evaluate the strength of emotion E in the tweet, providing a real-valued score from 0 to 1. A score of 0 denotes the absence of the emotion, while a score of 1 indicates the highest degree of intensity.	Tweet: Accept the challenges so that you can feel the exhilaration of victory.' - George S. Patton Emotion: joy Intensity score:	0.500
Task: Determine the appropriate intensity category of emotion E for the tweet, reflecting the emotional state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.	Tweet: I never let anything below me concern me. Emotion: fear Intensity class:	0: no fear can be inferred
Task: Determine the most suitable ordinal classification for the tweet, capturing the emotional state of the tweeter through a range of positive and negative sentiment intensity levels. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred.	Tweet: 2 applications for my dbs and still waiting. Been over a year now. Going to loose my job 👍🏿 @GOVUK #thanks #unhappy #crb Intensity class:	-2: moderately negative emotional state can be inferred

Task: Gauge the level of intensity for emotion E in the tweet, assigning it a score between 0 and 1. A score of 0 indicates the lowest intensity, while a score of 1 indicates the highest intensity.

Tweet: Boys Dm me pictures of your cocks! The best one will get uploaded! ☺️💦💦 #Cumtribute #dm #snapchat #snapme #nudes #dickpic #cocktribute Emotion: anger Intensity score:

0.396

Task: Classify the tweet into one of four ordinal intensity levels, indicating the degree of emotion E experienced by the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.

Tweet: Overtime... #TeamNA #WCH2016 Emotion: fear Intensity class:

0: no fear can be inferred

Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E).

Tweet: @NFLonFOX @TheDoctorCarson @FOXSports Easy, breezy, beautiful... Emotion: joy Intensity score:

0.604

Task: Evaluate the tweet for emotional cues and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that indicate the tweeter's state of mind.

Tweet: ... flat party and I instantly get bollocked about it. This tweet contains emotions:

Task: Analyze the tweet's sentiment and assign it to either 'neutral or no emotion' or one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).

Tweet: @OniLink86 @DarekMeridian lmao awe... #sad This tweet contains emotions:

sadness

Task: Classify the tweet into one of four ordinal classes of intensity of emotion E that best represents the mental state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.

Tweet: @andreasarahco do you actually heely on campus bc this should scare you Emotion: fear Intensity class:

1: low amount of fear can be inferred

Task: Determine the prevailing emotional tone of the tweet, categorizing it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that most accurately represent the tweeter's mental state.

Tweet: I forgot about this nice area down here with the fiery hearths This tweet contains emotions:

anticipation, joy, optimism

Task: Assign the tweet to one of seven ordinal classes, each representing a distinct level of positive or negative sentiment intensity, reflecting the mental state of the tweeter. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred.

Tweet: @Ginger_Naylor *Connie came back in* Hey you seem a bit more lively Intensity class:

0: neutral or mixed emotional state can be inferred

Task: Estimate the strength of emotion E in the tweet by assigning it a real-valued score between 0 and 1, where 0 signifies the least intensity and 1 signifies the greatest intensity.

Tweet: @RonMexico760 The guy who calls people 'cuck' and is anti-BLM is offended by idea that he might not be pro-policing reform? That's amazing. Emotion: anger Intensity score:

0.625

Task: Assign one of four ordinal intensity classes of emotion E to a given tweet based on the emotional state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.

Tweet: @_stfukohle it's ok champ you'll make it I'm cheering you on from a far Emotion: joy Intensity class:

2: moderate amount of joy can be inferred

Task: Evaluate the strength of emotion E in the tweet, providing a real-valued score from 0 to 1. A score of 0 denotes the absence of the emotion, while a score of 1 indicates the highest degree of intensity.

Tweet: Be #happy. Be #bright. Be YOU :) #identity #TimelessTips #friendship #family #forest #water #family #TrueLove #God #RoadSoFar #you #LifeTrip Emotion: joy Intensity score:

0.708

Task: Determine the appropriate intensity class for the tweet, reflecting the level of emotion E experienced by the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.

Tweet: When it comes to Syria, I get very fucking annoyed at pessimism, like I get full on triggered. Optimism or gtfo. Emotion: sadness Intensity class:

2: moderate amount of sadness can be inferred

Task: Categorize the tweet into one of seven ordinal classes, representing different degrees of positive and negative sentiment intensity, that most accurately reflects the emotional state of the Twitter user. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred.

Tweet: @amychozick @jswatz Not a word about terrorism. Intensity class:

0: neutral or mixed emotional state can be inferred

Task: Rate the intensity of emotion E in the tweet on a scale of 0 to 1, with 0 indicating the least intensity and 1 indicating the highest intensity.

Tweet: Kik me I want to swap pics I will post on my account anonymously if you wish Kik: vsvplou #Kik #kikme #nudes #tits #snapchat Emotion: anger Intensity score:

0.188

Task: Rate the intensity of emotion E in the tweet on a scale of 0 to 1, with 0 indicating the least intensity and 1 indicating the highest intensity.

Tweet: You dont have to feel grateful to be grateful, for it is written ' all things work together for good' for those who love God. #cheerful Emotion: joy Intensity score:

0.623

Task: Determine the appropriate intensity class for the tweet, reflecting the level of emotion E experienced by the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.

Tweet: 10 page script due Friday for class. Who said I could do this MFA thing? #panic #GradSchoolProblems #someonetelltinafeytohireme Emotion: fear Intensity class:

3: high amount of fear can be inferred

Task: Estimate the strength of emotion E in the tweet by assigning it a real-valued score between 0 and 1, where 0 signifies the least intensity and 1 signifies the greatest intensity.

Tweet: @cazzrhughes its reflective of the current political debate #awful Emotion: fear Intensity score:

0.508

Task: Classify the tweet into one of four ordinal intensity levels, indicating the degree of emotion E experienced by the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.

Tweet: Isaiah 40:31\nthose who trust in the Lord will find new strength.\nThey will soar high on wings like eagles.\nThey will run and not grow weary. Emotion: sadness Intensity class:

0: no sadness can be inferred

Task: Classify the tweet's emotional intensity into one of four ordinal levels of emotion E, providing insights into the mental state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.

Tweet: Ready for that nice, breezy, calm, sunshine weather.🍂🍁 #Autumn Emotion: joy Intensity class:

2: moderate amount of joy can be inferred

Task: Evaluate the strength of emotion E in the tweet, providing a real-valued score from 0 to 1. A score of 0 denotes the absence of the emotion, while a score of 1 indicates the highest degree of intensity.

Tweet: @RealJeffsdomain Wolfpack theme and trons and sting wore the wolf shirt Emotion: anger Intensity score:

0.312

Task: Identify the primary emotion conveyed in the tweet and assign it to either 'neutral or no emotion' or one or more of the provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best capture the tweeter's mental state.

Tweet: If you really care like you state @flyfrontier @FrontierCare then I would seriously address sensitivity training to your employees This tweet contains emotions:

anticipation, optimism

Task: Classify the tweet into one of four ordinal classes of intensity of emotion E that best represents the mental state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.

Tweet: @mylittlepwnies3 \n> #terrorism coffee addict\n> blocks cats, writers, artists and hedonists Emotion: fear Intensity class:

0: no fear can be inferred

Task: Gauge the level of intensity for emotion E in the tweet, assigning it a score between 0 and 1. A score of 0 indicates the lowest intensity, while a score of 1 indicates the highest intensity.

Tweet: Being alone is better than being lonely. Know what is worse than being lonely? Being empty; that's right!\n#Loneliness #aloneinthecity #fear Emotion: fear Intensity score:

0.729

Task: Rate the intensity of emotion E in the tweet on a scale of 0 to 1, with 0 indicating the least intensity and 1 indicating the highest intensity.

Tweet: @SeanUnfiltered Texans are scared of this bunch! Emotion: fear Intensity score:

0.600

Task: Measure the level of emotion E in the tweet using a real-valued score between 0 and 1, where 0 represents the lowest intensity and 1 represents the highest intensity.

Tweet: @LucidBurrito Doesnt do it to anyone else, he literally pulled me into the office cause someone complained I spit in the sink yesterday Emotion: sadness Intensity score:

0.457

Task: Analyze the tweet's emotional connotations and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best portray the tweeter's mental state.

Tweet: #Gratitude - recovery health love God conscious drive hope perseverance wealthy home kids SoCal #recoveryfit youthful #sober This tweet contains emotions:

joy, optimism

Task: Determine the appropriate intensity category of emotion E for the tweet, reflecting the emotional state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.

Tweet: Love takes off the masks that we fear we cannot live without and know we cannot live within. - James A. Baldwin Emotion: fear Intensity class:

0: no fear can be inferred

Task: Assign one of four ordinal intensity classes of emotion E to a given tweet based on the emotional state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.

Tweet: MC: what are you listen to these days?\nBogum: these days I feel gloomy, I listen to ccm (spiritual song) often.\n\nChurch oppa mode. :) Emotion: sadness Intensity class:

2: moderate amount of sadness can be inferred

Task: Assess the magnitude of emotion E in the tweet using a real number between 0 and 1, where 0 denotes the least intensity and 1 denotes the most intensity.

Tweet: So now... yeah. I'm home again.\nStill feeling mixed up inside & kinda gloomy. But a little more optimistic that I'll figure this out. Emotion: sadness Intensity score:

0.521

Task: Gauge the level of intensity for emotion E in the tweet, assigning it a score between 0 and 1. A score of 0 indicates the lowest intensity, while a score of 1 indicates the highest intensity.

Tweet: @SkyUK what a joke!! Cut our internet off early 'by mistake' and then don't reinstate it when we no longer need an engineer 😡 #fuming Emotion: anger Intensity score:

0.646

Task: Assign a suitable level of intensity of emotion E to the tweet, representing the emotional state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.

Tweet: @realDonaldTrump negative campaign of doom and gloom don't win elections Emotion: sadness Intensity class:

1: low amount of sadness can be inferred

Task: Determine the appropriate ordinal classification for the tweet, reflecting the tweeter's mental state based on the magnitude of positive and negative sentiment intensity conveyed. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred.

Tweet: You forever straight so fix that frown u good😇 @amayyaaag__ Intensity class:

1: slightly positive emotional state can be inferred

Task: Determine the appropriate intensity class for the tweet, reflecting the level of emotion E experienced by the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.

Tweet: @BjerkeDanielle @FunnySayings lol that's hilarious Emotion: joy Intensity class:

3: high amount of joy can be inferred

Task: Determine the degree of intensity for emotion E in the tweet, giving it a score between 0 and 1, where 0 signifies the least intensity and 1 signifies the greatest intensity.

Tweet: @LuluLemonLime83 wow , your right they do need help,so what I'm getting from the Laureliver fandom and bitter comic fandom and Emotion: anger Intensity score:

0.479

Task: Assess the emotional content of the tweet and classify it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best represent the tweeter's mental state.

Tweet: @megynkelly We should be ignoring these rioters like the current administration ignores #terrorism. This will obviously make it stop. This tweet contains emotions:

anger, disgust, fear

Task: Categorize the tweet into an intensity level of the specified emotion E, representing the mental state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.

Tweet: @eliroth ya know I love ya man, but #TheGreenInferno really fucked with my head....(giggle)..do it again. #epic #ineedtherapy Emotion: fear Intensity class:

0: no fear can be inferred

Task: Evaluate the tweet for emotional cues and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that indicate the tweeter's state of mind.

Tweet: @keithboykin unfortunately it won't end there... followers of whichever candidate isn't elected will throw tantrums. No winning this elec This tweet contains emotions:

anger, sadness

Task: Categorize the tweet into an ordinal class that best characterizes the tweeter's mental state, considering various degrees of positive and negative sentiment intensity. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred.

Tweet: Some Erykah Badu to sedate me 💕 Intensity class:

1: slightly positive emotional state can be inferred

Task: Classify the tweet into one of seven ordinal classes, corresponding to various levels of positive and negative sentiment intensity, that best represents the mental state of the tweeter. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred.

Tweet: @everycolorbot more like every color looks the same #triggered #colorblind #offended Intensity class:

-1: slightly negative emotional state can be inferred

Task: Categorize the tweet's emotional tone as either 'neutral or no emotion' or identify the presence of one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).

Tweet: On the last episode of #MakingAMurderer poor Brendan glad they #appeal it #shocking #crime #documentary #reallife This tweet contains emotions:

surprise

Task: Classify the tweet into one of seven ordinal categories, indicating the intensity of positive or negative sentiment expressed by the tweeter and reflecting their current mental state. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred.

Tweet: Take my kindness for weakness when you acting silly keeping it 100 ain't your forté #ChrisBrown #TeamBreezy Intensity class:

0: neutral or mixed emotional state can be inferred

Task: Evaluate the tweet for emotional cues and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that indicate the tweeter's state of mind.

Tweet: $FOGO max pessimism here and no bottom (yet). Has a solid PE ratio for a restaurant. Let's catch it at 8 level or 10 level if it comes. This tweet contains emotions:

joy, pessimism

Task: Categorize the tweet into one of seven ordinal classes, representing different degrees of positive and negative sentiment intensity, that most accurately reflects the emotional state of the Twitter user. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred.

Tweet: Scott Dann injured aka my worst nightmare Intensity class:

-3: very negative emotional state can be inferred

Task: Assess the emotional content of the tweet and classify it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best represent the tweeter's mental state.

Tweet: I only have to wave a fiery cross and we will f**kin' do this! This tweet contains emotions:

anger, anticipation, optimism

Task: Analyze the tweet's sentiment and assign it to either 'neutral or no emotion' or one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).

Tweet: I'm still laughing 'Bitch took my pillow' line #kurt This tweet contains emotions:

joy, optimism

Task: Measure the level of emotion E in the tweet using a real-valued score between 0 and 1, where 0 represents the lowest intensity and 1 represents the highest intensity.

Tweet: @XemitSellsMagic add tracking but resent them Emotion: anger Intensity score:

0.688

Task: Classify the mental state of the tweeter based on the tweet, determining if it is 'neutral or no emotion' or characterized by any of the provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).

Tweet: I'm really hitting all flavors of my sparkling water rap. But you know what's tripping me out? These half French and Spanish flavors. This tweet contains emotions:

joy, love

Task: Calculate the intensity of emotion E in the tweet as a decimal value ranging from 0 to 1, with 0 representing the lowest intensity and 1 representing the highest intensity.

Tweet: @SkySportsRL i would just get some decent referees #shocking Emotion: fear Intensity score:

0.312

Task: Classify the tweet into one of four ordinal intensity levels, indicating the degree of emotion E experienced by the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.

Tweet: SO many great pics from the show in Tokyo😍 I like all his outfits now except the lace one w those horrible pants....💁 Emotion: fear Intensity class:

0: no fear can be inferred

Task: Classify the mental state of the tweeter based on the tweet, determining if it is 'neutral or no emotion' or characterized by any of the provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).

Tweet: @BokuNoGio AND his momma was worse than Tony sopranos momma #wow #sad #history #major This tweet contains emotions:

disgust, sadness

Task: Determine the dominant emotion in the tweet and classify it as either 'neutral or no emotion' or one of the eleven provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).

Tweet: Always do sober what you said you'd do drunk. That will teach you to keep your mouth shut. \n― Ernest Hemingway #quote This tweet contains emotions:

optimism, trust

Task: Categorize the tweet based on the intensity of the specified emotion E, capturing the tweeter's mental state. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.

Tweet: @Docjp they unleashing God's wrath just as Cain did Emotion: anger Intensity class:

1: low amount of anger can be inferred

Task: Assign the tweet to a specific ordinal class that corresponds to the tweeter's mental state, considering various levels of positive and negative sentiment intensity. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred.

Tweet: Already plotting next steps if I get cut off by the same minivan in tomorrow's drop-off line. #preschoolpolitics #momthings Intensity class:

-2: moderately negative emotional state can be inferred

Task: Assess the emotional content of the tweet and classify it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best represent the tweeter's mental state.

Tweet: I'm not the type to flee from adversity nor does it discourage me. I'll always stand strong in the paint This tweet contains emotions:

joy, optimism, trust

Task: Analyze the tweet's emotional connotations and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best portray the tweeter's mental state.

Tweet: @caseycdutch @m_rath that's what some rioters are doing #terrorism This tweet contains emotions:

anger, anticipation, disgust, fear, sadness

Task: Categorize the tweet's emotional tone as either 'neutral or no emotion' or identify the presence of one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).

Tweet: When your rewatching glee and break down in tears all over again. 😭😢 This tweet contains emotions:

sadness

Task: Assign the tweet to a specific ordinal class that corresponds to the tweeter's mental state, considering various levels of positive and negative sentiment intensity. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred.

Tweet: Omg I actually thought she was going to jump. #SouthPark20 #southpark Intensity class:

-2: moderately negative emotional state can be inferred

Task: Analyze the tweet's sentiment and assign it to either 'neutral or no emotion' or one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).

Tweet: #GADOT please put a left turn signal at Williams and Ivan Allen Jr Blvd. This is absolutely ridiculous #ATLtraffic #horrible This tweet contains emotions:

anger, disgust, fear

Task: Rate the intensity of emotion E in the tweet on a scale of 0 to 1, with 0 indicating the least intensity and 1 indicating the highest intensity.

Tweet: @SomeonesAnIdiot @Sean10Lynagh due to hearty lawsuit NASCAR will raise beer prices $0.07 to accommodate for losses. Emotion: joy Intensity score:

0.167

Task: Classify the tweet into one of four ordinal classes of intensity of emotion E that best represents the mental state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.

Tweet: now im all alone and my joy's turned to moping Emotion: sadness Intensity class:

3: high amount of sadness can be inferred

Task: Analyze the tweet's sentiment and assign it to either 'neutral or no emotion' or one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).

Tweet: @chocorobos I have this one so I'm not so sad.. but wtf This tweet contains emotions:

anger, anticipation, disgust, optimism, sadness

Task: Determine the prevailing emotional tone of the tweet, categorizing it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that most accurately represent the tweeter's mental state.

Tweet: The 2nd step to beating #anxiety or #depression is realising that it's not about waiting for ...., Take action yourself now. This tweet contains emotions:

fear, joy, optimism, sadness

Task: Determine the appropriate intensity category of emotion E for the tweet, reflecting the emotional state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.

Tweet: @TauDeltaPhiDK THANK YOU FOR MY OBAMA CUT OUT!!!!!! I am elated that he's back home😍 Emotion: joy Intensity class:

3: high amount of joy can be inferred

Task: Classify the tweet into one of seven ordinal classes, corresponding to various levels of positive and negative sentiment intensity, that best represents the mental state of the tweeter. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred.

Tweet: Now I'm going to sulk again for a week until #OurGirl is back on! @michkeegan and @benaldridge07 are the best! @OurGirlWatch Intensity class:

0: neutral or mixed emotional state can be inferred

Task: Categorize the tweet based on the intensity of the specified emotion E, capturing the tweeter's mental state. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.

Tweet: The people that call in to POV on KX4 make my night. Emotion: joy Intensity class:

1: low amount of joy can be inferred

Task: Measure the intensity of sentiment or valence in the tweet, assigning it a score between 0 (highly negative) and 1 (highly positive).

Tweet: The amount of laughter ready to leave my body if United lose is unreal Intensity score:

0.703

Task: Evaluate the tweet for emotional cues and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that indicate the tweeter's state of mind.

Tweet: @Fra93_bruno wow I'm just really sadden by that. Terrible This tweet contains emotions:

disgust, sadness

Task: Determine the appropriate intensity category of emotion E for the tweet, reflecting the emotional state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.

Tweet: Lets get this Astros/A's game going already! We're going to need all 5 of you in attendance to cheer the A's to victory! Emotion: joy Intensity class:

2: moderate amount of joy can be inferred

Task: Estimate the strength of emotion E in the tweet by assigning it a real-valued score between 0 and 1, where 0 signifies the least intensity and 1 signifies the greatest intensity.

Tweet: one of the main things im doing w/ 13c is filling in the void of my empty bitter heart by making everything how i wanted it to be growing up Emotion: anger Intensity score:

0.333

Task: Estimate the strength of emotion E in the tweet by assigning it a real-valued score between 0 and 1, where 0 signifies the least intensity and 1 signifies the greatest intensity.

Tweet: her; i want a playful relationship\nme; *kicks her off the couch* Emotion: joy Intensity score:

0.375

Task: Classify the mental state of the tweeter based on the tweet, determining if it is 'neutral or no emotion' or characterized by any of the provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).

Tweet: @MaxiNutrition order 321073 parcel 15502922895987. #awful #customercare by @DPD_UK tried to view calling card online. black image #noshow This tweet contains emotions:

anger, disgust, sadness

Task: Classify the tweet into one of four ordinal classes of intensity of emotion E that best represents the mental state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.

Tweet: U know u have too much on ur mind when u find yourself cleaning a stove and kitchen by yourself at almost 3am... #pensive Emotion: sadness Intensity class:

2: moderate amount of sadness can be inferred

Task: Estimate the strength of emotion E in the tweet by assigning it a real-valued score between 0 and 1, where 0 signifies the least intensity and 1 signifies the greatest intensity.

Tweet: “When we give cheerfully and accept gratefully, everyone is blessed.”―Maya Angelou Emotion: joy Intensity score:

0.460

Task: Calculate the intensity of emotion E in the tweet as a decimal value ranging from 0 to 1, with 0 representing the lowest intensity and 1 representing the highest intensity.

Tweet: Forgot to plug the phone in overnight Emotion: fear Intensity score:

0.396

Task: Determine the appropriate intensity class for the tweet, reflecting the level of emotion E experienced by the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.

Tweet: He's mixing it up pretty well..using that slider pretty affective so far #thebabybombers #yankees #offense Emotion: anger Intensity class:

0: no anger can be inferred

Task: Categorize the tweet's emotional tone as either 'neutral or no emotion' or identify the presence of one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).

Tweet: @AmontanaW I nearly dropped my phone into the sink HAHAHAHA This tweet contains emotions:

fear, joy, optimism

Task: Identify the primary emotion conveyed in the tweet and assign it to either 'neutral or no emotion' or one or more of the provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best capture the tweeter's mental state.

Tweet: @josephperson Cam is still rattled from the backlash he received when he made the black QB comment and suffered the wrath of White America. This tweet contains emotions:

anger, disgust, sadness

Task: Classify the tweet into one of seven ordinal classes, corresponding to various levels of positive and negative sentiment intensity, that best represents the mental state of the tweeter. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred.

Tweet: @xiankiefer @TheLincoln Book 5! It's so sprightly & fun cuz he'd been reinvigorated by the Harry Potter series. I'm not kidding. Intensity class:

3: very positive emotional state can be inferred

Task: Assign a numerical value between 0 (least E) and 1 (most E) to represent the intensity of emotion E expressed in the tweet.

Tweet: @RapeseedOilFans \nWho nose where those scent roses went\nTo a spot in the Orient\nMummified\nIn rapeseed oil fried\nEating drinking & merriment. Emotion: joy Intensity score:

0.479

Task: Rate the intensity of emotion E in the tweet on a scale of 0 to 1, with 0 indicating the least intensity and 1 indicating the highest intensity.

Tweet: the sad moment when u hand in an exam knowing u failed and grieve by eating and sleeping Emotion: sadness Intensity score:

0.854

Task: Identify the primary emotion conveyed in the tweet and assign it to either 'neutral or no emotion' or one or more of the provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best capture the tweeter's mental state.

Tweet: @jamieyates That's what we strive for, Jamie! Please don't hesitate to reach out if you have any questions along the way. 🙂 This tweet contains emotions:

anticipation, joy, love, optimism, trust

Task: Evaluate the tweet for emotional cues and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that indicate the tweeter's state of mind.

Tweet: I don't get what point is made when reporting on Charlotte looting @CNNAshleigh. Why not explore what looting businesses symbolizes This tweet contains emotions:

anger, disgust

Task: Categorize the tweet based on the intensity of the specified emotion E, capturing the tweeter's mental state. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.

Tweet: having a pet store worker ask 'do you want to play with them?' is the most exhilarating feeling Emotion: joy Intensity class:

3: high amount of joy can be inferred

Task: Classify the mental state of the tweeter based on the tweet, determining if it is 'neutral or no emotion' or characterized by any of the provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).

Tweet: I lost my blinders .... #panic This tweet contains emotions:

fear

Task: Classify the tweet into one of four ordinal intensity levels, indicating the degree of emotion E experienced by the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.

Tweet: People you need to look up the definition of protest. What you are doing is not protesting is called vandalism. #stop Emotion: anger Intensity class:

3: high amount of anger can be inferred

Task: Categorize the tweet's emotional expression, classifying it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that reflect the tweeter's state of mind.

Tweet: Love how cheerful that woman is about storing someone else's furniture for an eternity. I'd have sold it by now. #GrandDesigns This tweet contains emotions:

joy, love, optimism

Task: Rate the intensity of emotion E in the tweet on a scale of 0 to 1, with 0 indicating the least intensity and 1 indicating the highest intensity.

Tweet: @rohan_connolly i think your high-profile female colleague would be one in yhat category... #massexodus #bitter Emotion: anger Intensity score:

0.396

Task: Evaluate the tweet for emotional cues and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that indicate the tweeter's state of mind.

Tweet: I should really study today for chemistry but playing madden is just way more fun. This tweet contains emotions:

anticipation, fear, joy, surprise

Task: Analyze the tweet's emotional connotations and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best portray the tweeter's mental state.

Tweet: I'm honestly upset that they rewarded Nicole 500k. #depressing #paulwasrobbed #rewardhardwork #bitterjury #bb18 This tweet contains emotions:

anger, disgust, pessimism, sadness

Task: Assign the tweet to a specific ordinal class that corresponds to the tweeter's mental state, considering various levels of positive and negative sentiment intensity. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred.

Tweet: but that was a mistake and a half assed excuse and now here i am burning in hell forever Intensity class:

-2: moderately negative emotional state can be inferred

Task: Analyze the tweet's emotional connotations and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best portray the tweeter's mental state.

Tweet: smh customers getting angry at me bc i aint got no marlboro lights in the gas hut. i called them in 2 hours ago, fuck you. This tweet contains emotions:

anger, disgust

Task: Measure the level of emotion E in the tweet using a real-valued score between 0 and 1, where 0 represents the lowest intensity and 1 represents the highest intensity.

Tweet: @JTregManc it's fair to say he's been a bit timid compared to what I've been known to see from him Emotion: fear Intensity score:

0.458

Task: Assign a suitable level of intensity of emotion E to the tweet, representing the emotional state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.

Tweet: Another loss to city in the cup next 🙈 😂😂 cmon united! Emotion: anger Intensity class:

0: no anger can be inferred

Task: Place the tweet into a specific intensity class, reflecting the intensity of the mentioned emotion E and the user's mental state. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.

Tweet: Quinn's short hair makes me sad. #glee Emotion: joy Intensity class:

0: no joy can be inferred

Task: Analyze the tweet's emotional connotations and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best portray the tweeter's mental state.

Tweet: I can't guess if you holding a grudge against the best' This tweet contains emotions:

anger, sadness

Task: Categorize the tweet based on the intensity of the specified emotion E, capturing the tweeter's mental state. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.

Tweet: @Cinestrong something a cyber bully would say Emotion: fear Intensity class:

0: no fear can be inferred

Task: Analyze the tweet's sentiment and assign it to either 'neutral or no emotion' or one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).

Tweet: That AK47 leave your spine with a frown This tweet contains emotions:

anger, disgust, fear, pessimism

Task: Evaluate the strength of emotion E in the tweet, providing a real-valued score from 0 to 1. A score of 0 denotes the absence of the emotion, while a score of 1 indicates the highest degree of intensity.

Tweet: Accept the challenges so that you can feel the exhilaration of victory.' - George S. Patton Emotion: joy Intensity score:

0.500

Task: Determine the appropriate intensity category of emotion E for the tweet, reflecting the emotional state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.

Tweet: I never let anything below me concern me. Emotion: fear Intensity class:

0: no fear can be inferred

Task: Determine the most suitable ordinal classification for the tweet, capturing the emotional state of the tweeter through a range of positive and negative sentiment intensity levels. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred.

Tweet: 2 applications for my dbs and still waiting. Been over a year now. Going to loose my job 👍🏿 @GOVUK #thanks #unhappy #crb Intensity class:

-2: moderately negative emotional state can be inferred