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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: I went to this sushi spot & they had tobi & an ANBU mask hung on the wall behind them. I will start going there even tho I don't eat seafood
This tweet contains emotions:
|
anticipation, joy, optimism
|
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: Morning all! Of course it is sunny on this Monday morning to cheerfully welcome us back to work.:)
Emotion: joy
Intensity score:
|
0.863
|
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: Catering channel's at the height technics hearty enjoyment symptomatize: vrlfEyrN
Emotion: joy
Intensity score:
|
0.542
|
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: @OC_Transpo some weeks there are no problems but this week is unbelievable -- are you guys even running regular 12 buses? #awful #solate
Emotion: fear
Intensity score:
|
0.456
|
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: @lucy_hyner @Soulboy2266 sadly not !! One less hour drinking time 😢🍻
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: @AaliyahLove69 I would be intimidated but I would like to think I would have manned up and helped.
This tweet contains emotions:
|
anticipation, disgust
|
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: Well that was exhilarating. I didn't know you could have goosebumps for 2 hrs 5m straight.
Intensity class:
|
2: moderately positive emotional state can be inferred
|
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: But 'for me not to worry, they'll get a glass guy over and bill us for it'
Emotion: fear
Intensity class:
|
0: no fear 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: — Self-hatred gives rise to fury, fury to the desire for self-change.
Emotion: anger
Intensity score:
|
0.458
|
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: Feminists should ask themselves, why they're so unhappy, and why they lack love in their lives. Is it b/c they are fighting a losing game?
Emotion: sadness
Intensity score:
|
0.458
|
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: @delta correction 26 ppl. Checked in. Standing at the gate. & Flt 1449 took off without us. #furious
Emotion: anger
Intensity score:
|
0.646
|
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: @LVLMLeah Nooooooooooooooooooooo. We have stupid, dismal, lame winters where we maybe get some dangerous ice once.
This tweet contains emotions:
|
anger, disgust, fear
|
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: Add Donte Moncrief to my dismal situation #blessed.
Intensity class:
|
0: neutral or mixed emotional state can be inferred
|
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: if u have time 2 open a snap, u have time 2 respond
Emotion: anger
Intensity class:
|
0: no anger can be inferred
|
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: Just rough situations all around for Schalke and Werder Bremen to start the campaign. Bremen dashed late with a new manager. Both with 0.
Emotion: sadness
Intensity class:
|
1: low amount of sadness 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: @LaurenBrierley2 sparkling water = death
Emotion: joy
Intensity score:
|
0.125
|
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: @RayGemini I've got 8 coming back this week. It's so joyous isn't it haha
This tweet contains emotions:
|
joy, love, 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: @KevinI @GGGBoxing @SpecialKBrook pretty average, klitschko fury did about 600k and Joshua white did about 450k
Emotion: anger
Intensity score:
|
0.417
|
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: In the name of our Lord & Saviour Harambe we pray, bless all apes across the world.\n\nHear our solemn oaths and pardon sympathetic hominids.
This tweet contains emotions:
|
joy, optimism, trust
|
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: Itching something #serious RN haven't slept but considering taking like 6 Benadryl for a 20 min nap I am itching SO BADLY wow
Emotion: sadness
Intensity score:
|
0.542
|
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: Manchester derby at home
Emotion: anger
Intensity score:
|
0.188
|
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: @abbeygray14 they're revolting
Emotion: fear
Intensity class:
|
0: no fear 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: If I could turn anxiety off--I would. #nooneunderstands
Emotion: fear
Intensity class:
|
3: high amount of fear can be inferred
|
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: #Talking about our #Problems is our greatest #Addiction#Break the #habitTalk about ur #Joys#quote #optimism #problemsolving #behappy
Emotion: joy
Intensity class:
|
0: no 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: @ChrisWarcraft species cf. Don Jr. refugees/Skittles.know he likes his snacks,but even @gop frown on talking about eating humans #lizardscum
Emotion: anger
Intensity score:
|
0.458
|
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: Rear garden alarm activated at Telford house at 106.4.
This tweet contains emotions:
|
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: So excited to watch @RuPaulsDragRace #allstars \n#RuPaul #revenge
This tweet contains emotions:
|
anger, joy
|
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: Americans as a whole are, for the most part, feeling borderline despair at the very least. Looking at a situation out of control.
Emotion: sadness
Intensity class:
|
3: high amount of sadness 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: @pi6ie I want to achieve to your level of optimism
This tweet contains emotions:
|
optimism
|
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: @partydelightsUK it's 5679787. Cannot DM you as we don't follow each other. Not such a #delight #party #fail #letdown
This tweet contains emotions:
|
anger, sadness
|
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E).
|
Tweet: @RobRiggle @joelmchale @NFLonFOX I still can't get jimmy garoppolo out of my head and it's been almost 3 weeks. Thanks a lot!
Emotion: joy
Intensity score:
|
0.500
|
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: #ArchangelSummit @sethgodin Anyone can be brave but you just have to last 5 mins longer than everyone else. #leadership #fear
Emotion: fear
Intensity class:
|
0: no fear 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: I'm so so so excited for #UsernameRegenerated I can't wait! I wish I could get a signed copy! I'm so happy for you. @Joe_Sugg
Emotion: joy
Intensity class:
|
3: high amount of joy can be inferred
|
Task: Quantify the sentiment intensity or valence level of the tweet, giving it a score between 0 (highly negative) and 1 (highly positive).
|
Tweet: Somebody who has braved the storm is brewing. #cheerful
Intensity score:
|
0.774
|
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: It feels like there are no houses out there for us. With the most basic requirements I have, there are literally no options. #discouraged
Emotion: sadness
Intensity score:
|
0.729
|
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: come to the funeral tomorrow at 12 to mourn the death of my gpa
This tweet contains emotions:
|
sadness
|
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: @AshleyCWilson @MrDavidHobbs @IndyCaronNBCSN Glad the TV coverage was so successful because the attendance looked pretty dismal.
Emotion: sadness
Intensity score:
|
0.438
|
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: Make someone happy ^_^
Emotion: joy
Intensity score:
|
0.604
|
Task: Rate the valence intensity of the tweeter's mental state expressed in the tweet, assigning it a score on a scale of 0 (most negative) to 1 (most positive).
|
Tweet: @OrbsOfJoy plan a date... like a date u find pleasing or smth. fuckign\n\n10/10. because the child will grow to be a ten out of ten
Intensity score:
|
0.565
|
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: @Tanzynia sadly David D is no longer with us imagine both together wow
Emotion: sadness
Intensity class:
|
1: low amount of sadness can be inferred
|
Task: Place the tweet into a specific ordinal class, which captures the tweeter's mental state by considering different 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: I feel so blessed to work with the family that I nanny for ❤️ nothing but love & appreciation, makes me smile.
Intensity class:
|
3: very positive emotional state 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: @Jacqueline_69 haha! She did well today. I can't get beyond her pout annoying me I'm afraid.
Emotion: sadness
Intensity score:
|
0.562
|
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: @WyoWiseGuy @LivingVertical however, REI did offer me the job today as well. Can't believe how exponentially freaking joyous I feel...!!!
Emotion: joy
Intensity class:
|
3: high amount of joy can be inferred
|
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: It's simple I get after two shots of espresso 'Grande, decaf, 130 degrees soy americano with extra foam' #barista
Emotion: fear
Intensity class:
|
0: no fear 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: @dfkm1970 @tomddumba the struggle is real. Whoa! I worry for the younger generation 💔
Emotion: fear
Intensity score:
|
0.660
|
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: @TweeriaLee A stumbling block to the pessimist is a stepping stone to the optimist.
Emotion: sadness
Intensity score:
|
0.271
|
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: @saclivin @MrsCagg specific & intentional way. And part of that intention is to provoke conversation around systemic racism towards blacks.
Emotion: anger
Intensity class:
|
2: moderate amount of anger 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: How do u grieve someone who legally wasn't a person yet?
This tweet contains emotions:
|
disgust, sadness
|
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E).
|
Tweet: @MoneyJay901 hard to tell in your pic. My mistake then. Either way, nothing I said initially was about race. U took it there. #sad #ignorant
Emotion: sadness
Intensity score:
|
0.646
|
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: OOOOOOOOH MY GOD UUUUGGGGHHHHHHHHH
This tweet contains emotions:
|
anger, disgust
|
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: @MalYoung @AngelicaMcD I hope to now see some levity, light, romance and happiness come Stitch and Abby's way after such a long hard road.
Emotion: joy
Intensity class:
|
0: no joy 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: We're in contained depression. Only new economic engine is #Sustainability, say Joel @makower + @markmykleby @ #VERGEcon. #NewGrandStrategy
This tweet contains emotions:
|
pessimism, sadness
|
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: Completely blown away by @EvaNoblezada @alistairbrammer @JonJonBriones and the cast of @MissSaigonUK tonight. #fathomevents #speechless #awe
Emotion: fear
Intensity class:
|
0: no fear can be inferred
|
Task: Place the tweet into a specific ordinal class, which captures the tweeter's mental state by considering different 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: @jimadair3 Guitar shop owners everywhere rejoice
Intensity class:
|
1: slightly positive emotional state can be inferred
|
Task: Gauge the intensity of sentiment or valence in the tweet, indicating a numerical value between 0 (extremely negative) and 1 (extremely positive).
|
Tweet: I'm throwing myself straight into American Horror Story so I don't have time to grieve
Intensity score:
|
0.483
|
Task: Assess the sentiment intensity or valence level of the tweet, ranging from 0 (extremely negative) to 1 (extremely positive).
|
Tweet: I'm going to get the weirdest thank you note--or worse--total silence and no acknowledgement.
Intensity score:
|
0.467
|
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: @simon_penn_r @AntisocialJW2 has turned into a rather fiery GG radical)
Emotion: anger
Intensity class:
|
2: moderate amount of anger 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: @torreBe Te gusta American horror story y The walking dead?
Emotion: fear
Intensity class:
|
0: no fear 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: When we give cheerfully and accept gratefully, everyone is blessed. »Maya Angelou
Intensity class:
|
2: moderately 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: We have left #Maine. #sadness
Emotion: sadness
Intensity score:
|
0.771
|
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: Remember: The life you have is a blessing for #God. Make it a joyful experience regardless of the odds. GBY
This tweet contains emotions:
|
joy, optimism
|
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: Checked-in for my flight to Toronto. Took seat 3D just to infuriate @perpetualgeek.
This tweet contains emotions:
|
anger, disgust
|
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: What if.... the Metro LRT went over the Walterdale?!?! 😂 #yeg #levity
This tweet contains emotions:
|
joy, surprise
|
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: @BitchestheCat Look at those teef! #growl
Emotion: anger
Intensity class:
|
0: no anger 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: We are elated to have @lisavol, Sid Espinosa and @dyuliharris, ready to inspire innovative students!! @knightfdn @MicrosoftSV @JessicaWeare
Emotion: joy
Intensity score:
|
0.700
|
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: What if.... the Metro LRT went over the Walterdale?!?! 😂 #yeg #levity
Emotion: joy
Intensity score:
|
0.500
|
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: When's it all finished, you will discover that it was never random! #thoughts #CrossoverLife
Intensity class:
|
0: neutral or mixed emotional state can be inferred
|
Task: Evaluate the valence intensity of the tweeter's mental state based on the tweet, assigning it a real-valued score from 0 (most negative) to 1 (most positive).
|
Tweet: I'd rather dump gasoline all over myself and run into a burning building than use Excel.
Intensity score:
|
0.259
|
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: @EtherealMystic_ - felt like he couldn't control — and here she was, giving so much of herself, selflessly pleasing him. His groans were -
Emotion: joy
Intensity class:
|
0: no 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: pummeling cheerfully, jauntily, utterly one-sidedly makes us harder, better, faster, stronger
Emotion: joy
Intensity score:
|
0.627
|
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: @canada4trumpnow @donlemon he has BAD TEMPERAMENT #HissyFits
Emotion: anger
Intensity class:
|
3: high amount of anger can be inferred
|
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: so fucking sad when the person you love doesn't try fighting for your happiness, when you'd do anything for them.
Emotion: sadness
Intensity score:
|
0.771
|
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: Start the convo...don't shy away..mental illness abounds in society including our workplace...be informed... #tsdoffsite
Emotion: fear
Intensity score:
|
0.479
|
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: Angelino's been horrific
This tweet contains emotions:
|
anger, disgust, fear, sadness
|
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: I don't get that my parents literally don't see how unhappy I been lately
Emotion: sadness
Intensity score:
|
0.792
|
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: Angel got me nervous out here 😷
Emotion: fear
Intensity class:
|
2: moderate amount of fear can be inferred
|
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: @JustPyroNow are you gonna do any kind of community raids when wrath of the machine drops?
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: #WTF @NYSCHereToHelp @NYSC allows #gym #atmosphere! #jumpship #nasty #atmosphere #unprofessional
Emotion: fear
Intensity class:
|
0: no fear can be inferred
|
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: Rear garden alarm activated at Telford house at 106.4.
Emotion: fear
Intensity class:
|
0: no fear can be inferred
|
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: #PeopleLikeMeBecause People are using this hashtag to brag about themselves. I'm not interested in pleasing others, but in pleasing God.
This tweet contains emotions:
|
anger, disgust, optimism
|
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: Good job #Texas for saying no to #Obama for #refugees who could be #terrorists! #Wakeup, #America! #Stop #terrorism. #pray @foxandfriends
Emotion: fear
Intensity class:
|
0: no fear 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: The irony in that last is that Republicans - more likely to watch Fox News - distrust the news media more. Yet they can't see Fox's lies!
This tweet contains emotions:
|
anger, disgust
|
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: @syd_viciously I have gained a tremendous amount of respect for @RandPaul over the past couple of years.
This tweet contains emotions:
|
joy, optimism, trust
|
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: Remember your journey is unique! Don't get discouraged because you're comparing your journey to someone else's. You will get there!
Emotion: sadness
Intensity class:
|
0: no sadness 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: On the way to Laser Vista ... lens implantation ... #LaserVista #nervous #happy
Emotion: fear
Intensity score:
|
0.625
|
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: So excited to watch @RuPaulsDragRace #allstars \n #RuPaul
Emotion: anger
Intensity class:
|
0: no anger 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: @SueWallace78 peanut butter???? You some kinda pervert??
Intensity class:
|
-2: moderately negative emotional state can be inferred
|
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: Absolutely fuming I've just scratched all my car 😡😡😡😡😡😡
Emotion: anger
Intensity class:
|
3: high amount of anger 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: bout to read this article 'Moving the Conversation Forward: Homosexuality & Christianity' from someone in the foursquare church
Emotion: fear
Intensity score:
|
0.224
|
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: This is awful
Emotion: fear
Intensity class:
|
2: moderate amount of fear 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: Some #people already talks about #Halloween \nYou'll get some #dark #music to go with it\n#gothic #bloody #HalloweenHorrorNights
This tweet contains emotions:
|
fear
|
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: 13 hour @bus rides make me #sorry
Emotion: anger
Intensity class:
|
0: no anger can be inferred
|
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: @LaurenBrierley2 sparkling water = death
This tweet contains emotions:
|
fear, pessimism
|
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: Fucking hell. Rush for the damn train also no use. Fucking 4min wait. Still sweating. #rage #smrtruinslives
This tweet contains emotions:
|
anger, disgust
|
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: @Girlandlurchers Yep, peeps on here always out to cheer others up! I'm fine, drooling at GBBO x
Emotion: joy
Intensity score:
|
0.620
|
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: #ahs6 every 5 minutes I've been saying 'nope nope I'd be gone by now.' 'MOVE' or 'GTFO' so thank you for the #fear
Emotion: fear
Intensity score:
|
0.629
|
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: @TalesofanAlfa @David_Milloy \nI like your thinking...but sadly no - that's the shed 😢
Emotion: sadness
Intensity score:
|
0.604
|
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: It's way too hard not to get discouraged.
Emotion: sadness
Intensity class:
|
2: moderate amount of sadness can be inferred
|
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: @HoggyBear95 the bantz are absolutely top notch, inconsolable I was when I realised
Emotion: sadness
Intensity class:
|
2: moderate amount of 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: Noooooo @GBBOUK without #MaryBerry will be #awful #endofanera going 2b so #lost @Channel4 have bought a #lameduck there #notallaboutthemoney
Emotion: fear
Intensity class:
|
1: low amount of fear can be inferred
|
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