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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: Today's realisation that it was the last time I watch swimming lesson cos I go back to work next week lead to a joyous bedtime. #worstoneyet
Emotion: joy
Intensity class: | 0: no 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: Only God knows why things happen, sometimes it's just hard to understand. #sad #prayingforyou
Emotion: sadness
Intensity score: | 0.875 |
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: I want to slide into the dms but im too fucking shy #shy
Emotion: fear
Intensity score: | 0.667 |
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: 💥⚖️Yeah‼️ PAUL‼️⚖️💥 #glorious #BB18
Intensity class: | 1: slightly positive emotional state 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: @HMiglino @CParks777 @Coco_Wms @bodyfit67 @TruthEqualsFact @politicususa I have never been more anxious of a election in my life‼️ #fearful
Emotion: fear
Intensity class: | 3: high amount of 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: Everywhere I go, the air I breathe in tastes like home.' - @The_Currys
Emotion: fear
Intensity class: | 0: no fear can be inferred |
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: @Megane_Matt @HikariMorou next to despair, hope shines even brighter (you get me Matt)
Emotion: sadness
Intensity score: | 0.375 |
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: @annalisewrobel_ awe thank you so much love 💕
Emotion: fear
Intensity score: | 0.062 |
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: Why doesn't anybody I know watch penny dreadful? ☹️️
This tweet contains emotions: | disgust, pessimism, sadness |
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: @carl_diggler @TMZ_Sports Thank you for saying what others are afraid to say, Carl. Big fan!
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: Ffs dreadful defending
Emotion: sadness
Intensity score: | 0.500 |
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: @MoviesTVNetwork Wow, did you get a really good buy on a bunch of '70's movies? There were bad then and are worse now!
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: @ATTCares why do I have 2 wait 48 hours to call YOU back to cancel an order I JUST placed after already spending 2 hours on the phone?! #sad
Emotion: sadness
Intensity class: | 2: moderate amount of sadness can be inferred |
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: @antoboyle I so wish you could someday come to Spain with the play, I can't believe I'm not going to see it #sad
Emotion: sadness
Intensity class: | 3: high amount of sadness 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: Way towards be prominent if your exasperate is peaked?: TGMbNqUEe
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: Best quote from a 7 in German - Almost
Emotion: joy
Intensity class: | 0: no joy can be inferred |
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: Changing my hair again
Emotion: fear
Intensity class: | 0: no fear can be inferred |
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: @AniahROSE I know smh. My heart sunk into my stomach.
Intensity class: | -2: moderately negative emotional state 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: @ADenkyirah Happy birthday! Hope you have a wonderful day filled with lots of joy and laughter <3 (despite tumblr being a jerk- once again)
Emotion: joy
Intensity class: | 3: high amount of joy 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: Am a very old person I can't handle some stuff....lol I just left her there.... Get back to me when you're sober
Emotion: sadness
Intensity class: | 1: low amount of sadness can be inferred |
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: @clppng #offended the tonys have found a way to leave me out and now y'all have too
Emotion: anger
Intensity class: | 2: moderate amount of anger 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: Shoutout to @VZWSupport for ruining my iPhone 7 order!!
Emotion: fear
Intensity class: | 0: no fear 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: @zavierdaniels had to snap going crazy 😭😭
Emotion: anger
Intensity score: | 0.458 |
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: @JaredWyand @ilovetailgating the beak on that woman is almost as shocking as the low IQ of her followers.
Emotion: fear
Intensity class: | 0: no fear 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: So about 18mths ago i signed up to @Lumo_Energy for their @VirginAustralia / Velocity FF deal. 18 months in still no FF points #shocking
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: Every year I go to universal studios to horror nights as a 3rd wheel lol 😊😂
This tweet contains emotions: | fear, joy |
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: @SkyNews when the East wind blue in summer in Durban, S Africa, we still surfed and got #stung badly! Must be carefull-A #sting can harm you
Emotion: anger
Intensity score: | 0.562 |
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: #HRmanagement must discourage the expediency factor from encroaching on the rolling out of a credible #workplaceviolenceprevention policy.
Emotion: sadness
Intensity score: | 0.196 |
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: The little sniffle at the end of the song gets me every time. #rejoice
Emotion: joy
Intensity class: | 2: moderate amount of joy 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: Watch this amazing live.ly broadcast by @izzybuzy365 #musically
Emotion: joy
Intensity class: | 2: moderate amount of joy 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: My heartbeat is forever stumbling on memories of things past. #longing #loss #shape #form #sadness
This tweet contains emotions: | disgust, sadness |
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: @TheMandyMoore You are beyond wonderful. Your singing prowess is phenomenal but damn... I'm just elated to watch you act again. #ThisIsUs 🤗
This tweet contains emotions: | anticipation, joy, love, optimism, 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: @Ms_HeartAttack holy shit it just a bee sting like fuck you're not dying
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: @hollywooddivas @TMZ_Sports Idiots like Larry Sanders scare us All!How can Morons these days Rush 2 Judge #Police w/o all facts yet?FU thugs
This tweet contains emotions: | anger, disgust |
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: @downseung I'm sorry about your loss... no one should ever give you shit for taking your time to mourn. No matter how long it takes.
Intensity class: | -2: moderately negative emotional state 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: @katethecursed @shannonrdk LOL this day is too gloomy for being people, should've canceled and stayed in bed
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: @lefluerr Lol yeah I read that but I stayed up and didn't nap tillI collect 3 people who I think they've got me 😂😂!!
This tweet contains emotions: | joy |
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: Oh I get i see it's #TexasTech playing tonight not the #Texans #TNF #texansarebad #terrible
Emotion: fear
Intensity class: | 0: no fear can be inferred |
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: Ok but I just got called a 'White Devil' on the train and I didnt know whether to laugh or be offended
Intensity class: | 0: neutral or mixed 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: @Cernovich It's like the horror movie The Hills Have Eyes...
Emotion: fear
Intensity class: | 0: no fear 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: I'm so restless
Intensity score: | 0.190 |
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: I'm strong 'cause I'm weak\nI'm beautiful 'cause I know my flaws\nI'm fearless 'cause I've been afraid\nI can laugh 'cause I've known sadness..
This tweet contains emotions: | joy, optimism, sadness, trust |
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: @rkuuleiq Fear is best/beast product of God/s. :) #aTheism #theism #biBle #christianity #hell #heaven #purgatory #psychology #jesus
Emotion: fear
Intensity score: | 0.370 |
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: @SiobhanSynnot Oh, good God. Quentin Letts is doing one of his 'comedy' turns. #angry @bbcthisweek @afneil #BBCTW
Emotion: anger
Intensity class: | 2: moderate amount of 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: Our tone of voice: we're like One Direction, we're thoughtful and timid, yet playful
This tweet contains emotions: | joy, optimism |
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: @TheGoatShow @GameGrumps now that I have been sucked into this wormhole of hilarity with no escape, I can say how weird and accurate this is
Intensity score: | 0.468 |
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: I'm so bored and fat and full and ridiculously overweight and rolls galore #terrible
Emotion: fear
Intensity score: | 0.562 |
Task: Determine the sentiment intensity or valence score of the tweet, representing the tweeter's mental state on a continuum from 0 (highly negative) to 1 (highly positive). | Tweet: mustache_harbor: TiburonChamber plus a hearty pour of #yachtrock by #mustacheharbor !
Intensity score: | 0.655 |
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: . @KotakBankLtd @udaykotak official got in touch. Issue not addressed. #unhappy #patheticservices
Emotion: sadness
Intensity class: | 3: high 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: I can literally eat creamy pesto pasta topped with grilled chicken, sun dried tomatoes, asparagus and pine nuts every single day of my life
Emotion: sadness
Intensity score: | 0.083 |
Task: Measure the intensity of sentiment or valence in the tweet, assigning it a score between 0 (highly negative) and 1 (highly positive). | Tweet: Benefit out exhilaration called online backing off: JkUVmvQXY
Intensity score: | 0.621 |
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: — Self-hatred gives rise to fury, fury to the desire for self-change.
Emotion: anger
Intensity class: | 1: low amount of anger 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: When I walk in darkness of despondency, Sc.verses I've memorized shine a light in my heart. Ex: Lam 3:22-25
Emotion: fear
Intensity class: | 0: no fear 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: talk about a mood pickup i went from depressed to elated so fast
This tweet contains emotions: | joy, optimism, surprise |
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: @UCSMindfulness thank u so much! we just finished another #mindfulness film called #release about #anxiety - plz share!
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: The radio just told me Lady GaGa is going country, which is like if the Beatles decided to do opera singing for their final albums
Emotion: fear
Intensity class: | 0: no fear 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: All this from a cigarette burning in Laura's hand, the angle of her chin, the purse of her lips.'(104) Gorgeous transition!@laurengrodstein
Emotion: anger
Intensity score: | 0.312 |
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: We're all in D. T. (Discipleship training or detox) for something. #messy #fearful #cutoff #choosefreedom #CryOut16
Emotion: fear
Intensity score: | 0.604 |
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: I'd rather die alone then end up with somebody who can't be sober
This tweet contains emotions: | anger, disgust, sadness |
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: @xmaseveevil1. #MSM is rejoicing that they've fooled us with these body doubles for so long & now her death is a secret. Just like Hawkings
This tweet contains emotions: | disgust |
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: Idk why but this Time around its so hard that it hurts, I already miss them all so much #silly #family #friends
Emotion: fear
Intensity class: | 1: low 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: Zephaniah 3:17 He surely is rejoicing over us with singing...such romance and so needed today!!
Emotion: joy
Intensity score: | 0.708 |
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: @r0Ils ppl get triggered over u smiling they're irrelevant
Intensity score: | 0.375 |
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: @DorH84607784 Oh FANTASTIC, I bet it was super exhilarating 🤗😍
Emotion: joy
Intensity score: | 0.840 |
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: @steph_baker7 i tried to turn off my alarm this morning and it turned on all my alarms instead
This tweet contains emotions: | anger |
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: @safaridjh but it's so aesthetically pleasing omg
Emotion: joy
Intensity class: | 2: moderate amount of 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: All this doom and gloom! We scored from open play again! And only conceded two this time. #progress they means a 1-1 draw on Saturday for me
This tweet contains emotions: | 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: @lucy_hyner @Soulboy2266 sadly not !! One less hour drinking time 😢🍻
Emotion: sadness
Intensity score: | 0.667 |
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: - blood and mucus and he chokes and has to swallow, mirth cut too short. 'Wrong answer.' It takes some awkward movements - @PersuasiveFuck
This tweet contains emotions: | anger, disgust, pessimism |
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: I'm honored to take on such a role in their joyous day. Hopefully I don't fuck it up
Emotion: joy
Intensity score: | 0.500 |
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: @DunsScottus @FaithNGuns @buggazing @Patriot_Musket Yep, Owen Garriott told me it was ghastly. None of his peeps ever had it :)
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: Right i may be an #sufc fan and the football maybe shit but marcos rojo for #mufc has had a shocking start he's just dreadful
Emotion: sadness
Intensity class: | 2: moderate amount of sadness 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: @TheGoatShow @GameGrumps now that I have been sucked into this wormhole of hilarity with no escape, I can say how weird and accurate this is
This tweet contains emotions: | anger, disgust, sadness |
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: inha's and seol's banter is rly fun to read. im in awe that seol is willing to deal with her tho
This tweet contains emotions: | joy, surprise |
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: Which #JohnCarpenter #horror #action #flick is your favorite ??
Emotion: fear
Intensity score: | 0.229 |
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: Sanatana Lopez is definitely me 😂
Emotion: joy
Intensity class: | 2: moderate 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: With that draw, the scum must be rubbing their hands with glee! Typical draw for the Woolwich lot!!! #jammygunnerscum
Emotion: joy
Intensity score: | 0.292 |
Task: Quantify the sentiment intensity or valence level of the tweet, giving it a score between 0 (highly negative) and 1 (highly positive). | Tweet: One point: DSP claims YTers lost half their viewership in 2012 if they weren't using direct capture. That's when the search changes happened
Intensity score: | 0.478 |
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: @gagasklaine it's old sadly
Intensity score: | 0.141 |
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: and apparently he's supposed to have a Scottish accent??? I'm
Emotion: anger
Intensity class: | 0: no anger 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: Turkish exhilaration: for a 30% shade off irruptive russian visitors this twelvemonth, gobbler is nephalism so...
This tweet contains emotions: | anticipation, joy, surprise |
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: Use your smile to change the world. Don't let the world change your smile.' #quote #actorslife #smile #love #hardworkpaysoff #fun
This tweet contains emotions: | joy, optimism |
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: My bf drove out of his way after a long day just to spend 15 min holding me to make me feel better. How'd I get so lucky #lucky
Emotion: joy
Intensity class: | 3: high amount of joy 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: @jkriv You're most welcome. Please check with us anytime you have a question or concern.
This tweet contains emotions: | anticipation, joy, optimism, trust |
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: i animated a little thing i might post it tomorrow since itll be a Good Thursday.. nice...
Emotion: joy
Intensity class: | 2: moderate amount of joy can be inferred |
Task: Assess the sentiment intensity or valence level of the tweet, ranging from 0 (extremely negative) to 1 (extremely positive). | Tweet: I am always ready to #smile.
Intensity score: | 0.724 |
Task: Assess the intensity of sentiment or valence in the tweet, representing the tweeter's mental state with a real-valued score between 0 (extremely negative) and 1 (extremely positive). | Tweet: @airtelindia have some issues with my broadband bill ,I am charged for the month before I signed up with airtel.. #hilarious
Intensity score: | 0.661 |
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: When someone tells you they're going to 'tear you apart' and all they have to say is 'why are you so tall?' #shocking
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: I'm worried someday I'll be yelling at my kids and they'll be confused about if or not I'm being serious 😭😭😭\n\nI'm too damn playful
This tweet contains emotions: | anger, disgust, pessimism, sadness |
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: Another L on the board we just cannot match up on paper with these teams at the moment and its showing on the field. Onto Denver
Emotion: anger
Intensity score: | 0.521 |
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 I walk in darkness of despondency, Sc.verses I've memorized shine a light in my heart. Ex: Lam 3:22-25 #despondency
This tweet contains emotions: | joy, optimism |
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: Bridesmaid dresses: having carnal delight in addition to separates: RFpBAX
Emotion: joy
Intensity score: | 0.417 |
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: Argh a big wasp buzzing between my blinds and my window. Halp! #wasp #evil #buzz
Emotion: anger
Intensity class: | 2: moderate amount of anger 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: #terribledebatequestions has given me so many laughs this afternoon! Thanks Twitter! #hilarious #cleverpeople
Intensity score: | 0.897 |
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E). | Tweet: So my Indian Uber driver just called someone the N word. If I wasn't in a moving vehicle I'd have jumped out #disgusted
Emotion: anger
Intensity score: | 0.896 |
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: I don't want the pity of my instructors but I'd like some understanding. I'm truly trying despite ALL circumstances that make me discouraged
Emotion: sadness
Intensity class: | 2: moderate amount of sadness 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: On the drive home today I heard a censored version of Spirits by The Strumbellas. 'Guns' replaced with 'dreams'. Just NO. #censorship
This tweet contains emotions: | anger, disgust, optimism |
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: 8. sweater weather - the neighbourhood\ngirls/girls/boys - panic! at the disco
Emotion: fear
Intensity score: | 0.458 |
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: Missing the 500th test match today , not able to witness it like watching it in India #shy #indvsnz #500thTest @BCCI
This tweet contains emotions: | sadness |
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: When you make a great tasting shake and no words can describe it!😃👌🏻 #shake #herbalifenutrition #tastesogood #nowords
Emotion: fear
Intensity score: | 0.125 |
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