instruction
stringclasses 50
values | input
stringlengths 32
202
| output
stringlengths 0
55
|
|---|---|---|
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: All work and no play makes Jack a dull boy
Emotion: sadness
Intensity class: | 1: low amount of sadness 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: 340:892 All with weary task fordone.\nNow the wasted brands do glow,\nWhilst the scritch-owl, scritching loud,\n#AMNDBots
This tweet contains emotions: | anger, disgust |
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: 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
This tweet contains emotions: | anger, disgust, surprise |
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: @veroicone my typical shake is ~100g banana, 1c almond milk, 1tbsp chia and protein. Sometimes I add PB2 or ice or other fruit.
This tweet contains emotions: | joy |
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: @Amphabio don't kill it bees are dying at an alarming rate
This tweet contains emotions: | anger, fear, sadness |
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: @SadiqKhan #terrorism shouldn't be a way of life in the united etates and wasn't until #islam brought it here! #IslamExposed #islambacon
This tweet contains emotions: | anger, disgust, fear |
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: I know few will mourn the loss of Stitch's Great Escape, but...see, THIS is the kind of cost-cutting at parks I really don't care for.
Intensity score: | 0.578 |
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: Just like there is a right way to pray, there is a right way to give - not grudgingly or of necessity, but cheerfully. #woficc
This tweet contains emotions: | joy, optimism, trust |
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: 🔥💁🏼- its lit having a class with you!!! Your such a great person and good at cheer!!
This tweet contains emotions: | joy, love, optimism, trust |
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: Constantly fucking boiling and it's not ok
Emotion: anger
Intensity score: | 0.771 |
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: Another loss to city in the cup next 🙈 😂😂 cmon united!
Emotion: anger
Intensity class: | 0: no 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: I'm just doing what u should b doing just minding my business and grinding relentless @LITO615
This tweet contains emotions: | anger, disgust |
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: @CNNPolitics I can't wait to hear what he had to say about the brilliant Dr. Hawking... it should be rich... In the poorest of taste! #bully
This tweet contains emotions: | anger, anticipation, 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: @drunkafzayn @vogueszap yes it's shocking how islamophobic Indias are considering how many Muslims live there
This tweet contains emotions: | anger, disgust, surprise |
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E). | Tweet: @PediMGHHMS3 sickle cell if right pt background. Or could be JIA or an allergic reaction to a bite e.g. bee sting among others.
Emotion: anger
Intensity score: | 0.292 |
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: Damnnit! Gonna be 1400 pts shy on Chiefs Rewards of getting a post game photo.
Emotion: fear
Intensity score: | 0.521 |
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: #PeaceIsPossible when both party accept one another and rejoice together after #OndoGuber,Nov26. @JciOndokingdom @cuttie_dove @Lekibeat
Emotion: joy
Intensity class: | 1: low amount of joy 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: And thus begins my 2 week holiday! 😏😏\n #holiday #ghastinoir #rest
Emotion: joy
Intensity score: | 0.792 |
Task: Determine the valence intensity of the tweeter's mental state on a scale of 0 (most negative) to 1 (most positive). | Tweet: Laudrup and his evil white companions rejoice.
Intensity score: | 0.617 |
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: This girl was shaking her drink in the break room and it wasn't fully closed and yeah it's all over the place now including me😑😑😂
Emotion: fear
Intensity score: | 0.458 |
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: #Talking about our #Problems is our greatest #Addiction#Break the #habitTalk about ur #Joys#quote #problemsolving #behappy
Emotion: joy
Intensity class: | 1: low amount of joy 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: @nigglydz lydiaaaa, we were the only ones that were supposed to know that you make me nervous 😶
Intensity class: | -2: moderately negative emotional state 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: $100 says Teufel is 'reassigned' within the organization before next year, but I wish it was sooner... #Mets #thirdbasecoach #lgm
This tweet contains emotions: | anticipation, optimism |
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: Well, the lines for Sweden's goals sure sting.
Emotion: anger
Intensity score: | 0.312 |
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: @iSmashFizzle that's me all the time. I carry ginger candy, peppermint oil and sea-bands at all times
Emotion: fear
Intensity score: | 0.354 |
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: @SteveStratford9 @PaulTowheyJr @ClassicDrWho @BBC @bbcdoctorwho all those will get animated IMO. Companion changes/Monsters/Classics.
Emotion: joy
Intensity score: | 0.292 |
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: @Thatguy_dree @RecklessWonder_ neither one of y'all can see me in this madden
This tweet contains emotions: | anger, joy, optimism |
Task: Gauge the intensity of sentiment or valence in the tweet, indicating a numerical value between 0 (extremely negative) and 1 (extremely positive). | Tweet: They tend to loosen up a bit when drunk, and can seem pretty cheerful.
Intensity score: | 0.677 |
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: @Curculiunculus @System1Politics Yep, as I pointed out before, it's the politics of loathing. That's why the big candidates are so horrible.
Emotion: fear
Intensity class: | 0: no fear 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: Always be #cheerful, #smile often make others happy, care for others, help who feel helpless and #vulnerable. Life feels good #leadership
Emotion: joy
Intensity class: | 3: high amount of joy 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: I hate having ideas but being too afraid to share them 😔
Emotion: fear
Intensity class: | 2: moderate amount of fear 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: @GambinoDeeJay @Linda76Graham @mikeeshy \n\nAnd also, trying to find it on Youtube is a fucking nightmare.
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: @SkySportsRL i would just get some decent referees
Emotion: fear
Intensity class: | 0: no fear 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: She began to squirm beneath @hcllbent, struggling to get out of his relentless grasp. When she realized that the attempt was useless,++
Emotion: anger
Intensity class: | 1: low 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: @PeanutRD @MelissaJoyRD @SarahKoszykRD @eat4performance @rustnutrition @jenhaugen hey #sparkling is the word I just picked 4 my biz card
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: @jay_roseee but that new breezy & tiller 🔥🔥🔥🔥🔥
Emotion: joy
Intensity class: | 1: low amount of joy 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: What's good is that we already hit rock bottom, even though I'm about two more seasons away from new depths of despair. #playoffs? #NJDevils
This tweet contains emotions: | 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: You ever just be really irritated with someone u love it's like god damn ur makin me angry but I love u so I forgive u but I'm angry
Emotion: anger
Intensity score: | 0.667 |
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: @Nataliem55 sadly, war has often been the factor that jump starts US economic growth
This tweet contains emotions: | 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: Your future is bright. #Remember
This tweet contains emotions: | joy, optimism |
Task: Determine the valence intensity of the tweeter's mental state on a scale of 0 (most negative) to 1 (most positive). | Tweet: @bodwell_james did it not just enliven your soul
Intensity score: | 0.532 |
Task: Quantify the sentiment intensity or valence level of the tweet, giving it a score between 0 (highly negative) and 1 (highly positive). | Tweet: Doesn't it just suck when you're so real to someone and try to exhilarate every ounce out of them to only see that they're not down
Intensity score: | 0.290 |
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: @DSDambuster just finally started #homefronttherevolution, what did you all do the story and gameplay??? #terrible #wasteofmoney
This tweet contains emotions: | anger, 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: @NFYFC @Wilkster_ hmm, don't know many yf who are short on confidence! Wish I'd been one,
Emotion: fear
Intensity class: | 0: no fear can be inferred |
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: Super shitting it about this tattoo #nervous
Intensity score: | 0.344 |
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: 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: 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: @crumpledlinen he chirp
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: What the fuck am I supposed to do with no lunch, no dinner, no money and I'm off to work #furious #hangry #day5
This tweet contains emotions: | anger, disgust, 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: @soyoprincess they irritate me. Them and their inch thick made up masks
This tweet contains emotions: | anger, disgust |
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: @GOT7Official @jrjyp happy birthday jin young!!!!!! #PrinceJinyoungDay #happyjinyoungday #got7 #happy #birthday
Emotion: joy
Intensity score: | 0.688 |
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: A warm #smile is the universal language of kindness William Arthur Ward #love #kindness
Intensity score: | 0.625 |
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: Oh I get i see it's #TexasTech playing tonight not the #Texans #TNF #texansarebad #terrible
Emotion: fear
Intensity score: | 0.354 |
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E). | Tweet: @Myahrissavietta I'm cheery now 😘😉
Emotion: joy
Intensity score: | 0.760 |
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: In other news. My legs hurt. #running #5kin26mins #flatfeet
Emotion: fear
Intensity class: | 0: no fear can be inferred |
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: @BrianaBanksxoxo I send ya a few #playful nibbles 😉
Intensity score: | 0.679 |
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: Shanghais chief distracting levity pampa - proper dingle carry away: uUDQujcia
Emotion: joy
Intensity score: | 0.180 |
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 envy the relentless, your cheerful smile aimed at the pouring rain, your positive attitude is an art you have continually mastered.
Emotion: joy
Intensity score: | 0.519 |
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: @NGilbert92 @_c0urtknee_ haha it's me, shocking I know 😂 you'll hear me moan I'm too cold in winter ⛄️
This tweet contains emotions: | joy, optimism, surprise |
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: @Hannahcolleen06 I have 12 & that's the only one I didn't like 😂 mine comes out patchy. It's the only dark color by her I have tho.
Emotion: sadness
Intensity score: | 0.312 |
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: Multitasking .... I may have to induce these seeds of mine to sleep. #restless
Emotion: fear
Intensity score: | 0.521 |
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: Fucking hell. Rush for the damn train also no use. Fucking 4min wait. Still sweating. #rage #smrtruinslives
Emotion: anger
Intensity score: | 0.917 |
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: @Slippus @PureGym yeah I received a fine today which I am furious about, currently appealing it after being a member for so long...
This tweet contains emotions: | anger, disgust, pessimism |
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: Tutoring gives me such an exhilarating feeling. I love helping people 😌
Intensity score: | 0.790 |
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: There's this Bpharm4 guy Eish that guy brings anger into my life. When I see him nje like darkness fills me @RamatsobaneM will know
Emotion: anger
Intensity score: | 0.667 |
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: Like he really just fucking asked me that. #offended
Emotion: anger
Intensity score: | 0.750 |
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: It is a solemn thing, and no small scandal in the Kingdom, to see God’s children starving while seated at the Father’s table. -AW Tozer
This tweet contains emotions: | anger, disgust, pessimism, 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: my boyfriend once forcibly stopped all of my anxiety coping methods at once (holding me, forcing my hands down that kinda stuff) and I --
Emotion: fear
Intensity class: | 2: moderate 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: Ready for my sweet princess to arrive. I'll he 37 weeks this Saturday! #excited #nervous
Emotion: fear
Intensity score: | 0.352 |
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: Your #smile is a messenger of your good will.
Emotion: joy
Intensity class: | 2: moderate amount of joy 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: What the fuck am I supposed to do with no lunch, no dinner, no money and I'm off to work #hangry #day5
Emotion: anger
Intensity score: | 0.729 |
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: @Nataliem55 sadly, war has often been the factor that jump starts US economic growth
Emotion: sadness
Intensity score: | 0.479 |
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: @FoxNews @SheriffClarke @FoxNewsInsider This man is an affront to our justice system.
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: @F1abraham holy shit...what the hell happened to your lips!! Fix that shit! #mtv #teenmom #horrible
Emotion: fear
Intensity score: | 0.479 |
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: I swear if @devincameron23 blocks me I'm going to hit her back
Intensity class: | -3: very negative 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: Sometimes I watch shitty tv to reinforce never giving up cuz if something is that fucking awful on tv, I still stand a chance. #optimism
Emotion: joy
Intensity score: | 0.104 |
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: @LonelyGoomba UK cops have an issue fearing intervention. Hence situations like Rotherham. So of course it'll be dwarfed by US cops.
Emotion: fear
Intensity score: | 0.562 |
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: @soboleskih Okay this is hilarious
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: Leon's cheerfulness is always a big help.
This tweet contains emotions: | joy, love, optimism, trust |
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: In 2016, Black people are STILL fighting to be recognized as human beings. #cantsleep
Emotion: anger
Intensity score: | 0.646 |
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: STAY JADED everyone is #terrible
Emotion: fear
Intensity score: | 0.417 |
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: Something about these cool, breezy fall days.. 😍🍂🌾🍁
This tweet contains emotions: | joy, love, optimism |
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: @Justin_Gau @JamesMelville You certainly wouldn't catch me with the multitude.
Emotion: fear
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: It's simple I get after two shots of espresso 'Grande, decaf, 130 degrees soy americano with extra foam' #barista
Emotion: fear
Intensity score: | 0.125 |
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: Wishing the Ipswich Tigers good luck in their games throughout homecoming week!! We are cheering you on here at the City Office! GO TIGERS!
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: I need to learn to be in one place at one time and try not to worry about everything all at once
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: I just really enjoy bright colors, like the colors you would see downtown Miami
Emotion: joy
Intensity score: | 0.729 |
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E). | Tweet: @Slippus @PureGym yeah I received a fine today which I am furious about, currently appealing it after being a member for so long...
Emotion: anger
Intensity score: | 0.646 |
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: A Lysol can got stuck in spray position and we're all slowly suffocating from the trash can that smells like a Febreeze factory. #panic
Emotion: fear
Intensity class: | 2: moderate 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: @Fly_Norwegian quite simply the #worst #airline #worstairline I've ever used! #shocking #appauling #dire #dismal #beyondajoke #useless
Emotion: sadness
Intensity score: | 0.667 |
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: Tomorrow is the day I cut and dye my hair! 😳 #excited
This tweet contains emotions: | anticipation, joy, 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: Who the hell is drilling outside my house?! Literally got to sleep at half four after a busy shift and these twats have woken me up
Emotion: anger
Intensity score: | 0.976 |
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: Every dancers dream song #worldpower
Emotion: anger
Intensity class: | 0: no anger 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: @JamesPiotr I am working on a feature right now about the preponderance of awful owners who are at war with fans. So many to choose from.
Emotion: fear
Intensity score: | 0.354 |
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: Having a terrific Tuesday? Crush it today with the Power of 4. Treat your internet like Pizza =D \n#PowerOf4
Emotion: fear
Intensity score: | 0.250 |
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: My ukulele bag has fallen apart. 😐 WELLL AT LEAST my life hasn't yet!! #optimism
Emotion: joy
Intensity score: | 0.208 |
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: Tweeting from the sporadic wifi on the tube #perilous
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: my boyfriend once forcibly stopped all of my anxiety coping methods at once (holding me, forcing my hands down that kinda stuff) and I --
Emotion: fear
Intensity score: | 0.740 |
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: @ardit_haliti I'm so gutted. I loved her cheery disposition.
Emotion: joy
Intensity class: | 1: low 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: @bt_uk why does tracking show my equipment delivered, when it wasn't? Why is my service suddenly delayed? We've already 3 weeks.
This tweet contains emotions: | anger, disgust, 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: To tell the truth and make someone cry is better than to tell a lie and make someone smile. #truth #lie #cry #offalonehugots
This tweet contains emotions: | joy, optimism, sadness |
End of preview. Expand
in Dataset Viewer.
Citation Information
Liu, Z., Yang, K., Xie, Q., Zhang, T., & Ananiadou, S. (2024, August). Emollms: A series of emotional large language models and annotation tools
for comprehensive affective analysis. In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 5487-5496).
- Downloads last month
- 41