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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: @Sargon_of_Akkad It'll be like burning rap albums; they'll have to buy it first, but gosh darn it, they have to get rid of it.
This tweet contains emotions: | anger, disgust, pessimism |
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: So unbelievably discouraged with music as of late. Incredibly behind on Completing my album. Not digging this at all.
Emotion: sadness
Intensity score: | 0.604 |
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: Somewhere between #hope and #despair the day after #meetingmyabuserincourt \n#DVSurvivor
Emotion: sadness
Intensity score: | 0.810 |
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: Manchester United v Manchester City #happy days #EFL
Intensity score: | 0.758 |
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 we give cheerfully and accept gratefully, everyone is blessed.\nΒ»Maya Angelou\n\n@DrMayaAngelou #RIP #MayaAngelou
This tweet contains emotions: | joy, optimism, sadness, trust |
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: @Thebeast_ufc what happened to the suicide tweet it was a joke obviously how could that offend anyone?π€
Intensity class: | -1: slightly negative emotional state 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: @mackenzian yes! That was my one qualm. These are deeply theological issues we're engaging theologically.
Emotion: fear
Intensity score: | 0.229 |
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: And I cried in front of my guy last night. And it's just been a horrible week but it's only for a week
This tweet contains emotions: | disgust, fear, pessimism, sadness |
Task: Measure the intensity of sentiment or valence in the tweet, assigning it a score between 0 (highly negative) and 1 (highly positive). | Tweet: @amstrado_CPC @ShittySUFanart the single tear is him being joyous that he's deleted the monster that has brought generations of despair
Intensity score: | 0.667 |
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: 1Pet 4:7 But the end of all things is at hand: be ye therefore #sober, and #watch unto prayer
Emotion: sadness
Intensity class: | 1: low amount of sadness 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: Special thanks to @hamsterwatch & @UgotBronx for keeping us updated & entertained this dismal BB season π
This tweet contains emotions: | joy, optimism |
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 mean I'm not done watching the pilot, but it's nice to see a group of actors perform without story lines dripping relentless nihilism.
This tweet contains emotions: | anger, disgust, joy, optimism |
Task: Classify the tweet into one of four ordinal classes of intensity of emotion E that best represents the mental state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: Colors of the leaves are- changing. Heatwaves in LA still- raging. Lattes made in batches. Visit pumpkin patches. #FallSongs
Emotion: anger
Intensity class: | 0: no anger 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: 13 hour @bus rides make me #angry #sorry
Emotion: anger
Intensity score: | 0.688 |
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: @KMunie7 @KaranEsch Helluva lot more animated than they were for the actual game >.<
Emotion: joy
Intensity class: | 0: no joy 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: Bloody parking ticket ππΈ #fuming
Emotion: anger
Intensity score: | 0.792 |
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: #nana 4 hoco bc my dream since freshman year awe πβ€β€β€ @thecandeyman
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: @CurtisJobling Yes indeed! We know masses of students would be so excited to see you! We need to get this sorted! #haunt
This tweet contains emotions: | fear, joy, optimism |
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E). | Tweet: @Gronnhair @buryprofs @DittoBistro it was indeed lovely and the team were incredibly attentive and on the ball. Cheese was a lively gesture!
Emotion: joy
Intensity score: | 0.646 |
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: @MaxVenator We've had no foreign policy but have had goofy Secretary of State John Kerry with his devil may care pose and jaunty blue scarf.
Intensity score: | 0.462 |
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: Buddha doesn't possess enough power to deliver you from your affliction!
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: @PridefulSamurai horrible things
Emotion: fear
Intensity class: | 2: moderate amount of 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: @NinjaWorrier @ali_zimmer @m_pattison How long ago was that? (I shudder to think.)
Emotion: fear
Intensity score: | 0.625 |
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: im crying katherine is the only one whos like talking to me during my anxiety attack im gonna faint
Emotion: fear
Intensity class: | 3: high amount of fear 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: Whatever you decide to do make sure it makes you .
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: Drop Snapchat names #bored #snap #swap #pics
Emotion: anger
Intensity class: | 2: moderate amount of anger 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: Such merriment & laughter from @dadwroteaporno at @KingsPlace & an instructional PowerPoint presentation.Well done to all concerned & thanks
This tweet contains emotions: | joy, optimism |
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: Henny and pine apples π€
This tweet contains emotions: | |
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: My Modern Proverb: 'Don't let anyone intimidate you about being single; most marriages end in divorce.'
This tweet contains emotions: | disgust, pessimism, sadness |
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: Love the new song I can't stop thinking about you by #sting.
Emotion: anger
Intensity class: | 0: no anger 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: @ADenkyirah Happy birthday! Hope you have a wonderful day filled with lots of joy and laughter <3 (despite tumblr being a jerk- once again)
This tweet contains emotions: | joy, love, 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: This night is sparkling don't you let it go,\nI'm wonder struck,\nBlushing on the way home.'
Intensity score: | 0.630 |
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: @NikhilTikare i like cold gloomy weather
This tweet contains emotions: | joy, love, trust |
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: Punchline king is back! @Paedeezy π₯π₯π₯π₯π₯π₯π₯π―π―π― #bright city lights
Emotion: joy
Intensity class: | 2: moderate amount of joy 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: 10 minutes with an incense and all I get is 2 Rattatas. π#PokemonGO
This tweet contains emotions: | anger, anticipation, disgust, 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: @LeePorter94 @DomMcGovern_ hi Dom I saw u at Notts county away, looking for 1 mufc away ticket will pay
Emotion: sadness
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: @spamvicious I've just found out it's Candice and not Candace. She can pout all she likes for me π
Emotion: anger
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: Just told me wife there was a chance it would be 2 Sydney teams in AFL grand final. Her response: 'there's two SYDNEY AFL teams?' #serious
Emotion: sadness
Intensity class: | 0: no 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: @CapehartJ agree! Those latest polls #alarming
This tweet contains emotions: | fear, sadness, 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: If I was a ghost I'd haunt people by giving them cramps in both of their legs when they do cardio πππ #Mwahaha
This tweet contains emotions: | fear, joy |
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: Manchester derby at home #revenge
Emotion: anger
Intensity class: | 0: no anger 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'm going to get the weirdest thank you note--or worse--total silence and no acknowledgement.
Emotion: fear
Intensity class: | 0: no fear can be inferred |
Task: Gauge the level of intensity for emotion E in the tweet, assigning it a score between 0 and 1. A score of 0 indicates the lowest intensity, while a score of 1 indicates the highest intensity. | Tweet: @ManUtd it was a terrible Freekick...
Emotion: fear
Intensity score: | 0.347 |
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: Check out this #film Robocoq 301 #animated #shortfilms
Emotion: joy
Intensity score: | 0.440 |
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: @kerrybowen_ you have anger issues!
This tweet contains emotions: | anger, disgust |
Task: Measure the level of emotion E in the tweet using a real-valued score between 0 and 1, where 0 represents the lowest intensity and 1 represents the highest intensity. | Tweet: Me and these burns that I pick up off the pitches don't get on at all like π’π’
Emotion: anger
Intensity score: | 0.438 |
Task: Place the tweet into an appropriate ordinal class, representing the tweeter's mental state by assessing the levels of positive and negative sentiment intensity conveyed. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred. | Tweet: Q&A with N. Christie @westernuHistory: fr. @marybethstart: What would Peter and Dardanella think of us knowing? #poorthings
Intensity class: | -2: moderately negative emotional state 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: @Ganypede I notice that nice people believe in a nice god and horrid people believe in a horrid god who happens to hate everybody they hate.
This tweet contains emotions: | |
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: I'm honored to take on such a role in their joyous day. Hopefully I don't fuck it up
This tweet contains emotions: | anticipation, fear, joy, optimism |
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: My nephews n cousins are nowhere near bad guys, but they could be killed @ any moment by a cop that thought they were bc of their color
Emotion: sadness
Intensity class: | 3: high amount of sadness 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: @lmench i'm actually offended by it. naming the most fattening sandwich after a man who died of coronary disease likely due to his diet?
Emotion: anger
Intensity score: | 0.625 |
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: @PatBlanchfield so you mean βlike Uber but for despair for someone other than the driver'
Emotion: sadness
Intensity class: | 1: low amount of sadness 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: You know you're in love when all you can do is smile whenever you talk about how he is to someone.
Intensity score: | 0.621 |
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: Anger is cheap and politeness is expensive. Don't expect everybody to be polite. #ThoughtfulThursday #anger #politeness
Emotion: anger
Intensity score: | 0.312 |
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: #panic Panic attack from fear of starting new medication
Emotion: fear
Intensity class: | 3: high amount of fear can be inferred |
Task: Determine the prevailing emotional tone of the tweet, categorizing it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that most accurately represent the tweeter's mental state. | Tweet: @Lexual__ @jdspielman10 RIP to the 100s of black men,, women,CHILDREN killed in Chicago. Where is the outrage?
This tweet contains emotions: | anger, disgust, sadness |
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: Gaaaaaaaad! Should have stayed in London!
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: @ChibiReviews Post series depression can be quite bad, but it will get better, I bet someone will pick the novel soon in the west.
This tweet contains emotions: | optimism, sadness |
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: a #monster is only a #monster if you view him through #fear
This tweet contains emotions: | fear, optimism |
Task: Analyze the tweet's sentiment and assign it to either 'neutral or no emotion' or one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust). | Tweet: Never let the sadness of your past ruin your future
This tweet contains emotions: | optimism, sadness |
Task: Determine the appropriate intensity category of emotion E for the tweet, reflecting the emotional state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: Idk why people be glorifying depression. I wouldn't wish real depression upon my worst enemy. Shits the worst stop acting like it's cool
Emotion: sadness
Intensity class: | 3: high amount of sadness 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: @rupindxr my heart actually sunk looooool I was so confused
This tweet contains emotions: | sadness |
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: βWorry is a down payment on a problem you may never have'. Β Joyce Meyer. #motivation #leadership
Emotion: fear
Intensity score: | 0.292 |
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: And 9/10 the character is a woman. Because if a man is fat he's jovial. If a woman is fat she's useless and maybe evil amirite?
This tweet contains emotions: | anger, disgust |
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: Been up since 4am. Too scared to go back to sleep #nightmare β feeling scared
This tweet contains emotions: | fear, 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: @Dak2future decorations are up all over Jersey already #outrage
Emotion: anger
Intensity class: | 2: moderate amount of 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: βbut he just can't. He feels tired but also restless. So here he now, scrolling his own music player, playing some music through hisβ
Emotion: fear
Intensity score: | 0.354 |
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: I wanna go to fright fest with squad
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: @Gielnorian @HedonismGaming cmode grimrail made me want to eat angry bees
This tweet contains emotions: | anger, disgust |
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: @BigBossPeltonen \nLikewise #death #cutting #despair
Emotion: sadness
Intensity score: | 0.729 |
Task: Quantify the sentiment intensity or valence level of the tweet, giving it a score between 0 (highly negative) and 1 (highly positive). | Tweet: Aw there's a young fox outside on the grass just jumping around all playful and having a little stretch π soo cute πΊ
Intensity score: | 0.781 |
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: ο©ο©ο©ο© heads melted, very tired but can't sleep.
This tweet contains emotions: | pessimism, sadness |
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: @jamiesmart Huh! It's always my fault isn't it >:( #huff #sulk
Emotion: anger
Intensity class: | 2: moderate amount of anger 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: @LucidHurricane_ wait, you mean he wasn't armed with a book? #shocking
Emotion: fear
Intensity score: | 0.398 |
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: Crossfit houston-la homefolks as for spry proprieties regimes: AJaFUE
Emotion: joy
Intensity class: | 0: no joy 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: Impractical Jokers...practically genius!!! @BQQuinn #good4thesoul #ImpracticalJokers #bingewatching
Emotion: joy
Intensity score: | 0.750 |
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: Tip 5: Don't worry about pleasing everyone. #TitanWisdom
This tweet contains emotions: | optimism |
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: That's fucking horrific defending from Schalke
Emotion: fear
Intensity score: | 0.562 |
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: Who actually chooses to drink sparkling water π€
Emotion: joy
Intensity score: | 0.208 |
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: Well my evaluation came back and i am minimally effective. Student test scores on the PARCC sunk my eval. it's time for me to quit teaching
Emotion: sadness
Intensity score: | 0.812 |
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: when season 13 of greys anatomy premieres today. it you're only on season 7 #sadness :(
Emotion: sadness
Intensity score: | 0.625 |
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: If you ain't shaking no ass, don't ask me for my liquor. Rule #1..
Emotion: fear
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: @TalesofanAlfa @David_Milloy \nI like your thinking...but sadly no - that's the shed π’
This tweet contains emotions: | sadness |
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E). | Tweet: @markhberman2003 @LanceZierlein @790blessing entire team from coaches on down played and coached scared from jumpstreet.
Emotion: fear
Intensity score: | 0.542 |
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: Literally dying & living at the same time as I catch up on @adrian_ver 's twitter. If you aren't following him your life is BASIC.
Intensity class: | 0: neutral or mixed emotional state can be inferred |
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: @MeghanEMurphy Oh gosh, if you get 800+ raging comments from cruise fans, I will just die laughing!
Intensity class: | 3: very positive emotional state can be inferred |
Task: Assign the tweet to a specific ordinal class that corresponds to the tweeter's mental state, considering various levels of positive and negative sentiment intensity. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred. | Tweet: Like he really just fucking asked me that.
Intensity class: | -2: moderately negative emotional state can be inferred |
Task: Gauge the level of intensity for emotion E in the tweet, assigning it a score between 0 and 1. A score of 0 indicates the lowest intensity, while a score of 1 indicates the highest intensity. | Tweet: @StaceyDavidson_ You're a thief and a liberal mope, investigated by the financial services board for theft of govt retirement funds. THIEF
Emotion: sadness
Intensity score: | 0.667 |
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 not very young man compiled info on a smiling baby then a mattress created new evil.
Emotion: joy
Intensity class: | 0: no joy 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: Research has determined 70% of #laughter is actually #anxiety.
Emotion: joy
Intensity score: | 0.231 |
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: And getting offended or furious that a writers style isn;t to your taste is ultimately daft, I suppose.
This tweet contains emotions: | anger, disgust |
Task: Determine the prevailing emotional tone of the tweet, categorizing it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that most accurately represent the tweeter's mental state. | Tweet: The feeling of taking someone's life is either scarring or exhilarating, but for people need to realize that we're going to die at some--
This tweet contains emotions: | anger, disgust, fear, 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: @SSheil coincidentally watched Ulzana's Raid last night - brutally indignant filmmaking.
This tweet contains emotions: | anger, disgust |
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 feel like an appendix. I don't have a purpose. #sad #depressed #depression #alone #lonely #broken #sadness #cry #hurt #crying #life
Emotion: sadness
Intensity class: | 3: high amount of sadness can be inferred |
Task: Calculate the sentiment intensity or valence score of the tweet, which should be a real number between 0 (extremely negative) and 1 (extremely positive). | Tweet: May a man live well-, and long-enough, to leave many joyful widows behind him.
Intensity score: | 0.534 |
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: #twitter #users Tweeting on twitter is like playing a game against the computer. Where's the life, Everyone too #afraid to say something?
This tweet contains emotions: | disgust, fear, pessimism |
Task: Determine the appropriate ordinal classification for the tweet, reflecting the tweeter's mental state based on the magnitude of positive and negative sentiment intensity conveyed. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred. | Tweet: Sioux Valley wins home competitive #cheer invite with a score of 158. ...Dell Rapids second at 138
Intensity class: | 0: neutral or mixed emotional state 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: @Nick_Offerman & @MeganOMullally 's #Summerof69 show was raw sexuality and pure #mirth ! Thanks for the belly laughs and butt sex japes!
This tweet contains emotions: | joy |
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: The #secret to all of every industry: just #start doing it...somehow people forget that they never gave you #permission.' - @thomaslennon
This tweet contains emotions: | anticipation, disgust, optimism |
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: @TiburonChamber plus a hearty pour of #yachtrock by #mustacheharbor !
Emotion: joy
Intensity score: | 0.500 |