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Task: Gauge the level of intensity for emotion E in the tweet, assigning it a score between 0 and 1. A score of 0 indicates the lowest intensity, while a score of 1 indicates the highest intensity. | Tweet: 236:416 While she was in her dull and sleeping hour,\nA crew of patches, rude mechanicals,\n#AMNDBots
Emotion: sadness
Intensity score: | 0.500 |
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: @TweeriaLee A stumbling block to the pessimist is a stepping stone to the optimist.
Emotion: sadness
Intensity class: | 0: no 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: Early morning cheerfulness can be extremely obnoxious #ALDUB62ndWeeksary
This tweet contains emotions: | disgust, joy |
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: Nawaz Sharif is getting more funnier than @kapilsharmak9 day by day. #laughter #challenge #kashmir #baloch
This tweet contains emotions: | disgust, joy |
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: You will never find someone who loved you like I did. And that my love, will be my revenge.
This tweet contains emotions: | anger, love |
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: @TrueRyuga I tore my MLC playing football in HS. Knees are serious business. Take care of them! Lemme know if you need anything.
Emotion: sadness
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: Heyyyy warriors!!!!! #anxiety #panicattacks
Emotion: fear
Intensity score: | 0.854 |
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: 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: 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: @jbanks88 offense can't score 3 redzone trips no points n lbs can't pull flags n i missed a flag that lead to a td dat took da league
Emotion: anger
Intensity score: | 0.458 |
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: Leon's cheerfulness is always a big help.
Intensity score: | 0.645 |
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: life is hard., its harder if ur stupid #life #love #sadness #sadderness #moreofsad #howdoestears #whatislife
Emotion: sadness
Intensity class: | 3: high 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: A nation with a large part of the population living in #fear of the police is neither #great nor #free - it's actually a #fascist nation
This tweet contains emotions: | anger, disgust, fear |
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: @Justin_Gau @JamesMelville You certainly wouldn't catch me with the multitude. #ghastly
This tweet contains emotions: | anger, disgust, fear |
Task: Rate the intensity of emotion E in the tweet on a scale of 0 to 1, with 0 indicating the least intensity and 1 indicating the highest intensity. | Tweet: @KicchaSudeep No words Sir... Thank you for the concern..
Emotion: sadness
Intensity score: | 0.563 |
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: @xxmariab listen yh don't provoke me cos I'll make you cry
Emotion: anger
Intensity class: | 2: moderate amount of anger 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: it gets better. without explanation; you just wake up one morning and you’re just happy, totally and utterly elated.
Emotion: joy
Intensity class: | 3: high amount of joy can be inferred |
Task: Classify the mental state of the tweeter based on the tweet, determining if it is 'neutral or no emotion' or characterized by any of the provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust). | Tweet: @DirtyDucko @funder I wish I could like this twice. #hilarious
This tweet contains emotions: | joy, 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: Shame on you @SkyNews showing an elephant being hunted and killed,
Emotion: fear
Intensity score: | 0.708 |
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: @kwelbyroberts they will come and you will rejoice at their arrival.
Emotion: joy
Intensity score: | 0.458 |
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: Dad asked if I was too hungover to function today. Little does he know I stayed sober last night so i could get shit faced tonight 😅
This tweet contains emotions: | anticipation, 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: @BTS_twt people have so much negativity filled inside them but im always happy that in such a gloomy world someone like u exists Namjoon
Emotion: sadness
Intensity class: | 1: low amount of sadness can be inferred |
Task: Rate the intensity of emotion E in the tweet on a scale of 0 to 1, with 0 indicating the least intensity and 1 indicating the highest intensity. | Tweet: @MagicAndFangs 'Just by getting lost! I don't want to see you in my eyes!' Hungary huffed and crossed her arms, looking away angrily.
Emotion: anger
Intensity score: | 0.562 |
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: @IreneEstry can't wait to see you Hun #cuddles #gossip
This tweet contains emotions: | anticipation, joy, love |
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: @andreamitchell said @berniesanders not only did not play up HRC in campaigning 4 her in OH but he did not discourage 3rd Party vote. TRUE??
Emotion: sadness
Intensity class: | 0: no sadness 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: Watch this amazing live.ly broadcast by @paulzimmer #lively #musically
This tweet contains emotions: | joy, optimism |
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: @UltimateBoxer My heart because you left me for so long again\n\n*slight pout but it turned to a smile*\n\nheheh just kidding, no I'm fine-
Emotion: anger
Intensity class: | 1: low 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: Make someone happy ^_^
Emotion: joy
Intensity score: | 0.604 |
Task: Place the tweet into a specific ordinal class, which captures the tweeter's mental state by considering different levels of positive and negative sentiment intensity. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred. | Tweet: If you are going to be a nurse, learn to be a nice patient person, Jesus 🙃
Intensity class: | 0: neutral or mixed emotional state can be inferred |
Task: Estimate the strength of emotion E in the tweet by assigning it a real-valued score between 0 and 1, where 0 signifies the least intensity and 1 signifies the greatest intensity. | Tweet: @priny_baby happppy happppyyyyyy happppppyyyyy haaapppyyyy birthday best friend!! Love you lots 💖💖💖💖💖💖💖🎉🎊 #chapter22 #bdaygirl #happy #love
Emotion: joy
Intensity score: | 0.900 |
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: I'm much to full of resentment
Emotion: anger
Intensity class: | 3: high amount of anger can be inferred |
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E). | Tweet: me: are you guys dating yet #trans #nervous #blowjobs #TFB dating in mack north ohio Bewdley
Emotion: fear
Intensity score: | 0.580 |
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: @ehtesham_toi @RaviShastriOfc unfortunate decision, our players are more of superstars than cricketers. BCCI scared of their tantrums.
Emotion: sadness
Intensity class: | 0: no sadness can be inferred |
Task: Assess the magnitude of emotion E in the tweet using a real number between 0 and 1, where 0 denotes the least intensity and 1 denotes the most intensity. | Tweet: @bt_uk appointment booked between 1-6 today, waited in all day and nobody showed up, also requested a call back and never got one
Emotion: fear
Intensity score: | 0.433 |
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: @nextofficial placed order for nearly a grand SIX weeks ago, called yesterday, order 'missing' and no call back today! #shocking
Emotion: fear
Intensity score: | 0.656 |
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: @Bwana86 I can fear that someone is always following me everywhere I go. Does that make it true??
Emotion: fear
Intensity class: | 1: low amount of fear can be inferred |
Task: Determine the prevailing emotional tone of the tweet, categorizing it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that most accurately represent the tweeter's mental state. | Tweet: Evening all. Don't forget it's #RobinHoodHour TONIGHT 🏹\n\n #bizitalk #bizhour #southyorkshire #MansfieldHour #sheffieldHour #NottsHour
This tweet contains emotions: | anticipation, joy |
Task: Assess the sentiment intensity or valence level of the tweet, ranging from 0 (extremely negative) to 1 (extremely positive). | Tweet: Totally scare for this upcoming results .
Intensity score: | 0.417 |
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: @wiIdfuI we have the same age and you're 1000 times more beautiful than me! #sad 😂
This tweet contains emotions: | pessimism, sadness |
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: American Schools are lively
Emotion: joy
Intensity score: | 0.614 |
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: Remember when Joe and Quinn had a thing on glee
Emotion: joy
Intensity class: | 0: no 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: @AnsarAAbbasi John Kerry fckd u,chief justiceofpak made the statement publicly about party supporting terror what else u need#terrorstatepak
This tweet contains emotions: | anger, disgust, fear |
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: Sorry guys I have absolutely no idea what time i'll be on cam tomorrow but will keep you posted.
This tweet contains emotions: | anticipation, 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: Coulda sworn it was Interview With A Vampire. Hmmm......Mandela Effect anyone? \n#interviewwithavampire #annerice #books #horror #ilovevamps
Emotion: fear
Intensity class: | 0: no 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: and I'm up from a dream where I said something really retarded on twitter and it got like 10000 retweets
Emotion: fear
Intensity score: | 0.491 |
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: @BrianaBanksxoxo I send ya a few #playful nibbles 😉
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: @kymwhitley hello Miss Lady I'm sure today brings you happiness and laughter use your voice also to make us laugh god knows we need it
Emotion: joy
Intensity class: | 2: moderate amount of joy 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: @katiewhiskey_ @bradnarok candy corn is the greatest candy in the world when it comes to being objectively terrible
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: ... flat party and I instantly get bollocked about it. #fuming
Emotion: anger
Intensity class: | 3: high amount of anger can be inferred |
Task: Classify the tweet into one of four ordinal intensity levels, indicating the degree of emotion E experienced by the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: {Strong hands moving to firmly grope each of @WhimsicallyWild's thighs, squeezing as her digging nails extract a growl from me.}
Emotion: anger
Intensity class: | 0: no anger 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: #Talking about our #Problems is our greatest #Addiction#Break the #habitTalk about ur #Joys#quote #problemsolving #behappy
Emotion: joy
Intensity score: | 0.494 |
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: Think like a queen. A queen is not afraid to fail. Failure is another steppingstone to greatness. Oprah Winfrey
Emotion: fear
Intensity score: | 0.167 |
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: @NitashaKaul @Snehakaul2Kaul so beautiful dear, thanks,everybody knows it is in benefit of India & GOI has done this terror attack as before
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: No we didn't just bully our professor to move the Chem quiz to Monday 😂
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: A joyous first webiversary/web mitzvah to Smithsonian's @WeiPoints!! @brianwolly @jackie_mansky @bethpylieberman @bilbo @mazeltov
Emotion: joy
Intensity score: | 0.667 |
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: light shining thru a clear sparkling stream of piss ,is a sight women will never know of(also tells tht system ure system is healthy)
Intensity score: | 0.500 |
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: @JackCurryYES he's just lucky...bad pitchers...#WHATEVER...ElKracken is #legit #future #gottawearshades #LetsGoYankees
This tweet contains emotions: | anger, disgust, optimism |
Task: Place the tweet into a specific ordinal class, which captures the tweeter's mental state by considering different levels of positive and negative sentiment intensity. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred. | Tweet: Nice to see Balotelli back to his best, good player.. Just lost his way a bit!
Intensity class: | 3: very positive 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: I'm throwing myself straight into American Horror Story so I don't have time to grieve
Emotion: sadness
Intensity class: | 2: moderate amount of sadness can be inferred |
Task: Assess the magnitude of emotion E in the tweet using a real number between 0 and 1, where 0 denotes the least intensity and 1 denotes the most intensity. | Tweet: Bes! You don't just tell a true blooded hoopjunkie to switch a f*c@n' team that juz destroyed your own team. You juz don't! #insult
Emotion: anger
Intensity score: | 0.891 |
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: @ceIestialfoxx I don't even remember that part 😅 the movie wasn't terrible, it just wasn't very scary and I expected a better ending 🙄
This tweet contains emotions: | disgust, fear, joy |
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: ..... wakes up and says 'have you tried changing her nappy?' 😡👊🏼 !!!!
This tweet contains emotions: | anger, disgust, optimism, 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: It's become a verb. 'I'm gonna Villaseñor all those old contacts I don't need anymore.' #sadness @melissavcomedy #waitingforexplanation
This tweet contains emotions: | 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: dropped my birth control on the floor and cant find it cause it blends with the carpet 🙃 #joy
This tweet contains emotions: | joy |
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: @ahtareen1 @ReginalAleman @krelifa @zamansj64 @AwiexaB Very pleasing ty!
Intensity class: | 2: moderately positive 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: The #pessimist complains about the wind; the #optimist expects it to change; the realist adjusts the sails.' - William Arthur Ward\n#IGNITE
Emotion: sadness
Intensity score: | 0.271 |
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: Onus is on #Pak to act against #terror groups which find all types of support for cross border terror: #MEA
This tweet contains emotions: | fear |
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: There's a certain hilarity in people angry at protests against the national anthem or the flag when these acts are covered by 1st Amendment.
Emotion: joy
Intensity score: | 0.312 |
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: but throughout that entire thing I was shaking rlly bad and my heart was racing and I was almost in tears lmao (thanks mr.*****)
Emotion: fear
Intensity score: | 0.917 |
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: @ScottAdamsSays broke it down on #snap great analysis on #CNBC
Intensity class: | 0: neutral or mixed emotional state 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: It's amazing how something gets stuck in your head, and you can't shake a memory... Sometimes, I miss people a lot. Wish they knew.
Intensity score: | 0.532 |
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: Wazza blocks Carrick's shot and then misses a sitter that Memphis, who was ready beside him, surely wouldve buried. Good start lol #MUFC
Emotion: fear
Intensity score: | 0.333 |
Task: Analyze the tweet's emotional connotations and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best portray the tweeter's mental state. | Tweet: I've been loving you too long #OtisRedding #blues
This tweet contains emotions: | joy, love |
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: What is this miserable ass weather all about 😭 dark and gloomy #depressing #weekoff #wheresthesun
Emotion: fear
Intensity score: | 0.600 |
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: Patti seems so sad. She stamped and ran behind the sofa. We will have to give her plenty of love and affection...more than usual. #sad
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: #BB18 Michelle crying again #shocking #bitter He's just not that into you 😢#TeamNicole
Emotion: fear
Intensity score: | 0.521 |
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: A 'non-permissive environment' is also called a 'battleground' - #MilSpeak
This tweet contains emotions: | disgust, 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: @flutterpolitely she is from the heyday 80's -could go either way, writing should be stronger but don't know who will be sacrificed first
Emotion: joy
Intensity class: | 0: no joy 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: Nothing worse than an uber driver that can't drive.
Emotion: fear
Intensity class: | 0: no fear can be inferred |
Task: Assess the magnitude of emotion E in the tweet using a real number between 0 and 1, where 0 denotes the least intensity and 1 denotes the most intensity. | Tweet: Joes gf started singing all star and then Joe got angry and was all sing it right and started angrily singing it back at her
Emotion: anger
Intensity score: | 0.521 |
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: @theAliceRoberts @FryRsquared @AdamRutherford They've obviously never tried 'repressing' a red head #fiery
Emotion: anger
Intensity class: | 2: moderate amount of anger 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: @WSJNordics You make the world a more joyful place. #TheNiceBot
Intensity score: | 0.610 |
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 like cycling because I get to intimidate people with my powerful calves & horrendous tan lines.
Emotion: fear
Intensity score: | 0.250 |
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 the sadness leaves you broken in your bed, I will hold you in the depths of your despair, and it's all in the name of love 🎶
Emotion: sadness
Intensity class: | 2: moderate amount of sadness 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: Rec'd call 2day from Haitian church we started in Florida some 15yrs ago. Preparing to acquire their own bldg. Wanted me to know. #rejoicing
Intensity class: | 2: moderately 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: @FoRDaYS14 😳 chewing what? #smile #arcdental #turlock
Intensity class: | 0: neutral or mixed emotional state 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: @destaneex @ProSyndicate @EGX oh don't panic he's gonna be there
Emotion: fear
Intensity score: | 0.438 |
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: Has September been dull? Get #SuperSeptember from Jumia Food as a new user. Order from The Place, Barcelos or Shawarma & Co for 30% off
This tweet contains emotions: | anticipation, joy, optimism |
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: @Thebeast_ufc what happened to the suicide tweet it was a joke obviously how could that offend anyone?🤔
This tweet contains emotions: | anger, fear, sadness, surprise |
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: @UKBlogAwards @ModishMale I would always be honest but it's great to feedback opinion to the brand - don't want to offend them #BlogHour
Emotion: anger
Intensity score: | 0.438 |
Task: Assess the magnitude of emotion E in the tweet using a real number between 0 and 1, where 0 denotes the least intensity and 1 denotes the most intensity. | Tweet: A tummy full of steak, wine, key lime pine and cuddles on tap. What a way to turn around a stressful Wednesday 💛
Emotion: sadness
Intensity score: | 0.188 |
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: @TheMoosesAngel He looks down at his brother, a smile forming on his face. 'What? People fearing me?'
Emotion: fear
Intensity score: | 0.333 |
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: Fingers crossed I can finish all my work early enough this Friday in time to catch @Raury at LIB 😦 #timetogrind
This tweet contains emotions: | anticipation, 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: I just killed a spider so big it sprayed spider guts on me like a horror movie.\n#ugh #revenge
Emotion: anger
Intensity class: | 2: moderate amount of anger can be inferred |
Task: Classify the tweet into one of four ordinal intensity levels, indicating the degree of emotion E experienced by the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: Ready for that nice, breezy, calm, sunshine weather.🍂🍁 #Autumn
Emotion: joy
Intensity class: | 2: moderate amount of joy 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: Rooney is 5 yards off the pace in a League Cup game against Northampton Town. Let that sink in for a moment. #MUFC
Emotion: sadness
Intensity score: | 0.292 |
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: @JohnMayer No DSM shows. #sadness
Emotion: fear
Intensity class: | 0: no fear can be inferred |
Task: Determine the degree of intensity for emotion E in the tweet, giving it a score between 0 and 1, where 0 signifies the least intensity and 1 signifies the greatest intensity. | Tweet: I'm doing all this to make sure you smiling down on me bro
Emotion: joy
Intensity score: | 0.387 |
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: Went to bed a 1:30, fell asleep after, my niece started crying at 4. I'm dying... 😧
Emotion: sadness
Intensity score: | 0.674 |
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: @louiseannexx u fucked my house up I'll always hold a grudge
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: *gets crushes on fictional and animated characters instead if real people*
Emotion: joy
Intensity score: | 0.300 |
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