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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 life in one word is depressing
Emotion: sadness
Intensity class: | 3: high amount of sadness can be inferred |
Task: Categorize the tweet based on the intensity of the specified emotion E, capturing the tweeter's mental state. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: @JoeShennan Meanwhile @JoshuaMurrayBM and I are getting a 7.40am train. I hope you really, really enjoy that hotel, Shennan. #fuming
Emotion: anger
Intensity class: | 2: moderate amount of 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: @blessspalding awe isa love u hoe thanks
Emotion: fear
Intensity score: | 0.208 |
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: Shame on you @SkyNews showing an elephant being hunted and killed, #shocking
Emotion: fear
Intensity class: | 2: moderate amount of fear 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: i already gets aggravated too fast like why aggravate me on purpose?
Emotion: anger
Intensity class: | 2: moderate amount of anger can be inferred |
Task: Identify the primary emotion conveyed in the tweet and assign it to either 'neutral or no emotion' or one or more of the provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best capture the tweeter's mental state. | Tweet: @RoyEnglish roy as fiery
This tweet contains emotions: | anger, anticipation, disgust |
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: Rollover car crash on warren st, traffic is horrid #Boston
Emotion: fear
Intensity score: | 0.583 |
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: @ltsukis im love you, even if you bully me sadly
This tweet contains emotions: | joy, love, sadness |
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: MC: what are you listen to these days?\nBogum: these days I feel gloomy, I listen to ccm (spiritual song) often.\n\nChurch oppa mode. :)
Intensity class: | -1: slightly negative 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: @lethargytyler ehhh I guess. I want to everyone I've ever burst out laughing in front ofπ
Emotion: anger
Intensity class: | 0: no anger can be inferred |
Task: Categorize the tweet based on the intensity of the specified emotion E, capturing the tweeter's mental state. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: @TheCatCampbell I too am Ravenclaw. #sadness #shouldhavebeenhufflepuff
Emotion: sadness
Intensity class: | 2: moderate amount of sadness can be inferred |
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: that's my breezy breezy breezy that's my breezy that's my buzzinnnnnn.
Intensity class: | 1: slightly positive 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 The Worst Place You Can Be Is In Your Own Head.'\n\n#quotes #worstenemy #depression #thinktoomuch
Emotion: sadness
Intensity score: | 0.854 |
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: One point: DSP claims YTers lost half their viewership in 2012 if they weren't using direct capture. That's when the search changes happened
This tweet contains emotions: | |
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: @tomsteinfort expected i thought #fear
Emotion: fear
Intensity score: | 0.639 |
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: Watching the NY Phil webcast. Something missing. Reminds me of a blithe Journey's End I once saw on Bway. Might just be the Gershwin.
Emotion: joy
Intensity class: | 0: no 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: @rohan_connolly i think your high-profile female colleague would be one in yhat category... #massexodus #bitter
This tweet contains emotions: | anger, disgust, sadness |
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: I found #marmite in Australia. `:) #happy
Intensity class: | 3: very positive emotional state can be inferred |
Task: Categorize the tweet into an intensity level of the specified emotion E, representing the mental state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: @MSNBC @fox @cnn @realDonaldTrump @HillaryClinton. Using fear to state his views. Not getting the facts before making a serious statement???
Emotion: sadness
Intensity class: | 0: no sadness can be inferred |
Task: Classify the tweet's emotional intensity into one of four ordinal levels of emotion E, providing insights into the mental state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: Why is it when you nap during the day you are so comfortable but sleeping at night you'll never be as comfortable
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: Check out this #film Robocoq 301 #animated #shortfilms
Emotion: joy
Intensity class: | 1: low 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: A 'non-permissive environment' is also called a 'battleground' - #MilSpeak
Emotion: joy
Intensity class: | 0: no 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: @wabermes The @RavalliRepublic had a good one but then the reporter quit. #sad
Emotion: sadness
Intensity class: | 3: high amount of sadness can be inferred |
Task: Determine the prevailing emotional tone of the tweet, categorizing it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that most accurately represent the tweeter's mental state. | Tweet: @Virgin_TrainsEC I feel for the conductor tonight, he's obviously taken grief over the last few weeks, he sounds weary of apologising!
This tweet contains emotions: | sadness |
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 had Golden Ocean the other day it was lush, then I gagged and was sick... What a waste of Β£20 - I was fuming @EmmaGould_ I miss you
Emotion: anger
Intensity class: | 3: high amount of 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: @ErinAndrews I β€οΈyou on DWTS You make my night every show! π
This tweet contains emotions: | joy, love |
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: Hate when guys cant control their anger ππ
Emotion: anger
Intensity score: | 0.646 |
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: @AnneMarieIAm Heard #alarm 1. time in Germany today #youFM, TG finally .. and far far too late. Germany always late w UK artists!!π‘π
Emotion: fear
Intensity class: | 0: no fear can be inferred |
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: I get embarrassed at the slightest things and then I'll fret about it all day I hate it
Intensity class: | -2: moderately negative emotional state 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: why the fuck does my mum want me to put corn in the curry?! #grim
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: @DSWT I despair at this madness! It's beyond #shocking it's cold blooded murder! How long will #SouthAfrica stand by &watch #WorldRhinoDay
Emotion: fear
Intensity score: | 0.771 |
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: 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 valence intensity of the tweeter's mental state on a scale of 0 (most negative) to 1 (most positive). | Tweet: Girls with hairy arms scare me
Intensity score: | 0.367 |
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: @daveweigel a laurel and hearty handshake
This tweet contains emotions: | joy, optimism |
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: @tweet_faver its reaper!! before he became reaper, you can find their stories on the wiki and thru the comics and animated shorts!
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: Never let me see you frown
Emotion: sadness
Intensity score: | 0.312 |
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: Ugh I want to punch a wall every time I have to use @windows 10. Literally the worst product ever made #windows10 #awful #killme
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: and claimed that all of the same things could scare us\nbut we were tough because of ancestry
Emotion: fear
Intensity score: | 0.542 |
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: @happyandbashful @Teigngardener @CEVokins @gardengirllucy Don't provoke the Voke.
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: Side chick's be trying to fuck u like your going to forget about your wife when your done. #terrible
Emotion: fear
Intensity score: | 0.500 |
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: @FilthyFrank My first time watching your vids and i died of laughter. Keep this up dude
Intensity score: | 0.793 |
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: Did you know I specialise in #anxiety and #panic attacks? Get in touch for all of my solutions for you. #Coventry
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: don't provoke me after letting me down !
Emotion: anger
Intensity score: | 0.521 |
Task: Gauge the level of intensity for emotion E in the tweet, assigning it a score between 0 and 1. A score of 0 indicates the lowest intensity, while a score of 1 indicates the highest intensity. | Tweet: We have been a better second half team this season. So there's that.
Emotion: joy
Intensity score: | 0.200 |
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: Happy Birthday shorty. Stay fine stay breezy stay wavy @daviistuart π
Emotion: joy
Intensity class: | 2: moderate amount of joy 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: Romero, Rojo, Blind, Memphis, Rooney. This is nearly a starting line up Iβd wanna punch in the face rather than shake their hand.
Emotion: fear
Intensity score: | 0.438 |
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: On the last episode of #MakingAMurderer poor Brendan glad they #appeal it #crime #documentary #reallife
This tweet contains emotions: | joy |
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: Hi Luke hemmings\n\nππΈπ\n\nIf I had a flower for every time you made me smile, I'd have a garden. Please follow me? \n\nππΈπ\nI love you. x16,092
This tweet contains emotions: | joy, love, optimism |
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: @Bluebelle89 @lsmith855 liking the optimism
Emotion: joy
Intensity class: | 2: moderate amount of joy 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: sav tells our mom 'I love you' and she responds 'Oh.' #sad
This tweet contains emotions: | disgust, sadness |
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: @HillaryClinton evidently @realDonaldTrump feels above #norms. SHOW the #tax return, if you have nothing to
Intensity score: | 0.383 |
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: @PatBlanchfield so you mean βlike Uber but for despair for someone other than the driver'
Emotion: fear
Intensity class: | 0: no fear can be inferred |
Task: Quantify the sentiment intensity or valence level of the tweet, giving it a score between 0 (highly negative) and 1 (highly positive). | Tweet: broken policy' #blasio <> #trump #giuliani 'broken windows' all part of 'pecking order' #bully politics #america RESIST #motto
Intensity score: | 0.375 |
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: At my funeral, when they close the casket, I want them to play, 'Call recording has completed.'' -@GlenEwing #lost #podcasting #talkshoe
Emotion: sadness
Intensity class: | 1: low 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: #Taurus, for the most part, you have perfect control over your Emotions and you are careful not to be so sulky around anyone!
This tweet contains emotions: | optimism |
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E). | Tweet: @KhaleesiofFood @BB_Updates she has stayed off the block almost all season, got out people that were good for her game, but no one seemed
Emotion: sadness
Intensity score: | 0.333 |
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 hope a goal comes soon on either side. Otherwise there is a serious threat of a dull and frustrating game. #COYS
This tweet contains emotions: | anger, disgust, pessimism, 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: Hate being sober so I popped two
Emotion: sadness
Intensity class: | 2: moderate amount of sadness can be inferred |
Task: Determine the prevailing emotional tone of the tweet, categorizing it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that most accurately represent the tweeter's mental state. | Tweet: @amychozick @jswatz Not a word about terrorism.
This tweet contains emotions: | anger, anticipation, disgust, fear |
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: @JustinTrudeau opened doors to terrorism and he will pay for it. @CP24 @globalnewsto
Emotion: fear
Intensity score: | 0.562 |
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: #AnthonyWeiner #DISTRACTION #what is really going on? #selection #election #Syria #race #riots #GasCrisis2016 #NoDAPL #rape
This tweet contains emotions: | anger, disgust |
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: @residentadvisor thanks for getting back to me, exemplary customer service for a loyal customer #jk #residentadvisor #poorservice
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: I forgot #BB18 was on tonight ο³ that is how much the real world has been distracting me #horrid ο
οΌοο
Emotion: fear
Intensity class: | 0: no fear 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: @simmy_hanley @Schrise also a
Emotion: joy
Intensity score: | 0.340 |
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: @goofoffartiste Ah, the Grand Old Paradox that is fearing the encroachment of the state but loving unconditionally its paid enforcers
This tweet contains emotions: | fear, joy, love, 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: Now ...what to do for the next hour while waiting for #OurGirl to start @BBCOne ?!
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: @jonfavs Don King is an insult to the intelligence of the Black Community. What are these people thinking?
Intensity score: | 0.207 |
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: @PixelMonsterYT @TeamGE0 @IZEDEPTIC @ztumtum @CrimtideTV @LtGrandslam @Slinkercorn Bahahahaha Dean looks hilarious and damn I got fat
This tweet contains emotions: | joy, optimism, surprise |
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: Sometimes the best motivations come from 'proving them wrong' #energy #relentless #MotivationalQuotes
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: @CornflakeDaddy @youngvulgarian Yeah, it was sooo horrific, I needed to sit down
Emotion: fear
Intensity score: | 0.792 |
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: Up on melancholy hill
Intensity score: | 0.339 |
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: Every time people push #Prescription Pot, prohibitionists rub their hands with #glee because U hand them #Cannabis & yourself into #slavery.
Emotion: joy
Intensity score: | 0.271 |
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 just killed a spider so big it sprayed spider guts on me like a horror movie.\n #ugh
Emotion: anger
Intensity class: | 0: no anger can be inferred |
Task: Categorize the tweet based on the intensity of the specified emotion E, capturing the tweeter's mental state. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: Sorry @wow_air definitely going with @Icelandair next time, this is beyond unreasonable @wowairsupport #yourappologiesmeannothing
Emotion: fear
Intensity class: | 0: no fear can be inferred |
Task: Determine the appropriate intensity category of emotion E for the tweet, reflecting the emotional state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: No, just tweet pictures of four fictional characters who describe you. One should be an animated character. @sunshinessp411
Emotion: joy
Intensity class: | 0: no joy 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: @victoriarghhh not mad but tilting? slightly irate? is that cool?
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: @Aliki111 Haters!!! You are low in self worth. Self righteous in your delusions. You cower at the thought of change. Change is inevitable.
Emotion: fear
Intensity score: | 0.562 |
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: @APkrawczynski Any possibly KG is being bought out as a player so that he can buy in from Glen as a minority owner?
Emotion: joy
Intensity class: | 0: no joy 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: With a jovial Trump on his ass, Don King just publicly told a crowd that 'We need [him] because you will always be a nigger.' #FuckTrump
This tweet contains emotions: | anger, disgust, sadness |
Task: Classify the mental state of the tweeter based on the tweet, determining if it is 'neutral or no emotion' or characterized by any of the provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust). | Tweet: some of the casuals tweets that Vic has faved are making me gag
This tweet contains emotions: | disgust, joy, 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: @GSchwartz_ it wasn't a joke .
Emotion: fear
Intensity class: | 0: no fear 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: A joyous first webiversary/web mitzvah to Smithsonian's @WeiPoints!! @brianwolly @jackie_mansky @bethpylieberman @bilbo @mazeltov
Emotion: joy
Intensity score: | 0.667 |
Task: Assign a suitable level of intensity of emotion E to the tweet, representing the emotional state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: Watch this amazing live.ly broadcast by @footballrocks123456 #lively #musically
Emotion: joy
Intensity class: | 2: moderate amount of joy 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: Newly engaged Stevie Wonder has been trying to disguise #the #awful smell from his throat: with a leather jacket made from a broken Wii.
Emotion: fear
Intensity class: | 0: no fear can be inferred |
Task: Analyze the tweet's emotional connotations and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best portray the tweeter's mental state. | Tweet: @jbiggy13 @ToneCapone111 ya and the d was what I was most confident about..... our offense is as good as it's been in 20 years...our d sucks
This tweet contains emotions: | anger, disgust |
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: Feeling like I've had the worst night of sleep ever - not great before the #London to #Brighton #cycle ride for @DMTFYP π΄100k #apprehension?
Emotion: fear
Intensity score: | 0.604 |
Task: Place the tweet into a specific intensity class, reflecting the intensity of the mentioned emotion E and the user's mental state. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: Even after @O2 ref the Β£5k fraud, they still treat me like dirt. No returned calls or apology #shocking #customerservice @mse @resolvercouk
Emotion: fear
Intensity class: | 0: no fear 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: @S_Moore24 wow that sounds terrific
Emotion: fear
Intensity score: | 0.146 |
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: βDo not fret if you are not cool! Humans who follow me, become instantly cool!β #Bot
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: Loving @Speechless_ABC so far. Just hilarious and @driverminnie is wonderful. #hilarious #Bravo ππ»ππ»
Emotion: joy
Intensity score: | 0.750 |
Task: Determine the dominant emotion in the tweet and classify it as either 'neutral or no emotion' or one of the eleven provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust). | Tweet: I shower to lay in bed for about an hour then dread wearing pants for the remainder of the day
This tweet contains emotions: | disgust, fear, joy, sadness |
Task: Estimate the strength of emotion E in the tweet by assigning it a real-valued score between 0 and 1, where 0 signifies the least intensity and 1 signifies the greatest intensity. | Tweet: Wine drunk is the worst version of myself ffs, don't even remember seeing basshunter
Emotion: fear
Intensity score: | 0.375 |
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: I just love it when people make plans for me without actually including me in this process #rage
Emotion: anger
Intensity score: | 0.688 |
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: @happyandbashful Flirt, simper, pout, repeat. Yuck.
This tweet contains emotions: | anger, disgust |
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 life went from happy to unhappy..
Emotion: sadness
Intensity score: | 0.812 |
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: but losing these games are the worst, you end up feeling a mixture of anger and sadness and shame and anxiety and it lasts for days
Intensity class: | -3: very negative emotional state can be inferred |
Task: Assign a suitable level of intensity of emotion E to the tweet, representing the emotional state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: We are about a little over an hour away! We will arrive soon, do not fret!
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: @luckiiCHARM_ Luckii, I'm changing in so many ways bc of Him!! It's a scary but joyful feeling, making me so strong.
This tweet contains emotions: | fear, 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: @Phin_MacCool Thatβs shocking
This tweet contains emotions: | fear, surprise |
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: @Nick_Offerman I'll be there!! Can't wait for all the #mirth!
Emotion: joy
Intensity score: | 0.646 |
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