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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: -- used as a pawn in this red woman's game] For now, try not to fret and act as if nothing is amiss. This is a royal -- @TheLadyOfGlenco
Emotion: sadness
Intensity score: | 0.354 |
|
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: @brian5or6 turn that shit off! Home Button under Accessibility. \n\nWhen did innovation become mind fuckery? . #iphonePhoneHome
Emotion: anger
Intensity class: | 3: high amount of anger can be inferred |
|
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: @PersephoneOD Her cheerful voice echoed through the grand, familiar home, a smile blossoming on my rosy brims, 'Mom.' I reciprocated the --
Intensity score: | 0.739 |
|
Task: Determine the valence intensity of the tweeter's mental state on a scale of 0 (most negative) to 1 (most positive).
Tweet: @S_Moore24 wow that sounds terrific
Intensity score: | 0.661 |
|
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: @kingvee_ don't provoke me to anger
Emotion: anger
Intensity class: | 3: high amount of anger can be inferred |
|
Task: Measure the level of emotion E in the tweet using a real-valued score between 0 and 1, where 0 represents the lowest intensity and 1 represents the highest intensity.
Tweet: #PiersGough on thoroughly lively and imaginative developers—“Sager have always challenged us to do better and do better.” @IslingtonSq
Emotion: joy
Intensity score: | 0.340 |
|
Task: Quantify the sentiment intensity or valence level of the tweet, giving it a score between 0 (highly negative) and 1 (highly positive).
Tweet: Some moving clips on youtube tonight of the vigil held at Tulsa Metropolitan Baptist church for #TerenceCruther #justice #anger #sadness
Intensity score: | 0.194 |
|
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: or when someone tells me I needa smile like excuse me ??? now I'm just frowning even harder are you happy
Emotion: sadness
Intensity score: | 0.500 |
|
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: Really.....#Jumanji 2....w/ The Rock, Jack Black, and Kevin Hart...are you kidding me! WTF! #ThisIsATerribleIdea #horrible
Emotion: fear
Intensity class: | 0: no fear can be inferred |
|
Task: Classify the mental state of the tweeter based on the tweet, determining if it is 'neutral or no emotion' or characterized by any of the provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).
Tweet: I aspire to have Val's self confidence and optimism tbh 👏💖 #GBBO
This tweet contains emotions: | joy, optimism |
|
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: I'm allowed to sulk
Emotion: sadness
Intensity score: | 0.729 |
|
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: A lifetime of laughter at the expense of the death of a bachelor
Emotion: joy
Intensity class: | 0: no joy can be inferred |
|
Task: Assess the magnitude of emotion E in the tweet using a real number between 0 and 1, where 0 denotes the least intensity and 1 denotes the most intensity.
Tweet: If you love something, let it go. If it comes back, it is yours. If it doesn't, it never will. #sadness #accepting
Emotion: sadness
Intensity score: | 0.771 |
|
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: #rocklandcounty get to ravis in suffern, ny. Great food, new #chef, terrific atmosphere. Say 'twitter' to server and get free #appetizer
Emotion: fear
Intensity score: | 0.125 |
|
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: Don't blame yourself,' he spoke, as if she were in the room, kicking the chair beneath him.\n#amwriting #dark
Emotion: sadness
Intensity score: | 0.479 |
|
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: Marcos Rojo Marcos Rojo running down the wing. Loved by the blues, feared by the reds
This tweet contains emotions: | anticipation, joy, love, optimism, trust |
|
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: Could not be happier!! #happy
This tweet contains emotions: | joy, love, optimism |
|
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: Getting so excited for @ClearwaterJazz 2016!! We play the main stage Sunday Oct. 16 at 3:30!! #jazzholiday #riesbrothers #rock #blues #jam
Emotion: sadness
Intensity score: | 0.125 |
|
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: @virginmedia I've been disconnected whilst on holiday 😤 but I don't move house until the 1st October 🤔
This tweet contains emotions: | anger |
|
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: @BBCTomEnglish @TimesSport And the dreadful Franglaise.
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: @EmmyMitchell_ hahahaha you're ridiculous!!! But thank you a joyous evening xx
Emotion: joy
Intensity score: | 0.815 |
|
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: Misery loves company. The church ought to be a place where it finds none.\n-Pastor Kris Theobald #joy
Emotion: joy
Intensity class: | 0: no joy can be inferred |
|
Task: Categorize the tweet's emotional tone as either 'neutral or no emotion' or identify the presence of one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).
Tweet: @lukeshawtime terrible
This tweet contains emotions: | anger, disgust |
|
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: Putin feels it acceptable to bomb & kill aid workers. Soon he may be sitting at the same table as Trump!! #Armageddon #USApleasedont
This tweet contains emotions: | anger, anticipation, 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: Delete this shit Josh just screenshotted my snap me
Emotion: anger
Intensity score: | 0.583 |
|
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: @dc_mma @ChampionsFight think shes afraid to fight Holly. One can only imagine what goes through her head when she thinks of Cyborg
Emotion: fear
Intensity class: | 2: moderate amount of fear 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: @JamieSmart93 that was shocking!
Emotion: fear
Intensity class: | 0: no fear 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: @CallofDuty how do u guys determine teams? Cause I'm 80% on shitty teams when I play and I'm fuckin over it #cod
This tweet contains emotions: | anger, disgust |
|
Task: Assess the emotional content of the tweet and classify it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best represent the tweeter's mental state.
Tweet: #2 complained then while his head and then called do not despair of God's mercy if you did sins go back to him and ask his forgiveness
This tweet contains emotions: | optimism |
|
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 freaking hate working with #word on my phone #write #writing #writerslife #writerproblems #writer
This tweet contains emotions: | anger, disgust |
|
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: When my life became such a concern to irrelevant ass people I'll never know
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: Stuck in a infuriate scrum about hegemonists. #scrum #scrum #Stuck
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: @Patsy1207 @markheardusa @theinquisitr Do your fuc*ing job and report the news.Just another bully to go in the basket.Freedom or fear???
Emotion: fear
Intensity score: | 0.583 |
|
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: @_Mrs_Peel @lp_lisa @PaulRGoulden @LisaLuscious Might be the pout of a star baker tho !
Intensity score: | 0.435 |
|
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: Can't believe @virginmedia are putting their prices up!! They already know I'm struggling to pay my bill & won't change my package!! #raging
Emotion: anger
Intensity class: | 3: high 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: @hotpatooties more like quickie divorce
Emotion: fear
Intensity score: | 0.216 |
|
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: @samsteinhp stop the presses, @realDonaldTrump said/proposed something racist.
This tweet contains emotions: | anger, disgust |
|
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: My blood is boiling
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: What I would give\nTo feel the sunlight on my face\nWhat I would give\nTo be lost in your embrace 🎧\n\n#Fallen
Emotion: sadness
Intensity class: | 2: moderate amount of sadness 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: 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: 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: alternate reality where @PoetryFound has a comments section and you can give poems a cheery thumbs up or a disappointed thumbs down
Emotion: joy
Intensity class: | 0: no joy can be inferred |
|
Task: Determine the prevailing emotional tone of the tweet, categorizing it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that most accurately represent the tweeter's mental state.
Tweet: @AskLloydsBank #worst exec complaints ever #horrific customer journey
This tweet contains emotions: | anger, disgust |
|
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: The #most wasteful day is a #day without
Emotion: joy
Intensity score: | 0.120 |
|
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: @Sami_3499 Oh noooo! #nomorehammocks #nightmare ;)
Emotion: fear
Intensity score: | 0.625 |
|
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: Taking umbrage because Jimmy Carr claimed that Bilbo Baggins went to Mordor on 8 out of 10 cats does Countdown. Know your Baggins', mate.
Emotion: anger
Intensity score: | 0.375 |
|
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 emotional state can be inferred. 2: moderately positive emotional state can be inferred. 1: slightly positive emotional state can be inferred. 0: neutral or mixed emotional state can be inferred. -1: slightly negative emotional state can be inferred. -2: moderately negative emotional state can be inferred. -3: very negative emotional state can be inferred.
Tweet: A 28 yr old man threw a saucepan of boiling water at a garda, & then hit the garda with the shaft of a brush...Letterkenny District Court.
Intensity class: | -2: moderately negative emotional state can be inferred |
|
Task: Assign one of four ordinal intensity classes of emotion E to a given tweet based on the emotional state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.
Tweet: @ShannonBeador we know the truth about her, the public is figuring it out. Her words mean nothing. #unhappy #mean #troubled #vile #bully
Emotion: sadness
Intensity class: | 2: moderate amount of sadness can be inferred |
|
Task: Categorize the tweet's emotional expression, classifying it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that reflect the tweeter's state of mind.
Tweet: I found #marmite in Australia. `:) #happy
This tweet contains emotions: | joy, love |
|
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: It's the most magical time of the year......Xmas party announced and the #outrage commences. Gotta love Silicon Valley millennials.
This tweet contains emotions: | joy, love, optimism |
|
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: @billie21806 @cnnbrk tell that to your bodies cheering on the deaths of black people by cops. their fear is killing us.
This tweet contains emotions: | anger, disgust, fear, pessimism, sadness |
|
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: In addition to fiction, wish me luck on my research paper this semester. 15-20 pages, oh boy.
This tweet contains emotions: | anticipation, fear, optimism, trust |
|
Task: Categorize the tweet's emotional expression, classifying it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that reflect the tweeter's state of mind.
Tweet: A warm #smile is the universal language of kindness William Arthur Ward #love #kindness
This tweet contains emotions: | joy, love, optimism |
|
Task: Assess the magnitude of emotion E in the tweet using a real number between 0 and 1, where 0 denotes the least intensity and 1 denotes the most intensity.
Tweet: #Afghanistan Vice President Sarwar Danish slams #Pakistan for breeding #terrorism during UNGA address\n@UN #USA
Emotion: fear
Intensity score: | 0.583 |
|
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 emotional state can be inferred. 2: moderately positive emotional state can be inferred. 1: slightly positive emotional state can be inferred. 0: neutral or mixed emotional state can be inferred. -1: slightly negative emotional state can be inferred. -2: moderately negative emotional state can be inferred. -3: very negative emotional state can be inferred.
Tweet: Lets get this Astros/A's game going already! We're going to need all 5 of you in attendance to cheer the A's to victory!
Intensity class: | 0: neutral or mixed emotional state 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: @DJ_Musicologist #Disney's 1994 #animated #musical #film #TheLionKing was influenced by #WilliamShakespeare's #Hamlet. Songs by #EltonJohn.
This tweet contains emotions: | anticipation, joy |
|
Task: Determine the degree of intensity for emotion E in the tweet, giving it a score between 0 and 1, where 0 signifies the least intensity and 1 signifies the greatest intensity.
Tweet: @iamsrk what's up w the gender bias? #indignant This fancypants saddler's daughter will opt for the leather jacket, thank you very much.
Emotion: anger
Intensity score: | 0.500 |
|
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: Evening all. Don't forget it's #RobinHoodHour TONIGHT 🏹\n\n#bizitalk #bizhour #southyorkshire #MansfieldHour #chirp #sheffieldHour #NottsHour
Emotion: joy
Intensity score: | 0.442 |
|
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: @SageHillfarms @HintonAlisa @hb_heather Hey, Jayme! Were your👂👂 burning cuz I was talking about you?😁 Are you going tomorrow?
This tweet contains emotions: | anger, anticipation |
|
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: That was a fast response madrid.....Zidane threaten unuh
Emotion: fear
Intensity score: | 0.396 |
|
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: Leon's cheerfulness is always a big help.
Emotion: joy
Intensity score: | 0.625 |
|
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: Gas prices are hilarious. Cause they're simultaneously super subsidised and taxed
Emotion: joy
Intensity class: | 0: no joy can be inferred |
|
Task: Categorize the tweet's emotional tone as either 'neutral or no emotion' or identify the presence of one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).
Tweet: @_MrAminuddin @ejainews @_AlifH @AhmadFuadAdnan dont play with this master noob u want to win.. #serious
This tweet contains emotions: | neutral or no emotion |
|
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: Celtic sure know how to send a wild shiver down your spine
Emotion: fear
Intensity class: | 2: moderate amount of 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: Some People hate nothing more than a happy confident person. Never mind #confident
Emotion: joy
Intensity score: | 0.318 |
|
Task: Categorize the tweet into one of seven ordinal classes, representing different degrees of positive and negative sentiment intensity, that most accurately reflects the emotional state of the Twitter user. 3: very positive emotional state can be inferred. 2: moderately positive emotional state can be inferred. 1: slightly positive emotional state can be inferred. 0: neutral or mixed emotional state can be inferred. -1: slightly negative emotional state can be inferred. -2: moderately negative emotional state can be inferred. -3: very negative emotional state can be inferred.
Tweet: Better mood today! Bring me #teasing, #flirting, #xdressers, #laughter, and #roleplayers! Also #confessions and #secrets @underdeskloser
Intensity class: | 2: moderately positive emotional state can be inferred |
|
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 emotional state can be inferred. 2: moderately positive emotional state can be inferred. 1: slightly positive emotional state can be inferred. 0: neutral or mixed emotional state can be inferred. -1: slightly negative emotional state can be inferred. -2: moderately negative emotional state can be inferred. -3: very negative emotional state can be inferred.
Tweet: @SimplyMayaMarie @STILLStanding_B 😂😂😂 y'all know I'm crazy its just shocking that's all
Intensity class: | 1: slightly positive 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: Yes I am picking up sticks and pine cones in my front yard
Emotion: sadness
Intensity score: | 0.167 |
|
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: #smile every morning to a positive head start with your #clients relations
Emotion: joy
Intensity score: | 0.562 |
|
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: Come and join in with #cakeclubhour tomorrow afternoon from 3pm! #bizhour
Emotion: joy
Intensity score: | 0.439 |
|
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: When you realize there is #NoHopeForHumanity so you just #start focusing on what's #best for you.
Emotion: fear
Intensity score: | 0.542 |
|
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: @FullTimeDEVILS Memphis looking bright. Rojo looking like Rojo.
Emotion: joy
Intensity score: | 0.473 |
|
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: 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: 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: Dates in the glove box' is pure panic excuse #GBBO
Emotion: fear
Intensity score: | 0.688 |
|
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 emotional state can be inferred. 2: moderately positive emotional state can be inferred. 1: slightly positive emotional state can be inferred. 0: neutral or mixed emotional state can be inferred. -1: slightly negative emotional state can be inferred. -2: moderately negative emotional state can be inferred. -3: very negative emotional state can be inferred.
Tweet: Not sure if thats an accomplishment or something to worry about
Intensity class: | -1: slightly negative emotional state 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: Am I the only person who dislikes fall? #FirstDayofFall #leaves #thingsdie #depressing #cold #noflipflops 👎🏾👎🏽👎🏻🍂🍁
This tweet contains emotions: | anger, disgust, sadness |
|
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: @alyssasimpson21 I gave up KENDRICK LAMAR to eat barbecue with him. #bitter
This tweet contains emotions: | anger, anticipation, disgust, sadness |
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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: @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??
This tweet contains emotions: | anticipation, surprise |
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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: We have left #Maine. #sadness
Emotion: sadness
Intensity score: | 0.771 |
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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: @MacEngelProf as a fact for levity, movie theaters on Post actually did play the N.A when I served; was the best part of movies like TheHulk
Emotion: joy
Intensity score: | 0.302 |
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Task: Determine the sentiment intensity or valence score of the tweet, representing the tweeter's mental state on a continuum from 0 (highly negative) to 1 (highly positive).
Tweet: I'm throwing myself straight into American Horror Story so I don't have time to grieve
Intensity score: | 0.483 |
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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: Tasers immobilize, if you taser someone why the fuck do you need to shoot them one second later?! This is really sick! #wtf #murder
This tweet contains emotions: | anger, disgust |
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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: @Gibberman10 @ScottHoward42 any of y'all remember when MLB tried a futuristic jersey those were all #terrible
Emotion: fear
Intensity score: | 0.375 |
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Task: Classify the tweet into one of four ordinal classes of intensity of emotion E that best represents the mental state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.
Tweet: If Monday had a face I would punch it #monday #horrible #face #punch #fight #joke #like #firstworldproblems #need #coffee #asap #follow
Emotion: fear
Intensity class: | 0: no fear can be inferred |
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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: oh these old things on my face? nah they're not tears from school related anger and frustration nope never
Emotion: anger
Intensity class: | 2: moderate amount of anger can be inferred |
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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: If I was friends with me I'd hate me SO MUCH with the amount I bully them
This tweet contains emotions: | anger, disgust, sadness |
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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 emotional state can be inferred. 2: moderately positive emotional state can be inferred. 1: slightly positive emotional state can be inferred. 0: neutral or mixed emotional state can be inferred. -1: slightly negative emotional state can be inferred. -2: moderately negative emotional state can be inferred. -3: very negative emotional state can be inferred.
Tweet: I'm just doing what u should b doing just minding my business and grinding relentless @LITO615
Intensity class: | -2: moderately negative emotional state can be inferred |
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Task: Determine the valence intensity of the tweeter's mental state on a scale of 0 (most negative) to 1 (most positive).
Tweet: @BreezyWeekes hey breezy, you wanna give me some of that coffee you posted on your snap?? please
Intensity score: | 0.574 |
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Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E).
Tweet: Your glee filled Normy dry humping of the most recent high profile celebrity break up is pathetic & all that is wrong with the world today.
Emotion: joy
Intensity score: | 0.100 |
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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 emotional state can be inferred. 2: moderately positive emotional state can be inferred. 1: slightly positive emotional state can be inferred. 0: neutral or mixed emotional state can be inferred. -1: slightly negative emotional state can be inferred. -2: moderately negative emotional state can be inferred. -3: very negative emotional state can be inferred.
Tweet: Happy Birthday, LOST! / #lost #dharmainitiative #12years #22september2004 #oceanic815
Intensity class: | 0: neutral or mixed emotional state can be inferred |
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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: #firsttweetever sippin #hotchocolate wondering #why I finally gave in <3 haha #hellloooootwitter - ...its because #facebookisforfamily #rage
Emotion: anger
Intensity score: | 0.542 |
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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: @StephenKing\n\nStephen King never once spoke out about how the Left crushes #FreeSpeech in publishing world.\n\n#Trump #horror #scifi #ccot #p2
Emotion: fear
Intensity class: | 0: no fear can be inferred |
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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: @pottermore : I can't find my patronus, the website doesn't work, I can't even see the questions.... #sadness...
Emotion: sadness
Intensity score: | 0.729 |
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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: @wrexham I've joined holidog, paw shake and tailster and have one regular customer I just love it 🙈🙈haha @EmilyHD26 @ellshd
Emotion: fear
Intensity score: | 0.208 |
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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: What if.... the Metro LRT went over the Walterdale?!?! 😂 #yeg #levity
Emotion: joy
Intensity class: | 1: low amount of joy can be inferred |
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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: @TheMandyMoore You are beyond wonderful. Your singing prowess is phenomenal but damn... I'm just elated to watch you act again. #ThisIsUs 🤗
Emotion: joy
Intensity score: | 0.771 |
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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: @lericoo 35. Do you hold a grudge against your ex?
This tweet contains emotions: | neutral or no emotion |
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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: Have the producers of @soverybritish ever been outside of their country? These are universal problems. #worldwide
Emotion: fear
Intensity class: | 0: no fear can be inferred |
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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: When you burst out crying alone and u realize that no one truly knows how unhappy you really are because you don't want anyone to know
Emotion: anger
Intensity class: | 1: low amount of anger can be inferred |
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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: @SueWallace78 peanut butter???? You some kinda pervert??
Emotion: fear
Intensity class: | 0: no fear can be inferred |
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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: #TerrorStatePak we r confirm that #navazsharif is post graduate distinction student of university of #terrorism. He can't spare himself.
This tweet contains emotions: | fear |