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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: @GreatFallVoyagr #bitter sums it up! Congrats Nicole! that's all folks #bb18 now onto #survivor !
This tweet contains emotions: | joy, optimism |
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: Wishing i was rich so i didnt have to get up this morning #poor #sleepy #sad #needsmoresleep
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: Afraid of no one an no one scares me!!! Funk y'all thought image one mans army!! '!
This tweet contains emotions: | anger, disgust |
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 don't think Luca understands how serious I am about Fall....he has no idea what's in store for him ππ
This tweet contains emotions: | joy |
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: @rockandpop pomte A Muse com panic Station Exitaso
Emotion: fear
Intensity score: | 0.370 |
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: @JuliaHB1 Bloody right #fume
Emotion: anger
Intensity score: | 0.500 |
Task: Analyze the tweet's sentiment and assign it to either 'neutral or no emotion' or one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust). | Tweet: And 9/10 the character is a woman. Because if a man is fat he's jovial. If a woman is fat she's useless and maybe evil amirite?
This tweet contains emotions: | anger, disgust |
Task: 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: Fucking hell. Rush for the damn train also no use. Fucking 4min wait. Still sweating. #smrtruinslives
Emotion: anger
Intensity score: | 0.771 |
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: Hell hath no fury like a late twenty something dude who's concur for government session keeps expiring before he can submit a form
Emotion: anger
Intensity score: | 0.479 |
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: #EFT is the single most effective tool I've learned in 40 years of being a therapist-Dr. Curtis A. Steele (psychiatrist) #stress
Emotion: fear
Intensity class: | 0: no fear can be inferred |
Task: Assign a numerical value between 0 (least E) and 1 (most E) to represent the intensity of emotion E expressed in the tweet. | Tweet: PM #SheikhHasina in @UN speech terms #terrorism as global challenge and urges world leaders to work together to unroot it from everywhere.
Emotion: fear
Intensity score: | 0.554 |
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: a #monster is only a #monster if you view him through
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: Had to delete my Facebook too much for me π€£
Emotion: joy
Intensity score: | 0.094 |
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: @m_t_f_72 I'm not surprised, I would be fuming! π€
Emotion: anger
Intensity class: | 2: moderate amount of anger can be inferred |
Task: Determine the appropriate intensity class for the tweet, reflecting the level of emotion E experienced by the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: I don't know what's worse, the new Pizza Hut commercials or the pizza that Pizza Hut makes.
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: It's now September and we're still battling a situation that was said to be handled March of this year. @ATT this is unacceptable #unhappy
Emotion: sadness
Intensity class: | 3: high amount of sadness 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: @andyfleming83 Bastard squirrels. π‘
Emotion: fear
Intensity score: | 0.500 |
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: Back in the big time after selection last night. Absolutely buzzing. Bring on the roaches #SG16 #kickittomehigh #nswgaa #blues #statevstate
Emotion: sadness
Intensity class: | 0: no sadness can be inferred |
Task: Classify the tweet into one of four ordinal intensity levels, indicating the degree of emotion E experienced by the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: 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: 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: Forgot to thank @_JusDee_ and @djolder for sharing @therealpeela's day-making #happy video.
Emotion: joy
Intensity class: | 2: moderate amount of joy 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: If Payet goes either in Jan or @ the seasons end, can't say I blame him. The boy must b so disheartened by what he's seeing at the mo.
Emotion: sadness
Intensity class: | 2: moderate amount of sadness 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: You have to learn how to live life regardless of circumstances & not let life leave you. \n#purpose #Growth #process #confident #happy #joy
Emotion: joy
Intensity class: | 1: low amount of joy can be inferred |
Task: Assess the emotional content of the tweet and classify it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best represent the tweeter's mental state. | Tweet: My dog wouldn't stop barking so now I'm up at eight am with a raging headache
This tweet contains emotions: | anger, disgust, sadness |
Task: Categorize the tweet into one of seven ordinal classes, representing different degrees of positive and negative sentiment intensity, that most accurately reflects the emotional state of the Twitter user. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred. | Tweet: #RIP30 Heaven is rejoicing because they've gained an angel, the Keifer family are in my prayers ππ
Intensity class: | 0: neutral or mixed emotional state 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: @leesyatt you are a cruel, cruel man. #therewillbeblood
Emotion: anger
Intensity class: | 3: high amount of anger 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: @RussellHartness @Mariners @BlueJays : Wrongdoing! Grrr. After the fact, I know, but emailing displeasure now anyway .
This tweet contains emotions: | anger, disgust, sadness |
Task: Categorize the tweet's emotional expression, classifying it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that reflect the tweeter's state of mind. | Tweet: @evanareteos :)) im now writing abt the changing face of sex industry in tr :))) now men will talk to me then!
This tweet contains emotions: | anger, joy, optimism |
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: @interception225 you're looking for an argument that i'm not engaging in. He's not even speaking his own words, i'm not raging at him.
Emotion: anger
Intensity class: | 1: low 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: Ronaldo has been shocking. He's tried to do skill twice and he's nearly fallen over both times
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: -c- and disarmed of her equipment on suspicion of being a potential accomplice to Annie Leonhart.
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: Watch this amazing live.ly broadcast by @hannah..mccloud #musically
Emotion: joy
Intensity score: | 0.500 |
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: @MUTGuru I know guys that sink $1000s into the game and only to build a team and play solos. But this hear you make nothing on solos.
Emotion: sadness
Intensity class: | 0: no sadness can be inferred |
Task: Classify the tweet into one of four ordinal intensity levels, indicating the degree of emotion E experienced by the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: Thank you @RachelPlatten for teaching me how to live again. It's been so long since & this ride is about to be exhilarating. I just know it
Emotion: joy
Intensity class: | 3: high amount of joy 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: @jamiesmart Huh! It's always my fault isn't it >:( #sulk
Intensity score: | 0.250 |
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: It breaks my heart seeing people down or upset.. I will try my best to make them smile or cheer them up π€
Intensity class: | 0: neutral or mixed 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: @XboxMAD @RobotBrush Ballmer will be furious. Another delivery lost...
Emotion: anger
Intensity class: | 2: moderate amount of anger 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: #PeaceIsPossible when both party accept one another and rejoice together after #OndoGuber,Nov26. @JciOndokingdom @cuttie_dove @Lekibeat
Emotion: joy
Intensity class: | 1: low amount of joy can be inferred |
Task: 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: @laura221b I don't think I've ever moved so fast in a panic in all my life π Gave me such a fright π
This tweet contains emotions: | fear |
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E). | Tweet: @EliTheProphet_ @ChrisMellini this is an automatic L for me but ima keep trying fam #relentless #thewengerway
Emotion: anger
Intensity score: | 0.267 |
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: @PanicAtTheDisco hey, y'all announced it like immediately after I asked. Nice. Thanks y'all
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: After she threw me out I had to sedate her. With a damn horse tranquilizer.'
Emotion: sadness
Intensity score: | 0.354 |
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: @VivYau is it all doom and gloom? I only want to hear lovely things about airbnb!
This tweet contains emotions: | anticipation, joy, sadness |
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: We're all in D. T. (Discipleship training or detox) for something. #messy #fearful #cutoff #choosefreedom #CryOut16
Emotion: fear
Intensity class: | 1: low amount of fear can be inferred |
Task: Assign a numerical value between 0 (least E) and 1 (most E) to represent the intensity of emotion E expressed in the tweet. | Tweet: @brian5or6 turn that shit off! Home Button under Accessibility. \n\nWhen did innovation become mind fuckery? #rage. #iphonePhoneHome
Emotion: anger
Intensity score: | 0.667 |
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: This night, room polluted with syringes, notebooks and shadows moving, this kind of night! Away melancholy, away!
Emotion: sadness
Intensity score: | 0.633 |
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: The terror threat level really need to be raised
This tweet contains emotions: | fear, pessimism |
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: @rclemmons much #sadness and #heartbreak
Emotion: sadness
Intensity class: | 3: high amount of sadness 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: Absolutely hate the Apple Watch iOS 10 update. Completely buggered some of my apps, including Spark. Awful interface, too. #grim
Emotion: sadness
Intensity class: | 2: moderate amount of sadness can be inferred |
Task: Classify the tweet into one of seven ordinal categories, indicating the intensity of positive or negative sentiment expressed by the tweeter and reflecting their current mental state. 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: Mate the thing I get excited about in my profession are mad. A client said she opened her bowels, I'm rejoicing
Intensity class: | 2: moderately positive emotional state 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: @readanerd cheer up chuckπ
Emotion: joy
Intensity score: | 0.240 |
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: The voice is all about Miley and Alicia this year. No longer about the contestants. #sad @thevoice
Emotion: sadness
Intensity score: | 0.604 |
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: @DJ_Musicologist #Disney's 1994 #animated #musical #film #TheLionKing was influenced by #WilliamShakespeare's #Hamlet. Songs by #EltonJohn.
Emotion: joy
Intensity class: | 1: low 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: @deadlyjokester *she let out a playful gasp and slowly wrapped her arms around his neck, kissing him back*
Emotion: joy
Intensity score: | 0.620 |
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 wonder if the #wolfcreek TV show is sponsored by the anti-tourist board of Australia to discourage visitors? #stayathome #dontvisit
Emotion: sadness
Intensity class: | 0: no sadness can be inferred |
Task: Calculate the intensity of emotion E in the tweet as a decimal value ranging from 0 to 1, with 0 representing the lowest intensity and 1 representing the highest intensity. | Tweet: @thomeagle Just to help maintain and boost our status as a world class centre for education, culture and tolerance.
Emotion: anger
Intensity score: | 0.167 |
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: the teams that face Barca and Bayern after a defeat are the ones who face the wrath
This tweet contains emotions: | anger, disgust |
Task: Categorize the tweet into one of seven ordinal classes, representing different degrees of positive and negative sentiment intensity, that most accurately reflects the emotional state of the Twitter user. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred. | Tweet: @el_tityboi bc it's a gloomy day Tony
Intensity class: | -3: very negative emotional state 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: I wish EVERYONE could see how #MSNBC #CNN talked over trumps speech. You ALL should be ashamed of the along with the sheep followers.
Emotion: anger
Intensity score: | 0.516 |
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E). | Tweet: @priny_baby happppy happppyyyyyy happppppyyyyy haaapppyyyy birthday best friend!! Love you lots πππππππππ #chapter22 #bdaygirl #love
Emotion: joy
Intensity score: | 0.958 |
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: Was a huge fan of @Ryanair but last few flights have been horrific. #rude #poorservice #nostock etc etc etc #dissapointed
Emotion: sadness
Intensity class: | 3: high amount of sadness 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: Woke up feeling fresh with a clear mind. That's never happened before.\n#morning #sober
Emotion: anger
Intensity score: | 0.156 |
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: Someone wake me when @Therealkiss make 2016 remix of 'Why'βοΈb/w #TerrenceCrutcher #Election2016 #colinkapernick #terrorism #riots this 2much
Emotion: fear
Intensity class: | 2: moderate amount of fear can be inferred |
Task: Categorize the tweet into an intensity level of the specified emotion E, representing the mental state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: @everton_de_leon @sterushton Genuinely grim stuff. Over a century of history sold off by some porn baron twats for a minty new stadium. Urgh
Emotion: sadness
Intensity class: | 2: moderate amount of sadness 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: First a coat. Now a pair of sunglasses. Next it'll be a limb. #lost
Emotion: sadness
Intensity class: | 2: moderate amount of sadness can be inferred |
Task: Classify the tweet into one of four ordinal intensity levels, indicating the degree of emotion E experienced by the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: Marcus Roho is dreadful
Emotion: sadness
Intensity class: | 1: low amount of sadness 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: @PerfectQuartz She's jogging a bit to stay beside her, puffing her cheeks with a huff each time. 'Oh-- jeez Jasper, why don't you β
Emotion: anger
Intensity score: | 0.375 |
Task: Categorize the tweet into an ordinal class that best characterizes the tweeter's mental state, considering various degrees of positive and negative sentiment intensity. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred. | Tweet: @del_krushnic I knw you have a temper paaa lol just chill dear don't be pissed waii or I will else worry u saaa but I'm sorry π«
Intensity class: | -2: moderately negative emotional state can be inferred |
Task: Determine the dominant emotion in the tweet and classify it as either 'neutral or no emotion' or one of the eleven provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust). | Tweet: Afraid of no one an no one scares me!!! Funk y'all thought image one mans army!! '!
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: @esraalajmy huff btw tyπ
Emotion: anger
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: Prayers & Protection to our brothers and sisters fighting in #Charlotte #against #machines
Emotion: anger
Intensity score: | 0.189 |
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: @KermodeMovie I shall be mooning him cheerfully when he arrives. Although he probably won't be president by then...
Intensity class: | 0: neutral or mixed emotional state can be inferred |
Task: Evaluate the valence intensity of the tweeter's mental state based on the tweet, assigning it a real-valued score from 0 (most negative) to 1 (most positive). | Tweet: @realDonaldTrump Way to unite the country - such a presidental tweet #sarcasm
Intensity score: | 0.500 |
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: @_MariaPetrova should have stopped after 'smiled'. Being rude=not the same as being funny.It was just being mean #bully #stoppickingonwomen
Emotion: fear
Intensity class: | 2: moderate amount of fear can be inferred |
Task: Evaluate the strength of emotion E in the tweet, providing a real-valued score from 0 to 1. A score of 0 denotes the absence of the emotion, while a score of 1 indicates the highest degree of intensity. | Tweet: Your boy' is having a nightmare @VivaLaSergio
Emotion: fear
Intensity score: | 0.646 |
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: @Will_0004 No justification for shooting without provocation, even if the person has a bad history. Justification is not the way to go
This tweet contains emotions: | anger, disgust, sadness |
Task: Determine the valence intensity of the tweeter's mental state on a scale of 0 (most negative) to 1 (most positive). | Tweet: Headed to Montalvo w/@jaxster3βbring on the #mirth, bitches!\nd(-_-)b\n@Nick_Offerman\n@MeganOMullally\n#SummerOf69Tour2016
Intensity score: | 0.537 |
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: Hey folks sorry if anything offensive got posted on here yesterday my account got hacked. All fixed now though. I hope :-/ #annoyed
This tweet contains emotions: | anger, disgust, fear, sadness |
Task: Classify the tweet into one of four ordinal classes of intensity of emotion E that best represents the mental state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: Sometimes I get mad over something so minuscule I try to ruin somebodies life not like lose your job like get you into federal prison #anger
Emotion: anger
Intensity class: | 3: high 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: Jorge deserves it, honestly. He's weak. #revolting #90dayfiance
Emotion: fear
Intensity score: | 0.229 |
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: IΒve learnt that a #smile and good #morning goes a long way, and saying #thankyou goes even further. #quote #retweet #inspire
Emotion: joy
Intensity class: | 2: moderate amount of 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: The most important thing to #bestrong is to hold your #anger #thoughts
This tweet contains emotions: | anger, disgust, optimism |
Task: Rate the intensity of emotion E in the tweet on a scale of 0 to 1, with 0 indicating the least intensity and 1 indicating the highest intensity. | Tweet: So disappointed in myself for spending Β£50 on an outfit for meeting a boy #noselfcontrol #nervous
Emotion: anger
Intensity score: | 0.682 |
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: @macmacm43 jeezus God #dark
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: @EmmaHobbs1 I did that! 3 days later my order isn't even in the same postcode as me #fuming
Emotion: anger
Intensity score: | 0.667 |
Task: Gauge the intensity of sentiment or valence in the tweet, indicating a numerical value between 0 (extremely negative) and 1 (extremely positive). | Tweet: It hasn't sunk in that I'm meeting the twins
Intensity score: | 0.452 |
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: Hell hath no fury like a late twenty something dude who's concur for government session keeps expiring before he can submit a form
Emotion: anger
Intensity class: | 2: moderate amount of anger can be inferred |
Task: Measure the intensity of sentiment or valence in the tweet, assigning it a score between 0 (highly negative) and 1 (highly positive). | Tweet: Grateful for all the hungry people in my life! Hungry to learn, change, grow, help, etc - not sure anybody has it better! #relentless
Intensity score: | 0.878 |
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E). | Tweet: Will do fine on the mat tonight with or without sleep. theres no worry for that on this side of the water
Emotion: fear
Intensity score: | 0.372 |
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: #RIPBiwott I think Robert oukos soul can now rejoice and rest in peace. Call an evil man evil and a good man a good man. He was an evil man
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: @Ragga_Storm #red is #dread love it
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: @ChronAVT ummm, the blog says 'with Simon Stehr faking 7th'...I'll expect an investigation forthwith. This is an
Emotion: anger
Intensity score: | 0.479 |
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: @emmajckson awe thank you (,:
Emotion: anger
Intensity score: | 0.076 |
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: @Apple thanks for ios10 update, even the best app @telegram freezing and crashing on SE. #angry
Emotion: anger
Intensity score: | 0.845 |
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: @MHChat #mhchat Childhood experiences inform adult relationships. We have associative memories Not a question of ability to process #sadness
This tweet contains emotions: | pessimism, sadness |
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: The Sorrow is grim reminder of how bad I can be at video games and how I could get a bit too trigger happy at times. RIP #MGS3
This tweet contains emotions: | sadness |
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: That grudge you're holding keeps making an appearance because #God wants you to deal with it.
Emotion: anger
Intensity class: | 2: moderate amount of anger 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: luv seeing a man with a scowl on his face walking with a protein shaker clenching his fists. i immediately stop n suck his dick
Emotion: anger
Intensity score: | 0.562 |
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: @amjadhussain73 @MehreenFaruqi Don't waste your time on that Muslim crap. Ups you are Arab too. π π π Greatings fro Pauline Hanson. π π π
This tweet contains emotions: | anger, disgust, joy |
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: Hey NASCAR fans. Are you going to the race in Loudon this weekend? Why not stop by New Day Diner for a great hearty breakfast before you go
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: God this match is dull #Wimbledon
This tweet contains emotions: | disgust, sadness |