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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: Yay bmth canceled Melbourne show fanfuckingtastic just lost a days pay and hotel fees not happy atm #sad
Emotion: anger
Intensity score: | 0.562 |
|
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 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 mean i guess most of the mean ones are treated as like playful but i want to support yoosung without dating him ;___;
Intensity class: | 0: neutral or mixed emotional state can be inferred |
|
Task: Calculate the intensity of emotion E in the tweet as a decimal value ranging from 0 to 1, with 0 representing the lowest intensity and 1 representing the highest intensity.
Tweet: I was cheering for NA team. Now I just want this is over and Gaudreau comes back in one piece. It is getting way too risky
Emotion: joy
Intensity score: | 0.192 |
|
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: In ever use to like smiling until I realized how good my teeth look ... Witout the braces
This tweet contains emotions: | joy, 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: ESPN just assumed I wanted their free magazines #offended
Emotion: anger
Intensity class: | 2: moderate 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: Jesus wept! Another RNS from #rusty @metaltigerplc quote 'Price sensitive news, Price Sensitive news' etc etc The #Ramping here is
This tweet contains emotions: | anticipation, disgust, 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 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: @FilthyFrank My first time watching your vids and i died of laughter. Keep this up dude
Intensity class: | 3: very positive emotional state can be inferred |
|
Task: Calculate the intensity of emotion E in the tweet as a decimal value ranging from 0 to 1, with 0 representing the lowest intensity and 1 representing the highest intensity.
Tweet: Go one extra mile just see her smiling
Emotion: joy
Intensity score: | 0.640 |
|
Task: Measure the intensity of sentiment or valence in the tweet, assigning it a score between 0 (highly negative) and 1 (highly positive).
Tweet: Asked one thing from our guys tonight and got it! #happy #proud #disappointed - THAT IS FOOTBALL #timetoclimbthetable
Intensity score: | 0.607 |
|
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: @peacexxanna your nightmare
This tweet contains emotions: | anger, disgust, fear |
|
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: When will the weeks full of Mondays end?? #disheartened
This tweet contains emotions: | pessimism, sadness |
|
Task: Assign a numerical value between 0 (least E) and 1 (most E) to represent the intensity of emotion E expressed in the tweet.
Tweet: @JaySekulow what can we do 2 get @realDonaldTrump 2 reveal his taxes? That is the immediate danger. But u will not answer me. #afraid
Emotion: fear
Intensity score: | 0.667 |
|
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: I get soooo nervous when an actually attractive guy tries to talk to me in person. Like 9/10 I turn him down just from habit 😭
This tweet contains emotions: | fear, sadness |
|
Task: Evaluate the strength of emotion E in the tweet, providing a real-valued score from 0 to 1. A score of 0 denotes the absence of the emotion, while a score of 1 indicates the highest degree of intensity.
Tweet: Trying to take what's lost and broken and make it right
Emotion: sadness
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: @punjabified porkistan lost terribly in 65 because of american intervation to talk we stopped
Emotion: sadness
Intensity class: | 1: low amount of sadness 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: Hey no turn over after a kick - way to go Texans! Way to go! #Texans #noheart
Emotion: fear
Intensity class: | 0: no fear can be inferred |
|
Task: Assess the emotional content of the tweet and classify it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best represent the tweeter's mental state.
Tweet: Show your new job you're not #afraid of new tasks. Take on a #project, be brave, make an #impression. #WorkTiveTruth
This tweet contains emotions: | joy, optimism |
|
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: A @FirstBSA not turning up? Why am I not surprised. Late for work again!
Intensity score: | 0.391 |
|
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: PM nawaz sharif adressed in uno produced mirth among kashmires well done pak wel done nawaz .we want demilterization
Emotion: joy
Intensity class: | 1: low amount of joy 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: Yall rlly gotta stop lettin bees put fear in ur heart. unless ur allergic, I'm not tryna see u run around from a fuckin bee...chill. u soft.
Emotion: fear
Intensity class: | 0: no fear 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: ima kitchen sink
This tweet contains emotions: | disgust, pessimism, sadness |
|
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: In ever use to like smiling until I realized how good my teeth look ... Witout the braces
Emotion: joy
Intensity score: | 0.613 |
|
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: @LindaStein1 Me too,I really hope the writers decide to give us an return to McDanno we all love w/o resentment & animosity fingers crossed
This tweet contains emotions: | fear, 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: chirp chirp! what a beautiful white and red bird! 🐦
Emotion: joy
Intensity class: | 2: moderate amount of 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: #Pakistan is ‘terrorist state’, carries out #war crimes: #India to @UN.\n #UNGA #UN
Emotion: fear
Intensity score: | 0.667 |
|
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E).
Tweet: @essdotX the jovial and forgiving negro is always pressed upon to act against his/her self-interest in favor of the oppressor
Emotion: joy
Intensity score: | 0.090 |
|
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: @SurfaceSupport A profoundly disappointing experience. I have 2 pay almost $500 2 remedy a defect n the product @Microsoft sold me #terrible
Intensity score: | 0.161 |
|
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: @yungdoujin wouldn't that basically be sparkling water
Emotion: joy
Intensity score: | 0.320 |
|
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: Idk why people be glorifying depression. I wouldn't wish real depression upon my worst enemy. Shits the worst stop acting like it's cool
Emotion: sadness
Intensity score: | 0.828 |
|
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: @chelseahandler I don't think your a girls girl #fraud #bully #celebeffer
This tweet contains emotions: | anger, disgust |
|
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: The majority of my clients have family/ partner/ day job/ life AND write their beautiful books. #awe #gratitude #HARDwork
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: @MaddenFreestyle i turn the game on wanting to play madden, and before i load up a game i just turn it off now.
This tweet contains emotions: | neutral or no emotion |
|
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: How's it possible to go from cheery earlier to the worst mood possible now🙄
Emotion: joy
Intensity score: | 0.020 |
|
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: @KeithOlbermann depressing how despicable Trump, with no policies, campaigning on bigotry & rancour can be so close, evil immoral disaster
This tweet contains emotions: | anger, disgust, sadness |
|
Task: Calculate the intensity of emotion E in the tweet as a decimal value ranging from 0 to 1, with 0 representing the lowest intensity and 1 representing the highest intensity.
Tweet: @marthalyssa yep. LOL
Emotion: anger
Intensity score: | 0.438 |
|
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 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: In serious need of a nap
Intensity class: | -2: moderately negative emotional state can be inferred |
|
Task: Determine the prevailing emotional tone of the tweet, categorizing it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that most accurately represent the tweeter's mental state.
Tweet: Transitioning to a new job is hard when you have nothing but joyful memories of the previous one. Thanks @LifeTeen for changing my life! ❤️
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: People too weak to follow their own dreams will always find a way to discourage yours.
Emotion: sadness
Intensity class: | 2: moderate 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: Losing the will 2 live with @virginmedia business bb gone down on hold for 23 minutes & whoever picked up cut me off #NoWorkForMe
Emotion: anger
Intensity class: | 2: moderate amount of anger 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: the teams that face Barca and Bayern after a defeat are the ones who face the wrath
Emotion: anger
Intensity score: | 0.458 |
|
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: @SouthernRailUK delays from Streatham Cmn to Clap Junc & now train took 20 mins for 9 mins journey. Missed 2 trains to Reading
Emotion: anger
Intensity class: | 2: moderate amount of anger 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: @punjabified porkistan lost terribly in 65 because of american intervation to talk we stopped
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: As I remember and reflect on Reginald Denny on a night much like this (like #Charlotte) I think to myself, the gun lobby must be rejoicing.
Emotion: joy
Intensity score: | 0.422 |
|
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 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: Take my kindness for weakness when you acting silly keeping it 100 ain't your forté #ChrisBrown #TeamBreezy
Intensity class: | 0: neutral or mixed emotional state can be inferred |
|
Task: Assign the tweet to a specific ordinal class that corresponds to the tweeter's mental state, considering various levels of positive and negative sentiment intensity. 3: very positive 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: Light of day per heyday popularization backfire cinematography: XUcQb
Intensity class: | -1: slightly negative emotional state can be inferred |
|
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: Im so serious about putting words in my mouth bitch don't add ' the ' to my sentence if I didn't say that shit on bloods
Intensity class: | -3: very negative emotional state can be inferred |
|
Task: Assess the magnitude of emotion E in the tweet using a real number between 0 and 1, where 0 denotes the least intensity and 1 denotes the most intensity.
Tweet: From what I know of the man, I have to assume that @realDonaldTrump has had a heated argument with his own penis.
Emotion: sadness
Intensity score: | 0.354 |
|
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: Follow me on Snapchat 👻 Carlabtst15 #snapchat #snap
Emotion: anger
Intensity class: | 0: no anger 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: #NawazSharif says India poses unacceptable conditions to dialogue.#India's only condition is an end to #terrorism. :@MEAIndia
Emotion: fear
Intensity class: | 1: low amount of 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: @TelegraphNews why is this evil corrupt fuck still knocking about? The wrong people die I'm telling you. Do you job grim reaper!
This tweet contains emotions: | anger, disgust |
|
Task: Determine the prevailing emotional tone of the tweet, categorizing it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that most accurately represent the tweeter's mental state.
Tweet: Body is sleepy but the mind is active. So sad... Have to get ready for work in 30 minutes. Damn! #restless
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: @DevilsAdvcate @ManUtd absolutely boring.M a big Manchester United fan, nd its really disappointing to see them play in ths dull boring way
This tweet contains emotions: | anger, disgust, 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: @OstinOng YUUUHH 🙄😭 plus clin ep and prevmed ugghhh hahaha
Emotion: anger
Intensity class: | 1: low 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: @msdhoni #dhoni bcoz of is calmness nd match winning finishers nd a proud #miltirian #dad#husband nd wonderful humanbeing nd his #smile
Emotion: joy
Intensity class: | 2: moderate amount of joy 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: Just over a week until I start my new job in F1! Looking forward to it and cacking myself at the same time!
Emotion: fear
Intensity score: | 0.440 |
|
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: On the other side of fear lies freedom! - JB Glossinger #quote
This tweet contains emotions: | fear, joy, optimism, trust |
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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: carry on my wayward son there'll be peace when you are done lay your weary head to rest don't you cry no more
Emotion: sadness
Intensity score: | 0.500 |
|
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E).
Tweet: Val downing a bottle of vodka there to stop her from shaking! #GBBO
Emotion: fear
Intensity score: | 0.632 |
|
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: @TheRandomAnt @meg_m203 yeah, they figured that ornaments are way more wanted than spektar and desolate gear. Well they thought right.
This tweet contains emotions: | anticipation, optimism |
|
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: Bes! You don't just tell a true blooded hoopjunkie to switch a f*c@n' team that juz destroyed your own team. You juz don't! #insult
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: #ThankYouCGI - Do not grow weary in doing good. #CGI2016
This tweet contains emotions: | joy, optimism |
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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: testing
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: @twojacksdetail @bluelivesmtr Very rare an officer just shoots without regard. They don't want that on their conscience. #incite #inflame
Emotion: anger
Intensity class: | 3: high amount of anger can be inferred |
|
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E).
Tweet: Michelle, who did NOTHING is hating on Nicole's game hahaha.... #bitter #bb18
Emotion: anger
Intensity score: | 0.500 |
|
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: @ImNotInfected — rather someone that could help her. Concern clouded her green eyes, not once having seen a girl alone in the woods and —
Emotion: sadness
Intensity class: | 1: low 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: @CurtisJobling Yes indeed! We know masses of students would be so excited to see you! We need to get this sorted!
Emotion: fear
Intensity class: | 0: no fear 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: @jk_rowling never thought an angry oompa loompa would be my Boggart, but there you have it. #boggart #PresidentTrump
Emotion: fear
Intensity class: | 0: no 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: Dear future big brother players, just chase dick all season and you too can win 500,00 dollars and an Sti #bb18
Emotion: anger
Intensity class: | 0: no anger 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: Point scorning and fury at Labor does nothing to address long term detention and the need to resettle #asylumseekers from #manus and #Nauru
Emotion: anger
Intensity class: | 1: low 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: The ghost of Stefano reflects on the grim indignity of being murdered by corrupt cops in faux love. #days
Emotion: anger
Intensity score: | 0.521 |
|
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: If you #invest in my new #film I will stop asking you to invest in my new film. #concessions #crime #despair #shortsightedness #celebrities
Emotion: fear
Intensity class: | 0: no fear 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: When you're prof suggest @Pharrell and William James may be unlikely dialogue partners and then plays the #happy video #WeAreCST
This tweet contains emotions: | joy, optimism |
|
Task: Assess the sentiment intensity or valence level of the tweet, ranging from 0 (extremely negative) to 1 (extremely positive).
Tweet: ima kitchen sink
Intensity score: | 0.414 |
|
Task: Gauge the level of intensity for emotion E in the tweet, assigning it a score between 0 and 1. A score of 0 indicates the lowest intensity, while a score of 1 indicates the highest intensity.
Tweet: there are magpies gathering around me help I'm going to be swooped ! #terrorism
Emotion: fear
Intensity score: | 0.771 |
|
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: @CapehartJ agree! Those latest polls
This tweet contains emotions: | anticipation, optimism, trust |
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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: Forgot to plug the phone in overnight #nightmare
This tweet contains emotions: | disgust, fear, sadness |
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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: @SalterUK second pair of scales I have bought that have stopped working after battery change. Is this an issue you are aware of? #unhappy
This tweet contains emotions: | anger, pessimism, sadness |
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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: I'm honestly upset that they rewarded Nicole 500k. #depressing #paulwasrobbed #rewardhardwork #bitterjury #bb18
This tweet contains emotions: | anger, disgust, pessimism, sadness |
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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: @imtarakate Uggh that's really horrible. You're not a bad person by any stretch of the imagination. I hope this person realizes that.
Emotion: fear
Intensity class: | 0: no fear can be inferred |
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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: The Quarterback' wrecks me every time.. #glee
Intensity class: | -2: moderately negative emotional state can be inferred |
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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: @LethbridgeCity I love how playful you guys are becoming -- both on- and offline! 🚗 🚕 🚙 #beepbeep
Emotion: joy
Intensity score: | 0.673 |
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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: A shy failure is nobler than an immodest success.
This tweet contains emotions: | optimism |
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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: Don't join @BTCare they put the phone down on you, talk over you and are rude. Taking money out of my acc willynilly! #fuming
Emotion: anger
Intensity class: | 3: high amount of anger can be inferred |
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Task: Assess the sentiment intensity or valence level of the tweet, ranging from 0 (extremely negative) to 1 (extremely positive).
Tweet: There goes the butterflies in my stomach. #anxietyproblems
Intensity score: | 0.516 |
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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: @crumpledlinen he chirp
Emotion: joy
Intensity score: | 0.292 |
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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: . @UNFCCC @uncclearn The problem is the time it has taken to do this means its going to be out of date already. #sadly
Emotion: sadness
Intensity score: | 0.445 |
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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: Just because I'm hurting \nDoesn't mean I'm hurt \nDoesn't mean I didn't get \nWhat I deserved \nNo better and no worse #lost @coldplay
Emotion: sadness
Intensity class: | 2: moderate amount of sadness 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: #LMFAO @MSNBC 's #racepimp Tamron Hall used the words 'fscts' and 'MSNBC' in the same sentence #hilarity #libtard #biasedmedia #neverHillary
Emotion: joy
Intensity score: | 0.500 |
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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: Southend players always haunt Man U
This tweet contains emotions: | anger, disgust |
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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: @WilsonsWorld I was in high school and remember helping neighbors clean up back home in Greenville. Pretty sobering stuff. #sadness
This tweet contains emotions: | pessimism, sadness |
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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: Just watched Django Unchained, Other people may frown, but I titter in delight! 2/5
Emotion: joy
Intensity score: | 0.536 |
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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: The T.I / Shawty Lo beef is one of the more underrated ones in hip-hop history. Chock-full of wit, bravado and hilarity.
This tweet contains emotions: | joy |
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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: I truly feel like science has the ability to make a milk out of anything ... cashew milk, hemp milk, pine nut milk, dandelion milk
Emotion: sadness
Intensity score: | 0.271 |
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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: Friday is here, and we are open tonight and tomorrow. Get a jump on your Halloween and come play with us. #hauntedattraction #tulsa
Emotion: fear
Intensity score: | 0.337 |
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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: That feel when you travel 700 miles to pick up a form that arrives in the post two days after you leave.
Emotion: anger
Intensity class: | 1: low amount of anger 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: I just wanna know why there's no outrage for black on black crime and no one knows those victims but BLM is out to kill cops based on media
This tweet contains emotions: | anger, disgust, sadness |
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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: #GoodAfternoon! ^^ Doesn't matter whn you #start something, as long as you start it #today. 'Age' only exists in the mind. You are #Timeless
Emotion: fear
Intensity class: | 0: no fear can be inferred |
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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: NL's top bureaucrat is a director of a group formed to oppose NL's top megaproject. #nlpoli - never dull
Emotion: sadness
Intensity class: | 0: no sadness 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: Yo Yo Yo,my name is #DarthVader \nI feel like I need to puff on my inhaler (I'm no rapper but that was some sick bars) #breathless #bars #rap
This tweet contains emotions: | joy |
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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: Check out this #film Robocoq 301 #shortfilms
This tweet contains emotions: | anticipation, joy, optimism |