instruction
stringclasses 50
values | input
stringlengths 32
202
| output
stringlengths 0
55
|
|---|---|---|
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: we shiver in the pause between words \nabandonment still fresh upon the tips of our tongues
This tweet contains emotions:
|
optimism, pessimism
|
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: Moment of levity n Charlotte dude on rollerblades goes skating through protesters. Better if he was wearing short shorts & blowing a whistle
This tweet contains emotions:
|
joy, optimism
|
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: @SteveStratford9 @PaulTowheyJr @ClassicDrWho @BBC @bbcdoctorwho all those will get animated IMO. Companion changes/Monsters/Classics.
Emotion: joy
Intensity class:
|
0: no joy can be inferred
|
Task: Assess the emotional content of the tweet and classify it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best represent the tweeter's mental state.
|
Tweet: Ramos with his ground shaking headers..π
This tweet contains emotions:
| |
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 am more comfortable here at the Dove House than I was in my own home for 24 years. This is HOME & I am very grateful. #dove #indy #sober
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: How I Murdered Your Mother #SpookyTv #horror
Emotion: fear
Intensity score:
|
0.625
|
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: @VectoneMobileUK The worst customer service and lack of professionalism from this service provider! #phoneprovider #badbusiness
Emotion: fear
Intensity score:
|
0.458
|
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: #Terencecutcher #Tulsa the man onthe helicopter said he looks like a bad dude, that is the problem, when they see black they see bad,
Intensity score:
|
0.290
|
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: y'all shabazz's name in my phone is 'easy breezy beautiful' & I will not apologize.
Emotion: joy
Intensity score:
|
0.300
|
Task: Gauge the intensity of sentiment or valence in the tweet, indicating a numerical value between 0 (extremely negative) and 1 (extremely positive).
|
Tweet: My baskets are better when I'm in a bad mood someone irritate me before practice please
Intensity score:
|
0.313
|
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: mmmm i'm kinda sad i hope i can shake this before school
Emotion: fear
Intensity score:
|
0.616
|
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: Howling with laughter at βWELL DONE BEZZA!β #bakeoff #GBBO
Emotion: joy
Intensity class:
|
3: high 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: Today I answered a call from a college rep who didn't realize I did, and I got to hear part of his lively debate about if evolution is real.
Emotion: joy
Intensity score:
|
0.358
|
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: JV girls earn the W vs Stonington 2-1 today. Goals by K Waite and S Winakor. @DeluciaAlexis 1 assist. @mhseccathletics
This tweet contains emotions:
|
anticipation
|
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: GAMEDAY VS BUFORD TODAY AT 5:30 AT HOME!!!!!!!!! NEVER BEEN SO EXCITED
Emotion: anger
Intensity class:
|
0: no anger can be inferred
|
Task: Categorize the tweet based on the intensity of the specified emotion E, capturing the tweeter's mental state. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.
|
Tweet: @donna_bellav @SoniaRayS @gig_aholic He looks especially lovely. Sadly, I do not *removes potentially indignant Mr D from convo*
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: oh these old things on my face? nah they're not tears from school related anger and frustration nope never
Emotion: anger
Intensity score:
|
0.479
|
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: @RVAGameBreak @GAHSBasketball @GAJagsFootball \nGo Jags!!π I think we have a good shot of beating Deep Run tomorrow!
Emotion: anger
Intensity class:
|
0: no 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: #Awareness seek #shelter .#Letgo Old #habit of chasing #desires resultin in #anger #fear #worry .#Choose #Satisfaction within #Peace #Relax
Emotion: anger
Intensity score:
|
0.312
|
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: 2 applications for my dbs and still waiting. Been over a year now. Going to loose my job ππΏ @GOVUK #thanks #unhappy #crb
This tweet contains emotions:
|
anger, disgust, pessimism, sadness
|
Task: Gauge the intensity of sentiment or valence in the tweet, indicating a numerical value between 0 (extremely negative) and 1 (extremely positive).
|
Tweet: Too many gloomy days
Intensity score:
|
0.333
|
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 my comedic relief w/ @SofiaVergara during season premiere of #ModernFamily. Just what a girl needs! #hilarious
Emotion: joy
Intensity score:
|
0.846
|
Task: Place the tweet into a specific ordinal class, which captures the tweeter's mental state by considering different levels of positive and negative sentiment intensity. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred.
|
Tweet: If Troyler will die, I'm gonna die with them\n#troyler #sadness #fuckin'lifeisnotafairytale
Intensity class:
|
-3: very negative emotional state 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: Ok this movie was good in it's time, and whilst we were young... π Still enjoy a shy Ethan Hawk #BeforeSunrise
This tweet contains emotions:
|
joy, optimism
|
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: Val is far too cheery for my liking βπ»
This tweet contains emotions:
|
disgust, joy, pessimism
|
Task: Determine the appropriate intensity category of emotion E for the tweet, reflecting the emotional state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.
|
Tweet: I got a short fuse when im sober.
Emotion: sadness
Intensity class:
|
0: no sadness 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: @esanderc @MrsFridayNext It is very specific areas only. I care like 0% about clothes, much to my mother's dismay.
This tweet contains emotions:
|
disgust, sadness
|
Task: Classify the mental state of the tweeter based on the tweet, determining if it is 'neutral or no emotion' or characterized by any of the provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).
|
Tweet: Angelino's been horrific
This tweet contains emotions:
|
anger, disgust, fear, sadness
|
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: A presentations propensity for hilarity plays a large part in determining it's funny/offensive ratio and how well such thoughts will go over
This tweet contains emotions:
|
disgust, joy, surprise
|
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: @strangerpeace We'll have a ceremony next time we meet. It'll involve burning something, then possibly booze and/or caffeine.
This tweet contains emotions:
|
anticipation, joy
|
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: @LeeMorris7 I had no idea until I came off air directing at 7pm #shocking π
Emotion: fear
Intensity score:
|
0.479
|
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: If I could turn anxiety off--I would. #nooneunderstands #anxiety
Emotion: fear
Intensity score:
|
0.896
|
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: @kevinmenzel annual reminder that i don't care and will cheerfully eat anything so labeled
This tweet contains emotions:
| |
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: @scotydoesntkn0 start buying Death Wish Coffee and shake hands with espresso every now and then.
Emotion: fear
Intensity class:
|
0: no fear 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: You can't fight the elephants until you have wrestled the pigs. #quoteoftheday
This tweet contains emotions:
|
anticipation, 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: If I spend even 5 minutes with you and you already irritate me I seriously will bitch you out until you shut up
This tweet contains emotions:
|
anger, disgust
|
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: @corruptmelon now im feeling the
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: @RealMichaelKay Annoys me to about the Ortiz tribute too, how would the Oriole fans and organization feel if Yanks did that to them?
This tweet contains emotions:
|
anger
|
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: @MisterSalesman @ThinkPostsDaily #smiling doesnt necessary means your happy.sometimes it just means you're strong!
This tweet contains emotions:
|
joy, optimism, trust
|
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: I keep feeling the heaviness on my left hand and look down and I am in awe every single time ππ #notusedtoit #imafiancΓ©e #wut
Emotion: sadness
Intensity score:
|
0.208
|
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E).
|
Tweet: Absolutely shocking. The decline of Rooney is a little embarrassing really!
Emotion: fear
Intensity score:
|
0.542
|
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: @Markk1872 Red heads are more fiery.
This tweet contains emotions:
|
anger, fear
|
Task: Rate the intensity of emotion E in the tweet on a scale of 0 to 1, with 0 indicating the least intensity and 1 indicating the highest intensity.
|
Tweet: @StarklyDark 'Come here. Come on. Into my arms. I'm not going anywhere, Tony, I swear.' Steve told him, quiet and solemn.
Emotion: sadness
Intensity score:
|
0.500
|
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: @CesarSampao @thisisbolton don't get me started on town centre. Used to go every week.... not been for 18 months
This tweet contains emotions:
|
sadness
|
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 am their fury. I am their patience. I am a conversation. πβ€οΈβ¨
This tweet contains emotions:
|
anger, anticipation, love, sadness, trust
|
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: @yonahimes they never posted stuff like this?????\ni mean i was able to scroll over it so it wasnt a big deal but it was #shocking
This tweet contains emotions:
|
anger, disgust, fear, sadness, surprise
|
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: @alyssaxbeauty nightmare before Christmas
This tweet contains emotions:
|
anger, disgust, fear
|
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: Class is canceled due to a funeral. Not sure if it's appropriate to be happy or sad..
Emotion: joy
Intensity class:
|
1: low amount of joy can be inferred
|
Task: Categorize the tweet into an intensity level of the specified emotion E, representing the mental state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.
|
Tweet: Honestly don't give af who wins out of us and pine, I'm just worried about getting drunk Saturday nightπ
Emotion: sadness
Intensity class:
|
0: no 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: Love is when all your happiness and all your sadness and all your feelings are dependent on another person.
Emotion: sadness
Intensity score:
|
0.333
|
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: Hey @gmail why can I only see 15 sent emails? Where's the thousands gone? #panic
Intensity class:
|
-2: moderately negative emotional state 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: Recording some more #FNAF and had to FaceTime my mum to let her know I was okay after I let out a high pitched scream π #suchagirl
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: @marielleblaine8 @princesskeilani I told pine I didn't want it so I didn't have to have it
Emotion: sadness
Intensity score:
|
0.354
|
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: @rkuuleiq Fear is best/beast product of God/s. :) #aTheism #theism #biBle #christianity #hell #heaven #purgatory #psychology #jesus
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: @dublinwaltz bts' νμμ°ν trilogy MV is my all time favπ quite gloomy but beautiful as wellβ¨
Emotion: sadness
Intensity class:
|
0: no sadness 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: Root canal therapy has had a bad reputation in the past... but new technology has allowed more comfortable procedures! #smile #dental
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: @AuntieSupreme @KimberlyCarole y'all found me to express yalls displeasure. π
This tweet contains emotions:
|
anger, disgust, sadness
|
Task: Classify the tweet's emotional intensity into one of four ordinal levels of emotion E, providing insights into the mental state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.
|
Tweet: @BigBossPeltonen \nLikewise #death #cutting #despair
Emotion: fear
Intensity class:
|
3: high amount of fear 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: @megynkelly We should be ignoring these rioters like the current administration ignores #terrorism. This will obviously make it stop.
Intensity score:
|
0.417
|
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: @chutneysupercat hi lovely brownie, MM is calling me tuppytupperware.. its awful
Emotion: fear
Intensity score:
|
0.440
|
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: OOOOOOOOH MY GOD UUUUGGGGHHHHHHHHH
Emotion: anger
Intensity class:
|
3: high amount of anger can be inferred
|
Task: Categorize the tweet based on the intensity of the specified emotion E, capturing the tweeter's mental state. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.
|
Tweet: @mywrldsbl I can be your wolf if you want. Hihi~
Emotion: joy
Intensity class:
|
0: no joy 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 new lock sound is grim
Emotion: sadness
Intensity score:
|
0.562
|
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: @YahooFantasy update may have been the worst mistake of my day
This tweet contains emotions:
|
anger, pessimism, sadness
|
Task: Calculate the intensity of emotion E in the tweet as a decimal value ranging from 0 to 1, with 0 representing the lowest intensity and 1 representing the highest intensity.
|
Tweet: @wahrbear @marinarchy @diam0ndsapph1re There is some hilarity in someone who is literally openly anti-science calling others anti-science.
Emotion: joy
Intensity score:
|
0.385
|
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: I feel so blessed to work with the family that I nanny for β€οΈ nothing but love & appreciation, makes me smile.
Intensity class:
|
3: very positive emotional state 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: @christyfrink @stephenyeargin @El_Brandino I once hooked them up backward. Not recommended. #smoke #panic
This tweet contains emotions:
|
anger, disgust, fear, 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: semores: let's get this. #mirth #SAW #keepthetradition ππβπ΅πππΌπ€π₯ππππΎπ§
Emotion: joy
Intensity score:
|
0.560
|
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: whenever I put 'I wanna be adored' on my brother alwayss sings 'I wanna be a dog' instead just to irritate me
Emotion: anger
Intensity score:
|
0.415
|
Task: Rate the valence intensity of the tweeter's mental state expressed in the tweet, assigning it a score on a scale of 0 (most negative) to 1 (most positive).
|
Tweet: Come and join in with #cakeclubhour tomorrow afternoon from 3pm! #bizhour #chirp
Intensity score:
|
0.625
|
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: still shaking though π
Emotion: fear
Intensity class:
|
2: moderate amount of 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 people hit on me i try to shake them off by talking about how i hide from communism
This tweet contains emotions:
|
anger, disgust
|
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: everyone hates twice, and i kinda did too but they got bops i'm bumping rn to cheer up
Emotion: joy
Intensity class:
|
0: no joy 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: Wish I could convince the rest of my children to go to their fucking preschool and elementary schools with fear of gun violence.
Emotion: fear
Intensity score:
|
0.840
|
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: You forever straight so fix that frown u goodπ @amayyaaag__
Emotion: anger
Intensity class:
|
1: low amount of anger can be inferred
|
Task: Categorize the tweet based on the intensity of the specified emotion E, capturing the tweeter's mental state. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.
|
Tweet: eun: im really unhappy with this and i dont like her like that pls dont\n\nyall: okay but SHE loves HIM
Emotion: sadness
Intensity class:
|
2: moderate amount of sadness can be inferred
|
Task: Analyze the tweet's emotional connotations and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best portray the tweeter's mental state.
|
Tweet: @DatelineNBC this is a sight, sound & smell to behold in person--still gives me the creeps to think about.
This tweet contains emotions:
|
fear, pessimism
|
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: @snowangel415 @cjwalters66 Maybe also being attacked by Tom's rabid fans to whom he & his clothes were always perfect also put me off him...
Emotion: anger
Intensity score:
|
0.646
|
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 really want to read this fic i found but it's #serious and this room is full of #memes
Emotion: sadness
Intensity class:
|
0: no 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: Hey @gmail why can I only see 15 sent emails? Where's the thousands gone?
Emotion: fear
Intensity class:
|
0: no fear 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: Quinn's short hair makes me sad.
Emotion: joy
Intensity class:
|
0: no 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: Starting to get butterflies in our tummies about tomorrow...who will win?! #nervous @IPMCOGSAwards
This tweet contains emotions:
|
fear, pessimism
|
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: @DFSCare apparently you are to contact me. Sofas were meant to be delivered today. Old ones gone. Sitting on floor. No sofas!
Emotion: anger
Intensity class:
|
2: moderate amount of anger can be inferred
|
Task: Categorize the tweet based on the intensity of the specified emotion E, capturing the tweeter's mental state. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.
|
Tweet: I'm about to block everyone everywhere posting about the storm. I think everyone is aware of the damn rain and what not so quit. #damn
Emotion: anger
Intensity class:
|
3: high amount of anger can be inferred
|
Task: Determine the most suitable ordinal classification for the tweet, capturing the emotional state of the tweeter through a range of positive and negative sentiment intensity levels. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred.
|
Tweet: ..... wakes up and says 'have you tried changing her nappy?' π‘ππΌ !!!!
Intensity class:
|
-2: moderately negative emotional state 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: @DDNewsHindi #UNGA no talks should be carried out with Pakistan now ... His mouth stinks of #terrorism #UriAttack
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: What u do wen ur love cheats on u ? Wen thy don't understand the emotions behind the anger, the constant waiting.. what u do ? @ritujai18874
This tweet contains emotions:
|
anger, disgust, fear, 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: @DouthatNYT @jbouie @DamonLinker Yes, it is bad to point out racism lest it provoke the racists. Some racists do indeed not like it.
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: @cc_yandian @HillaryClinton her team must draw from a hat for daily personality #drugged #yeller #quiet #screamer #ππ
Emotion: anger
Intensity class:
|
2: moderate amount of anger 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: Wow what a thought! #JudgeLynnToler 'I can't have the specter of this morning's problem haunt my afternoon.' Well written! That 1 sentence
Emotion: fear
Intensity class:
|
0: no fear can be inferred
|
Task: Assess the sentiment intensity or valence level of the tweet, ranging from 0 (extremely negative) to 1 (extremely positive).
|
Tweet: Liam is too distant makes me mourn πͺ
Intensity score:
|
0.240
|
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: Joes gf started singing all star and then Joe got angry and was all sing it right and started angrily singing it back at her
Emotion: anger
Intensity 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: @enews #breezy deserve it..
Emotion: joy
Intensity class:
|
1: low amount of joy 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: @GreatFallVoyagr #bitter sums it up! Congrats Nicole! that's all folks #bb18 now onto #survivor !
Emotion: anger
Intensity score:
|
0.354
|
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: @Max_Kellerman it also helps that the majority of NFL coaching is inept. Some of Bill O'Brien's play calling was wow, ! #GOPATS
This tweet contains emotions:
|
anger, disgust, joy, 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: LGBTQ media should inform, inspire, entertain &unite our community. It shouldn't give platform 2 those whose goal is 2 offend us 4 attention
This tweet contains emotions:
|
anger, disgust, joy
|
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: @RonMexico760 The guy who calls people 'cuck' and is anti-BLM is offended by idea that he might not be pro-policing reform? That's amazing.
Emotion: anger
Intensity score:
|
0.625
|
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 best revenge is massive success. βFrank Sinatra
Emotion: anger
Intensity score:
|
0.375
|
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: Job interview tomorrow π #bright side
Emotion: joy
Intensity score:
|
0.640
|
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: Feeling like I've had the worst night of sleep ever - not great before the #London to #Brighton #cycle ride for @DMTFYP π΄100k #apprehension?
This tweet contains emotions:
|
anger, disgust, fear, pessimism, sadness
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.