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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: @jpodhoretz I still respect you. I suppose there is so little to be gleeful about these days so take what you can. Good for you.
Emotion: joy
Intensity score:
|
0.417
|
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: @luxbet Did you even give out any pizzas ? Serious fail #hungry #furious #hangry
Emotion: anger
Intensity score:
|
0.447
|
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: Watch this amazing live.ly broadcast by @its.finfin #musically
Emotion: joy
Intensity score:
|
0.458
|
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: @HannahFJames I'm distraught! 😭 Candice and her pout can piss off
Emotion: sadness
Intensity class:
|
3: high amount of sadness 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: @ggreenwald @SusanSarandon We are blaming 5% of the fucking idiots who are putting the World in the middle of their tantrums. You are one.
Emotion: anger
Intensity score:
|
0.792
|
Task: Assign the tweet to one of seven ordinal classes, each representing a distinct level of positive or negative sentiment intensity, reflecting the mental state of the tweeter. 3: very positive 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: This weather got me fucked up. Like you either be sunny and hot or gloomy and cold. No in between.
Intensity class:
|
-3: very 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: @Iucifaer you can go on what you usually do its just their own personal reason and not mean to offend anyone :(
This tweet contains emotions:
|
optimism, sadness
|
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: my wasp sting is so itchy
Emotion: anger
Intensity score:
|
0.356
|
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: now im all alone and my joy's turned to moping
Emotion: sadness
Intensity score:
|
0.729
|
Task: Classify the tweet's emotional intensity into one of four ordinal levels of emotion E, providing insights into the mental state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.
|
Tweet: I delete numbers so quick with no hesitation
Emotion: fear
Intensity class:
|
0: no fear can be inferred
|
Task: Determine the appropriate intensity category of emotion E for the tweet, reflecting the emotional state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.
|
Tweet: Said it before and I'll say it now: America is really fortunate that black people only want equality and not revenge.
Emotion: anger
Intensity class:
|
2: moderate 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: @LouisFil just curious as to what you mean. No rush, no animosity, no disdain.
Emotion: anger
Intensity score:
|
0.458
|
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: @coltonflurry @StrangeFacesLA I cancelled by CBS all access live feeds before JC even said Vic won AFP. Paul.should have won IMO #bitter
Emotion: anger
Intensity score:
|
0.517
|
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: Modern family never fails to cheer me up. Especially Phil.
Emotion: joy
Intensity class:
|
3: high amount of joy can be inferred
|
Task: Classify the tweet into one of seven ordinal classes, corresponding to various levels of positive and negative sentiment intensity, that best represents the mental state of the tweeter. 3: very positive 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: A delight to be at the Lane tonight and witness the debuts of some young talent that could be the backbone of our club!! #COYS
Intensity class:
|
3: very positive emotional state can be inferred
|
Task: Classify the tweet's emotional intensity into one of four ordinal levels of emotion E, providing insights into the mental state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.
|
Tweet: her; i want a playful relationship\nme; *kicks her off the couch*
Emotion: joy
Intensity class:
|
0: no 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: My nephew sees that i have a frown on my face and he tells me 'you're beautiful '!😢💞😩
Emotion: anger
Intensity score:
|
0.229
|
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: Just like there is a right way to pray, there is a right way to give - not grudgingly or of necessity, but cheerfully. #woficc
Emotion: joy
Intensity score:
|
0.440
|
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: It's easy to #fall #asleep in class, but hard to in bed. #True #whileyouweresleeping #insomnia #TeamFollowBack #RockTheReTweet
This tweet contains emotions:
|
disgust, pessimism
|
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: @paulkrugman relentless echo chamber - negative comments with lots of reverb. Typical bully behavior.
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: @CohenDS Yell, 'Bye, garbage!' cheerfully after it.
Emotion: joy
Intensity score:
|
0.360
|
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: @siomo @NEWSTALK1010 20 says he gets reelected..... #be #afraid
Emotion: fear
Intensity class:
|
0: no fear can be inferred
|
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: As the birds chirp and the cows moo we need to listen to the sound of nature to ensure that all is well.
Intensity score:
|
0.581
|
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: Heard of panic! At the disco? How about Kach-ing! at the ATM
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: #happiness #recipe: an open mind, #laughter, a kind #heart &
Emotion: joy
Intensity class:
|
2: moderate 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: Crossfit houston-la homefolks as for spry proprieties regimes: AJaFUE
Emotion: joy
Intensity score:
|
0.271
|
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: Well @AprilDRyan Trump's rabid base needs 2 hear this & U can always find an overseer like King to say it.\n@JoyAnnReid @SMShow @frangeladuo
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: @keithboykin unfortunately it won't end there... followers of whichever candidate isn't elected will throw tantrums. No winning this elec
Emotion: anger
Intensity class:
|
2: moderate 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: Praying for the #Lord to keep #anger #hate #jealousy away from your heart is a sign of #maturity #conciseness
Emotion: anger
Intensity score:
|
0.354
|
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: not going to waste my energy holding a grudge against someone who wasnt even in my life a year XD \ntime to release those feelings of dislike
This tweet contains emotions:
|
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: kenny - where were you born\nme - washington\nkenny - you fucking liar you were born in the fiery pits of hell
Emotion: anger
Intensity score:
|
0.917
|
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: My boss likes to stand in my office & smile at me like a shark: maliciously gleeful, and ask me how am I as if I have a secret to tell her.
Emotion: joy
Intensity score:
|
0.396
|
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: @delta correction 26 ppl. Checked in. Standing at the gate. & Flt 1449 took off without us. #furious
Emotion: anger
Intensity class:
|
3: high amount of anger 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: 340:892 All with weary task fordone.\nNow the wasted brands do glow,\nWhilst the scritch-owl, scritching loud,\n#AMNDBots
This tweet contains emotions:
|
anger, disgust
|
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: Been working in Blanchardstown shopping centre for over 2 years now and I only figured out today where Marks & Spencer's is
Emotion: sadness
Intensity score:
|
0.292
|
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: Usually I'm not one to rush colder weather but this year I'm so ready for hot coffee, dark lippies, scarves, sweaters, & boots 🍂👢☕️💄
This tweet contains emotions:
|
joy, 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: I like the commercial where @kohara19, on a chocolate milk bender, steals a soccer ball from some guys and refuses to give it back.
Emotion: fear
Intensity score:
|
0.188
|
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: I was having a good dream.. and then my alarm went off
Emotion: fear
Intensity class:
|
0: no fear can be inferred
|
Task: Determine the appropriate intensity category of emotion E for the tweet, reflecting the emotional state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.
|
Tweet: pray for my boy huff
Emotion: anger
Intensity class:
|
0: no anger 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: 💥⚖️Yeah‼️ PAUL‼️⚖️💥 #joyous #glorious #BB18
Emotion: joy
Intensity class:
|
3: high amount of joy 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: @TehShockwave turn that grumpy frown upside-down\n\nYou did something next to impossible today
This tweet contains emotions:
|
sadness, surprise
|
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: #WTF @NYSCHereToHelp @NYSC allows #gym #bully #atmosphere! #jumpship #nasty #atmosphere #unprofessional
This tweet contains emotions:
|
anger, disgust, 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: @BitchestheCat Look at those teef!
Emotion: anger
Intensity class:
|
1: low 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: @sundersays made me laugh, that quote. In a sort of rueful way.
Emotion: sadness
Intensity score:
|
0.375
|
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: @JUSTICESLUT420 sadly this sort of poster died by the 90s afaik
Intensity class:
|
-2: moderately negative emotional state can be inferred
|
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: Try to find the good in the negative. The negative can turn out to be good.\n#anxietyrelief #optimism #openminded
Intensity class:
|
1: slightly positive emotional state 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: backed pats -2.5 10/11 just before
Emotion: joy
Intensity class:
|
0: no joy 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: streets of rage 2 was hard to find for a while and then Itunes stepped in and the guys doing the vinyl \nmade it so simple
Emotion: anger
Intensity score:
|
0.458
|
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: 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: Turns out 'it' wasn't even anything to be concerned about at all. Im happy and a bit frustrated it took so long to get this answer.
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: I'm so proud he understands this, he shows love, thought and compassion and it's not done in a clouded way..
Emotion: sadness
Intensity score:
|
0.188
|
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: I think it's time to change my #irate motif, now that #TalkLikeAPirate Day is over, but...Pirate Minion is so cute, I don't want to. 😟
Emotion: anger
Intensity score:
|
0.417
|
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: This maybe a new start but it will always be align with the end. #forward
This tweet contains emotions:
|
anticipation, joy, optimism
|
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: @Bungie spent over 2 fucking hours and still can't get that dam SIVA fragment on Fellwinters peak mountain
Emotion: anger
Intensity class:
|
3: high 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: Wish I was a kid again. The only stressful part was whether Gabriella and Troy would get back together or not. #hsm2 #nightmare
Emotion: fear
Intensity class:
|
0: no fear 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: @MxJackMonroe I couldn't get on with it either. Bits started drooping that shouldn't droop. GP said mooncup alone to blame.
Emotion: sadness
Intensity class:
|
2: moderate amount of sadness 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: ♪OLD FISH #discourage
Emotion: fear
Intensity score:
|
0.260
|
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: @lakeline I still find you pleasing.
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: Did u laugh today? Laugh hard? I hope so..we NEED laughter now. #love
This tweet contains emotions:
|
joy, love, optimism
|
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E).
|
Tweet: @david_garrett Quite saddened.....no US dates, no joyous anticipation of attending a DG concert (since 2014). Happy you are keeping busy.
Emotion: joy
Intensity score:
|
0.140
|
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: Now ...what to do for the next hour while waiting for #OurGirl to start @BBCOne ?!
Emotion: fear
Intensity class:
|
0: no fear can be inferred
|
Task: 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: @lilymacintyre_ she was my favourite such a joyful soul
Intensity score:
|
0.683
|
Task: Quantify the sentiment intensity or valence level of the tweet, giving it a score between 0 (highly negative) and 1 (highly positive).
|
Tweet: @govph I would like to know about the source of The President's optimism about running the country. I wonder if he can answer my curiosity.
Intensity score:
|
0.355
|
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: Seeing an old coworker and his wife mourn the loss of their 23 year old daughter was one of the saddest things I've ever seen 😢
This tweet contains emotions:
|
disgust, fear, pessimism, sadness
|
Task: Evaluate the tweet for emotional cues and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that indicate the tweeter's state of mind.
|
Tweet: Feeling like I've had the worst night of sleep ever - not great before the #London to #Brighton #cycle ride for @DMTFYP 🚴100k ?
This tweet contains emotions:
|
anger, disgust, sadness
|
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: Watch this amazing live.ly broadcast by @haythatjamile8 #musically
Emotion: joy
Intensity score:
|
0.519
|
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: It's the most magical time of the year......Xmas party announced and the #outrage commences. Gotta love Silicon Valley millennials.
This tweet contains emotions:
|
joy, love, optimism
|
Task: 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: @leener00 @libbyfloyd1 @G_Eazy my snap is andriaprebles ❤️
Emotion: anger
Intensity score:
|
0.271
|
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: every time a new Anthony Weiner revelation breaks, Bill Clinton says a prayer of thanks that texting/DMing didn't exist in his heyday.
Intensity score:
|
0.404
|
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: Lol little things like that make me so angry x
Emotion: anger
Intensity class:
|
2: moderate amount of anger 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: During the day @JeffProbst is jovial. At #TribalCouncil he's a different, darker fellow. Still simply but smiles are few. #Survivor
This tweet contains emotions:
|
joy, optimism
|
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: Modern family never fails to cheer me up. Especially Phil.
Emotion: joy
Intensity class:
|
3: high amount of joy can be inferred
|
Task: Calculate the intensity of emotion E in the tweet as a decimal value ranging from 0 to 1, with 0 representing the lowest intensity and 1 representing the highest intensity.
|
Tweet: @Lexual__ @jdspielman10 RIP to the 100s of black men,, women,CHILDREN killed in Chicago. Where is the outrage?
Emotion: anger
Intensity score:
|
0.562
|
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: @Onision @Eugenia_Cooney annoyed by the good loving fans of Onision including myself Is really annoyed at how people just are too cheerful.
Emotion: joy
Intensity score:
|
0.104
|
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: @cazzrhughes its reflective of the current political debate
Emotion: fear
Intensity class:
|
0: no fear 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: This nigga doesn't even look for his real family 🙄😂
Emotion: sadness
Intensity class:
|
0: no sadness 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: If you don't respond to an email within 7 fays, you wifl be killed by an animated gif of the girl from The Ring.
This tweet contains emotions:
|
anger, disgust
|
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: @kaijinboyfriend --while being animated much more recently technology-wise which makes for a very nice combination/look)
This tweet contains emotions:
|
joy, optimism
|
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: Boys Dm me pictures of your cocks! The best one will get uploaded! ☺️💦💦 #Cumtribute #dm #snap #snapchat #snapme #nudes #dickpic #cocktribute
This tweet contains emotions:
|
anticipation, joy, surprise
|
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: So much #terrible #music playing on the #radio has started to make me wonder weather my taste in music is good or just completely shit
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: @skinkev let's rage
This tweet contains emotions:
|
anger
|
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: Lmboo , using my nephew for meme
Intensity class:
|
1: slightly positive 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: @BBCPolitics @BBCNews I'd rather leave my child with @BorisJohnson
This tweet contains emotions:
| |
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: I just killed a spider so big it sprayed spider guts on me like a horror movie.\n#ugh #revenge
Emotion: anger
Intensity score:
|
0.521
|
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: Hi guys! I now do lessons via Skype! Contact me for more info. #skype #lesson #basslessons #teacher #free lesson #music #groove #rock #blues
Emotion: sadness
Intensity score:
|
0.167
|
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E).
|
Tweet: Georgia Tech's Secondary is as soft as a marshmallow. #horrible
Emotion: fear
Intensity score:
|
0.583
|
Task: Determine the sentiment intensity or valence score of the tweet, representing the tweeter's mental state on a continuum from 0 (highly negative) to 1 (highly positive).
|
Tweet: I can't pull myself out of depression
Intensity score:
|
0.054
|
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: “Set a goal to achieve something that is so big, so exhilarating that it excites you and scares you at the same time.” \n― Bob Proctor
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: ⊰ @FrameOfAnAngel ⊱ \n\n+ Of them. I'm here for answers, and if I scare her to death, there won't be answers for me. \n\nSo instead, I just +
Emotion: fear
Intensity class:
|
1: low amount of fear 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: @jpodhoretz I still respect you. I suppose there is so little to be gleeful about these days so take what you can. Good for you.
Emotion: joy
Intensity score:
|
0.417
|
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: @GarthJennings loved #sing #tiff but 1 q there is 1 japanese line but obviously spoken by non japanese. no way to find japanese for 1 line?
Intensity class:
|
0: neutral or mixed emotional state 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: #food #деньги #smile microsoft_.net_framework_4.5.1_full_plus_by_gora
Emotion: joy
Intensity score:
|
0.375
|
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: It's not that the man did not know how to juggle, he just didn't have the balls to do it.\n#funny #pun #lol #hilarious #punny
This tweet contains emotions:
|
joy, optimism
|
Task: Evaluate the tweet for emotional cues and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that indicate the tweeter's state of mind.
|
Tweet: @mikeburke91 @AP I guess. It's just heartbreaking the ease with which they can kill an innocent man and get away with it. #indignation
This tweet contains emotions:
|
anger, disgust, 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: @chloemcaleese what a nightmare!
Emotion: fear
Intensity class:
|
2: moderate amount of 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: Absolutely fuming that some woman jumped into my prebooked taxi and drove off 😡
Emotion: anger
Intensity class:
|
3: high amount of anger can be inferred
|
Task: Analyze the tweet's sentiment and assign it to either 'neutral or no emotion' or one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).
|
Tweet: @khloe_speaks sad music
This tweet contains emotions:
|
sadness
|
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: if you're unhappy with someone just fucking tell them you're unhappy and leave. Don't go fuckin around with other people on the side
Intensity class:
|
-3: very 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: When you have 15 doe run the opposite side of you 🙁
This tweet contains emotions:
|
anticipation, sadness
|
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E).
|
Tweet: I am just so bitter today 😐
Emotion: anger
Intensity score:
|
0.583
|
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