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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: All work and no play makes Jack a dull boy
Emotion: sadness
Intensity score:
|
0.500
|
Task: Gauge the intensity of sentiment or valence in the tweet, indicating a numerical value between 0 (extremely negative) and 1 (extremely positive).
|
Tweet: Impractical Jokers...practically genius!!! @BQQuinn #laughter #good4thesoul #ImpracticalJokers #bingewatching
Intensity score:
|
0.732
|
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: @PediMGHHMS3 sickle cell if right pt background. Or could be JIA or an allergic reaction to a bite e.g. bee sting among others.
Emotion: anger
Intensity score:
|
0.292
|
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: @veggiesausage that happens...u will be ok tomorrow cheer it up..Don't give up no no noπππ
Emotion: joy
Intensity score:
|
0.396
|
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: Last @LGCanada product I buy - I promise! Absolutely #terrible #CustomerService
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: You have a #problem? Yes! Can you do #something about it? No! Than why #worry
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: Marcus Rojo is the worst player i have ever seen. Useless toasting burning bastard
Emotion: anger
Intensity class:
|
2: moderate amount of anger can be inferred
|
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: I am just so bitter today π
This tweet contains emotions:
|
anger, disgust, pessimism, sadness
|
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: @ggreenwald Smh, remove ideologically bankrupt and opportunistic establishment now. They're burning all bridges and social contracts.
Emotion: anger
Intensity class:
|
2: moderate amount of anger can be inferred
|
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: Been sober for days lmao
This tweet contains emotions:
|
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: @iamnotatwit Or did I lie and cut 5 years off my age to be young and spry and hire-able in Hollywood? #thegoldbergs
This tweet contains emotions:
|
disgust, fear, surprise
|
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E).
|
Tweet: I highly suggest if you are looking online for a company to help you send you're package overseas..DO NOT EVER EVER USE @FastLaneInt #horrid
Emotion: fear
Intensity score:
|
0.438
|
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E).
|
Tweet: @phil500 \nSo sadden \nSpunky a beautiful dog\nA sad story a lovely happy\nAn loved dog \nPlay little one have fun you\nare so loved
Emotion: sadness
Intensity score:
|
0.452
|
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: @BuzzFeed so this houses will get into my instestines and scare my poop and I'll shit my pants?
This tweet contains emotions:
|
anger, disgust, fear
|
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: @NJDDanin123 I personally liked #relentless β¦didn't get #OurHouse #OneJersey #werealldevilsinside \nDoes nothing till a puck drops #NJDevils
This tweet contains emotions:
|
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: What do Aquila, Ajahnae, and Euriechsa have in common besides ridiculously stupid,horrible,ugly, God awful names? Tracey IS NOT their father
This tweet contains emotions:
|
anger, disgust, pessimism, sadness
|
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: What do Aquila, Ajahnae, and Euriechsa have in common besides ridiculously stupid,horrible,ugly, God awful names? Tracey IS NOT their father
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: @Thebeast_ufc what happened to the suicide tweet it was a joke obviously how could that offend anyone?π€
Intensity score:
|
0.422
|
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: It's better to be wetter than it is dry' - @RLevin91 certainly found that hilarious #GBBO
Emotion: joy
Intensity score:
|
0.600
|
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: @KeithOlbermann depressing how despicable Trump, with no policies, campaigning on bigotry & rancour can be so close, evil immoral disaster
Emotion: sadness
Intensity class:
|
3: high amount of sadness 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 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: The best revenge is massive success. βFrank Sinatra
Intensity class:
|
1: slightly positive emotional state can be inferred
|
Task: Determine the sentiment intensity or valence score of the tweet, representing the tweeter's mental state on a continuum from 0 (highly negative) to 1 (highly positive).
|
Tweet: Super shitting it about this tattoo #nervous
Intensity score:
|
0.344
|
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: Staff on @ryainair FR1005. Asked for info and told to look online. You get what you pay for. #Ryanair @STN_Airport #Compensation
Emotion: fear
Intensity score:
|
0.312
|
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: Lines from Don't Quit take me to a place of ultimate strength when I start to feel weary. πͺπΎ
Emotion: sadness
Intensity score:
|
0.479
|
Task: Determine the sentiment intensity or valence score of the tweet, representing the tweeter's mental state on a continuum from 0 (highly negative) to 1 (highly positive).
|
Tweet: I'm going to get the weirdest thank you note--or worse--total silence and no acknowledgement.
Intensity score:
|
0.467
|
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: If you love something, let it go. If it comes back, it is yours. If it doesn't, it never will. #sadness #accepting
This tweet contains emotions:
|
optimism, sadness
|
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 folks sorry if anything offensive got posted on here yesterday my account got hacked. All fixed now though. I hope :-/ #angry #annoyed
Intensity class:
|
-3: very negative emotional state 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: God hears your voice optimism at the moment that you think that everything has failed you β¨.
Emotion: joy
Intensity score:
|
0.312
|
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E).
|
Tweet: @TheDuranSite Russian mistrust of the U.S is well justified & the precaution they've taken are very prudent.
Emotion: fear
Intensity score:
|
0.375
|
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: @happyandbashful Flirt, simper, pout, repeat. Yuck.
Emotion: sadness
Intensity score:
|
0.625
|
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: @pikapies I have many happy memories of the Isle Of Wight.\n...\nBut yeah, sink that shit.
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: #picoftheday : How...why... Really... !!\n #funny #picoftheday #lol #random #laugh #chair #of #despair #funnypics #virgin #cafe #i...
Emotion: sadness
Intensity score:
|
0.146
|
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: @soozclifford Sure have... Sydney are too tough, too quick and their 'team' pressure is too much for the Cats to handle. Motlop/Cowan #timid
Emotion: fear
Intensity class:
|
0: no fear can be inferred
|
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: Seeing double am so tired but I always grudge getting off my phone at night π
Intensity class:
|
-2: moderately negative emotional state 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: #personaldevelopment\n\nToday is a gift, that's why it's called the present... #happiness #optimism #entrepreneur #personaldevelopment β¦
Intensity class:
|
3: very positive 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: Drawing mini-comics is joyful; folding mini-comics is meditative and relaxing. I think I need to do them for more than just Halloween...
Emotion: joy
Intensity score:
|
0.562
|
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: @MollieTebbatt guess what I'm doing? watching your great grandad sink the titanic..
Emotion: sadness
Intensity class:
|
0: no sadness 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: @B4caferacer I see things in the clouds that others can't see so I can
This tweet contains emotions:
|
joy, optimism, trust
|
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: I forgot #BB18 was on tonight ο³ that is how much the real world has been distracting me #horrid ο
οΌοο
Emotion: fear
Intensity score:
|
0.529
|
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: I wonder what would happen if I were a father. #weary
This tweet contains emotions:
|
anticipation, fear, pessimism, sadness
|
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: All clouded out.\n\n Considering using a camera, 1) star trails 2) eyepiece projection.
Emotion: sadness
Intensity score:
|
0.250
|
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: @BenLeubsdorf @DykstraDame @WSJ idiots are going to sink the economy with free money policies.
Emotion: sadness
Intensity class:
|
0: no sadness can be inferred
|
Task: Gauge the intensity of sentiment or valence in the tweet, indicating a numerical value between 0 (extremely negative) and 1 (extremely positive).
|
Tweet: @TheOnlySweeney their slogan should've been #start instead of #finish
Intensity score:
|
0.375
|
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: today has been terrible but tonight will end better because I get to see Malik β€οΈ
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: @iJuvia_ \n\nHearing the noises, Akame opened her eyes and sat up, facing Juvia. She didn't expect at all to see someone around and staid --
This tweet contains emotions:
| |
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: @frecklybellamy the walking dead, mr robot, american horror story, merlin
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: sav tells our mom 'I love you' and she responds 'Oh.' #sad
Emotion: sadness
Intensity class:
|
2: moderate amount of sadness 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: @RadioX @ChrisMoyles wow. not heard this in forever. Random but. great #xph
Emotion: anger
Intensity class:
|
0: no anger can be inferred
|
Task: Categorize the tweet's emotional tone as either 'neutral or no emotion' or identify the presence of one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).
|
Tweet: π I just want to start all over again .
This tweet contains emotions:
|
anticipation, optimism, sadness
|
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: Been working in Blanchardstown shopping centre for over 2 years now and I only figured out today where Marks & Spencer's is #lost
This tweet contains emotions:
|
disgust, pessimism, sadness
|
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: Overwhelming sadness. This too shall pass. #lost #lonley #startingover
This tweet contains emotions:
|
disgust, pessimism, sadness
|
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: @ccgdavidson I remember being awestruck looking around thinking, 'You could fit the entire population of our town in here ten times over.'
Emotion: fear
Intensity score:
|
0.271
|
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 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: Use your smile to change the world. Don't let the world change your smile.' #quote #actorslife #smile #love #hardworkpaysoff #fun
Intensity class:
|
3: very positive emotional state can be inferred
|
Task: Assign one of four ordinal intensity classes of emotion E to a given tweet based on the emotional state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.
|
Tweet: @asjoshtaylor sadly I don't think I'll see you on tour, but have fun, you're gonna rock! πππ»π #HotForMeTour
Emotion: sadness
Intensity class:
|
0: no sadness 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: @TamraBarney @ShannonBeador @RHOC_KellyDodd Tamra would F her up if she swung on Tamra\nKelly is a piece of π© #needstobeadmitted #bully
Emotion: fear
Intensity score:
|
0.542
|
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: @RogueCoder250 We are in so much trouble!! I don't think the Rev will see the funny side of our project. #nervous
This tweet contains emotions:
|
fear
|
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'm getting so nervous for my first anatomy exam π©
This tweet contains emotions:
|
fear
|
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 don't fuck with people who don't smile back at me in corridors
This tweet contains emotions:
|
anger, disgust
|
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: Honestly don't know why I'm so unhappy most of the time. I just want it all to stop :( #itnevergoes
This tweet contains emotions:
|
fear, pessimism, sadness
|
Task: Categorize the tweet's emotional tone as either 'neutral or no emotion' or identify the presence of one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).
|
Tweet: @KMunie7 @KaranEsch Helluva lot more animated than they were for the actual game >.<
This tweet contains emotions:
|
anticipation, joy, love, optimism
|
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: #India is sponsoring terrorism in #Balochistan. #KulbhushanYadav an Indian spy agent was arrested in Balochistan by Pakistani forces.
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: @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 class:
|
3: high amount of 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: @kwelbyroberts they will come and you will rejoice at their arrival.
Emotion: joy
Intensity class:
|
1: low amount of 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: Who knew softballs could sting so bad? Jimmy Fallon has been under a lot of heat for his &ldquo;softball&rdquo; Donald Trump interview
Emotion: anger
Intensity score:
|
0.414
|
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: @cburt43 turn that frown upside down
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: Nature looks a lot greener on gloomy dayz
Emotion: sadness
Intensity class:
|
2: moderate amount of 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: Let's refuse to live in #fear - #sotoventures
This tweet contains emotions:
|
fear, 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: I'm Black, 43. I read books, p/u my kids from school....'My prayer is that u wl lv a long, fulfilling, joyous, peaceful, GOD-pleasing life!
This tweet contains emotions:
|
joy, love, optimism, trust
|
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: @mediacrooks @thenewshour @LodhiMaleeha @ndtv @IndiaToday This is hilarious ! Not a Freudian slip, eh !
Intensity score:
|
0.821
|
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: Why is it when you nap during the day you are so comfortable but sleeping at night you'll never be as comfortable
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: why are people so offended by kendall he ends photo shoot like seriously shut the fuck up
This tweet contains emotions:
|
anger, disgust
|
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'm honestly upset that they rewarded Nicole 500k. #depressing #paulwasrobbed #rewardhardwork #bitterjury #bb18
Emotion: sadness
Intensity score:
|
0.667
|
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: Remember when Joe and Quinn had a thing on glee
Emotion: joy
Intensity class:
|
0: no joy 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: Love is when all your happiness and all your sadness and all your feelings are dependent on another person.
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: I just deleted my save file trying to load it up. Now I have to start. All. Over. Again. I am going to freaking kill someone. Pray for me.
Emotion: fear
Intensity score:
|
0.820
|
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: @CNN Wait, didn't she get a case of the ass when Donald Trump called it terrorism BEFORE all the facts were in? I guess it's ok if she does
Emotion: fear
Intensity class:
|
0: no fear can be inferred
|
Task: Evaluate the tweet for emotional cues and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that indicate the tweeter's state of mind.
|
Tweet: @NessaMatthews he's perfect. But not even in that way where you sort of resent him or suspect that he leads a double life. Just perfect.
This tweet contains emotions:
|
joy, love, optimism
|
Task: Assess the magnitude of emotion E in the tweet using a real number between 0 and 1, where 0 denotes the least intensity and 1 denotes the most intensity.
|
Tweet: How do you help someone with #depression who doesn't believe they have it and doesn't trust therapists?
Emotion: sadness
Intensity score:
|
0.604
|
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: @l1ght__eyes u tried boiling em takes years too
This tweet contains emotions:
|
sadness
|
Task: Categorize the tweet into an ordinal class that best characterizes the tweeter's mental state, considering various degrees of positive and negative sentiment intensity. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred.
|
Tweet: Well look at the bright side. You found a use for that rope #TipsToSurviveAPowerOutage
Intensity class:
|
0: neutral or mixed 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: Some moving clips on youtube tonight of the vigil held at Tulsa Metropolitan Baptist church for #TerenceCruther #justice #sadness
This tweet contains emotions:
|
sadness
|
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: @daveweigel a laurel and hearty handshake
Intensity score:
|
0.621
|
Task: Determine the valence intensity of the tweeter's mental state on a scale of 0 (most negative) to 1 (most positive).
|
Tweet: Tend the sick, Lord Christ; give rest to the weary, bless the dying, soothe the suffering, pity the afflicted, shield the joyous;
Intensity score:
|
0.645
|
Task: Classify the tweet into one of four ordinal classes of intensity of emotion E that best represents the mental state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.
|
Tweet: You forever straight so fix that frown u goodπ @amayyaaag__
Emotion: anger
Intensity class:
|
1: low amount of anger 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: @tweetingacct @amandacarpenter @TeamTrump the 'pledge' would have never have to be made if petulant child POStrump didn't threaten to run
This tweet contains emotions:
|
anger, anticipation, disgust, fear, pessimism
|
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: Don't be bitter
This tweet contains emotions:
|
disgust, optimism, pessimism, sadness
|
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: I seriously hope these chances Celtic are missing are going to come back to haunt them with an Alloa sucker punch
Intensity score:
|
0.387
|
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: @politico @realDonaldTrump another angry white man!
Emotion: anger
Intensity score:
|
0.708
|
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: Wow just watched Me Before You and it was seriously one of the most depressing movies of my life
Emotion: sadness
Intensity score:
|
0.667
|
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 bet dat dog eating name brand cheerios. cant relate. i eat cheery O's
This tweet contains emotions:
| |
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: penny dreadful just cleaved off a fraction of my heart
Emotion: sadness
Intensity class:
|
1: low amount of 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: The best revenge is massive success. βFrank Sinatra
This tweet contains emotions:
|
anger, optimism, surprise
|
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: She's foaming at the lips the one between her hips @realobietrice, one of many great lyrics
Intensity class:
|
1: slightly positive emotional state can be inferred
|
Task: Assess the magnitude of emotion E in the tweet using a real number between 0 and 1, where 0 denotes the least intensity and 1 denotes the most intensity.
|
Tweet: And by the way, Takeru's eyes sparkling while eating was like the cutest thing ever.
Emotion: joy
Intensity score:
|
0.688
|
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: Romero is fucking dreadful like seriously my 11 month old is better than him.
Emotion: fear
Intensity score:
|
0.458
|
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: I had Golden Ocean the other day it was lush, then I gagged and was sick... What a waste of Β£20 - I was fuming @EmmaGould_ I miss you
This tweet contains emotions:
|
anger, disgust, sadness
|
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: I'm always smiling so that's why I'm always happy π
Emotion: joy
Intensity score:
|
0.731
|
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: Knowing I have my hair to wash and dry is like knowing you had that English close reading in your school bag to do #dread
Emotion: fear
Intensity score:
|
0.650
|
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: @aGirlHasNo_Name @MdlMurray shot by black police woman Typical looney toon thinking. #Hillary #divide #chaos
This tweet contains emotions:
|
anger, disgust
|
Task: Place the tweet into an appropriate ordinal class, representing the tweeter's mental state by assessing the levels 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: @TheRandomAnt @meg_m203 yeah, they figured that ornaments are way more wanted than spektar and desolate gear. Well they thought right.
Intensity class:
|
0: neutral or mixed emotional state can be inferred
|
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