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Task: Evaluate the valence intensity of the tweeter's mental state based on the tweet, assigning it a real-valued score from 0 (most negative) to 1 (most positive). | Tweet: Someone needs to start listening to @OssoKXLY about #AllStarGame2017 ideas. #brilliant @700espn
Intensity score: | 0.600 |
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: @daveweigel a laurel and hearty handshake
Intensity class: | 1: slightly positive emotional state can be inferred |
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: A black female LEOπ was shot 8 times and died in Philadelphia --Where's the #outrage black people? @BarackObama #Sharpton #blm #TheFive
Intensity class: | -3: very 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: IΒve learnt that a #smile and good #morning goes a long way, and saying #thankyou goes even further. #quote #retweet #inspire
Emotion: joy
Intensity class: | 2: moderate amount of joy can be inferred |
Task: Evaluate the tweet for emotional cues and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that indicate the tweeter's state of mind. | Tweet: @Nxrthstxr I think it's the daunting fact of the typical offer being those grades. Even though it's been proven not to be the case exactly
This tweet contains emotions: | anger, pessimism, surprise |
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: My new favourite #film with out a shadow of a doubt it #Okja #beautifull #funny #sad #emotional #real #Netflix #MUSTWATCH #now
Emotion: sadness
Intensity class: | 0: no sadness can be inferred |
Task: Evaluate the strength of emotion E in the tweet, providing a real-valued score from 0 to 1. A score of 0 denotes the absence of the emotion, while a score of 1 indicates the highest degree of intensity. | Tweet: Every Wednesday I like to visit the inmates at Arkham. Deliver a fruit basket. And a cheery bouquet of enhanced interrogation.
Emotion: joy
Intensity score: | 0.458 |
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: When we give cheerfully and accept gratefully, everyone is blessed. Β»Maya Angelou
Intensity class: | 2: moderately 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: I don't want the pity of my instructors but I'd like some understanding. I'm truly trying despite ALL circumstances that make me discouraged
Emotion: sadness
Intensity score: | 0.625 |
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: Making my buddy cry !! Bitch wait for revenge π€ππ»
Emotion: anger
Intensity score: | 0.812 |
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: My #anxiety is rising tonight and I'm not sure why. Sometimes I wonder if I'm a magnet for any free-floating anxiety in the universe.
Emotion: fear
Intensity class: | 3: high amount of 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: Sometimes I get to sit back and be proud of myself for pleasing Him so well.
Emotion: joy
Intensity class: | 0: no joy 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: Swear all of my guy friends are scaredy cats. You don't do horror movies. You don't do haunted houses. Wtf do you do then?
Intensity class: | -2: moderately negative emotional state 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: Get there deviant differently enigmatic bellboy in passage to correct thy ring up jaunty: IWLDpe
Emotion: joy
Intensity class: | 0: no joy can be inferred |
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: @eMilsOnWheels I'm furious π©π©π©
Intensity class: | -3: very negative emotional state can be inferred |
Task: Assess the sentiment intensity or valence level of the tweet, ranging from 0 (extremely negative) to 1 (extremely positive). | Tweet: i just spent $40 on big little sis tomorrow and i am beyond happy about it #SAW #mums
Intensity score: | 0.883 |
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: They'll be yo friend, shake your hand, then kick in yo door thas the way the game goπ€π€.
This tweet contains emotions: | anger, 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: @KateyKeegan now I'm really excited for November! Hope they're not all horrid chavs though π
This tweet contains emotions: | anticipation, fear, joy |
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: @lala Loving your book 'The Power Play'-It is a serious game changer. If nothing else, my dreaming big will land me amongst the stars. π
This tweet contains emotions: | anticipation, joy, love, optimism |
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 hate that a black lady is painting herself white on the internet for laughs and likes... #terrible #BadForm #DidntLaugh
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: @GarfieldLineker @TimCRoberts *on his back. Apologies for retweeting a tweet with grammatical error #mybad π±
This tweet contains emotions: | disgust, sadness |
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: Paranoia is a fear every races has
Emotion: fear
Intensity class: | 1: low amount of fear can be inferred |
Task: Categorize the tweet into an intensity level of the specified emotion E, representing the mental state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: @MericanMainer AWW. I had a Maine Coon when I was little named Ted Eddy the Wonder Cat. They're such good cats! Very playful and sweet
Emotion: joy
Intensity class: | 2: moderate amount of joy can be inferred |
Task: Classify the tweet's emotional intensity into one of four ordinal levels of emotion E, providing insights into the mental state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: Watch this amazing live.ly broadcast by @rosannahill #musically
Emotion: joy
Intensity class: | 1: low amount of joy can be inferred |
Task: Gauge the level of intensity for emotion E in the tweet, assigning it a score between 0 and 1. A score of 0 indicates the lowest intensity, while a score of 1 indicates the highest intensity. | Tweet: @memorie_holiday @AngryOrchard about 2 wks ago,playing pokemon and not paying attention. Placed my elbow on a rail 3 inches from 4 no sting.
Emotion: anger
Intensity score: | 0.500 |
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: Band members wanted. Contact me #NewcastleGateshead #Sunderland #musicians #musicbusiness #musicislife #music #musically #band #blues #folk
Emotion: sadness
Intensity class: | 0: no sadness 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: @GMModular @goldmedalindia horrible experience with a company like this #goldmedal #horrible sales person #wrong commitments#wrongproduct
This tweet contains emotions: | anger, disgust |
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: @homoaesthetics YESYESYES like jd is the closest cahracter that is similar to blaine!! the optimism and ability to crack tough characters
Intensity class: | 1: slightly positive emotional state can be inferred |
Task: Determine the dominant emotion in the tweet and classify it as either 'neutral or no emotion' or one of the eleven provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust). | Tweet: My oldest cat pisses me off. She's always been weary of Kennen (senile kinda), but recently shes been sweet. Until she attacked and bit him.
This tweet contains emotions: | anger, fear |
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: @happyandbashful Flirt, simper, pout, repeat. Yuck.
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: @C1TYofFL1NT This will haunt my dreams. @JoePrich
This tweet contains emotions: | fear, 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: @PersephoneOD Her cheerful voice echoed through the grand, familiar home, a smile blossoming on my rosy brims, 'Mom.' I reciprocated the --
Emotion: joy
Intensity class: | 1: low amount of joy 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: @aradsliff don't know I'm from nj we are the worst on purpose.
Emotion: joy
Intensity class: | 0: no joy can be inferred |
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: Latest on new optimism on keeping #Raiders in #Oakland, live right now on @KCBSNews: @NFL meets here w/Lott & Schaaf to talk new stadium
Intensity class: | 1: slightly positive emotional state can be inferred |
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E). | Tweet: tfw you're en-route to your future :) !! @HUCJIR i'm coming for ya! #openhouse #futurecantor #NYCletsgo
Emotion: joy
Intensity score: | 0.560 |
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: Wishing the Ipswich Tigers good luck in their games throughout homecoming week!! We are cheering you on here at the City Office! GO TIGERS!
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: I'm not the type to flee from adversity nor does it discourage me. I'll always stand strong in the paint
Emotion: sadness
Intensity class: | 0: no sadness 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: Coulda sworn it was Interview With A Vampire. Hmmm......Mandela Effect anyone? \n#interviewwithavampire #annerice #books #horror #ilovevamps
This tweet contains emotions: | anticipation, fear, joy, love |
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: 340:892 All with weary task fordone.\nNow the wasted brands do glow,\nWhilst the scritch-owl, scritching loud,\n#AMNDBots
Emotion: sadness
Intensity class: | 1: low amount of sadness 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: @jamiesmart Huh! It's always my fault isn't it >:( #huff #sulk
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: in love with @BarberCeleste insta!!!... #hilarious
Emotion: joy
Intensity class: | 3: high 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: I just want to say: social media isnβt here to #bully that has to be #stopbullying ! Please be kind to eaxh other! #lovewins
Emotion: fear
Intensity score: | 0.360 |
Task: Assess the sentiment intensity or valence level of the tweet, ranging from 0 (extremely negative) to 1 (extremely positive). | Tweet: My partner's new headphones works 2 well. It's bad. He couldn't hear me yelling @ him when i was about 5ft in front him! #ironic #technology
Intensity score: | 0.333 |
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: @VerizonSupport thanks for saying My wife and I were getting our iphones today and then losing both of them with no ETA #thanks #angry
This tweet contains emotions: | anger, disgust |
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: This girl was shaking her drink in the break room and it wasn't fully closed and yeah it's all over the place now including meπππ
Emotion: fear
Intensity class: | 0: no fear 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: Watch this amazing live.ly broadcast by @brooks_swaggysquad #lively #musically
This tweet contains emotions: | joy |
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: @JDMHatch_G @A34Bart @IOInteractive @Ravenclaww04 @Hitman This is an attitude that makes me beam with delight every time I encounter it.
Emotion: joy
Intensity class: | 2: moderate amount of joy can be inferred |
Task: Determine the appropriate intensity category of emotion E for the tweet, reflecting the emotional state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: @zavvi @zavvihelp only offering 6 moth warranty #ps4pro #truth #ripoff
Emotion: fear
Intensity class: | 0: no fear 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: I love when #girls are busy in teaching how to #pout while taking #selfie in a mall , their desication is immense #women love #perfection
Emotion: sadness
Intensity score: | 0.125 |
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: promise of restoration to the nation of israel...'everywhere you look blessing '..barns/wine overflow.Everything beautiful #joyful #do_u_see
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: @marthalyssa yep. LOL
This tweet contains emotions: | joy, optimism |
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: Ppl like that irritate my soul
Intensity class: | -2: moderately negative 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: Old saying 'A #smile shared is one gained for another day' @YEGlifer @Scott_McKeen
Emotion: joy
Intensity class: | 1: low amount of joy 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: I forgot #BB18 was on tonight ο³ that is how much the real world has been distracting me #horrid ο
οΌοο
Emotion: fear
Intensity class: | 0: no fear 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: @RVAGameBreak @GAHSBasketball @GAJagsFootball \nGo Jags!!π I think we have a good shot of beating Deep Run tomorrow! #revenge
Emotion: anger
Intensity score: | 0.417 |
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: @MannersAboveAll *laughs louder this time, shaking my head* That was really cheesy, wasn't it?
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: @Johncrookshanks 'Elizabeth Smith!' She said with a cheery smile 'Pleasure to meet you, sir! Where have you travelled from?'
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: terror attacks in usa pay no mind lol
Emotion: fear
Intensity score: | 0.479 |
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: @WhiskurMew Happy birthday, beautiful! I hope today is as lovely, wonderful, and astounding as you are!! You deserve no less than that! ππππ
Emotion: joy
Intensity score: | 0.891 |
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: @laura221b I've left it for my dad to deal with π My work is done as soon as it's felt the wrath of my slipper π·
Emotion: anger
Intensity score: | 0.521 |
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: Do not #educate your child to be #rich, educate them to be #happy. So when they grow up, they'll know the #value of things, not the price.
Emotion: joy
Intensity score: | 0.371 |
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: People that smoke cigarettes irritate my soul.
Emotion: anger
Intensity score: | 0.492 |
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: A3: But chronic sadness may mean there are underlying issues than getting sad occassionally over a particular issue (2/2) #mhchat
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: @DonnyMurray I'm just no offended by stuff.We're gettin a situ where folk moan about the Polis/SNP but then happy to snitch when offended...
This tweet contains emotions: | anger, disgust |
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: If the future doesn't fill you with existential dread are you even a real person
Emotion: fear
Intensity class: | 0: no fear can be inferred |
Task: Calculate the intensity of emotion E in the tweet as a decimal value ranging from 0 to 1, with 0 representing the lowest intensity and 1 representing the highest intensity. | Tweet: Why is it so windy? So glad I didn't ride my bike. #fear #wind
Emotion: fear
Intensity score: | 0.812 |
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: Omg he kissed herπ #w
This tweet contains emotions: | anticipation, joy, surprise |
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 truly feel like science has the ability to make a milk out of anything ... cashew milk, hemp milk, pine nut milk, dandelion milk
Emotion: sadness
Intensity score: | 0.271 |
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: Had a conversion with a random fellow passenger on a #melbourne @metrotrains yesterday evening #youwouldntreadaboutit
This tweet contains emotions: | joy, optimism |
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: @metrotrains why is there no disabled access at pontefract monkhill?
Emotion: fear
Intensity class: | 0: no fear 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: Shoutout to @VZWSupport for ruining my iPhone 7 order!!
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: @girlsreallyrule Both Trump + King are relentless self-promoters who don't give a rip about anyone else. A perfect match for both Donalds.
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: can't believe Mint fest is two days away and i hate my outfit π©π©π #nightmare
Emotion: fear
Intensity score: | 0.542 |
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: If Payet goes either in Jan or @ the seasons end, can't say I blame him. The boy must b so disheartened by what he's seeing at the mo.
Emotion: sadness
Intensity score: | 0.625 |
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: @NM_NickNocturne Incentivise people to roam the Internet being morally offended, as if they didn't do it enough already.
Intensity class: | -2: moderately negative emotional state can be inferred |
Task: Determine the prevailing emotional tone of the tweet, categorizing it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that most accurately represent the tweeter's mental state. | Tweet: Had to delete my Facebook too much for me π€£
This tweet contains emotions: | anger, disgust, sadness |
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: @1720maryknoll I was #fuming Kenny.
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: That's the old me though #imachildofgod #whatistwerking #sober #married #bye
This tweet contains emotions: | joy, optimism, 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: One of the great/horrible moments as a professor is seeing a wonderful student leaving your university to pursue his/her true passion.
Intensity class: | -2: moderately negative 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: I think they may be
Emotion: anger
Intensity class: | 0: no anger can be inferred |
Task: Evaluate the strength of emotion E in the tweet, providing a real-valued score from 0 to 1. A score of 0 denotes the absence of the emotion, while a score of 1 indicates the highest degree of intensity. | Tweet: Don't fucking tag me in pictures as 'family first' when you cut me out 5 years ago. You're no one to me.
Emotion: fear
Intensity score: | 0.621 |
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: @Thatguy_dree @RecklessWonder_ neither one of y'all can see me in this madden
This tweet contains emotions: | anger, 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: @mikeburke91 @AP I guess. It's just heartbreaking the ease with which they can kill an innocent man and get away with it. #indignation
Emotion: anger
Intensity class: | 3: high amount of anger can be inferred |
Task: Gauge the level of intensity for emotion E in the tweet, assigning it a score between 0 and 1. A score of 0 indicates the lowest intensity, while a score of 1 indicates the highest intensity. | Tweet: Watch this amazing live.ly broadcast by @jaredhorgan #musically
Emotion: joy
Intensity score: | 0.521 |
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: I'm always smiling so that's why I'm always happy π
Intensity class: | 3: very 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: Accept the challenges so that you can feel the exhilaration of victory!!
This tweet contains emotions: | anticipation, joy, optimism, surprise, 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: Three days off a month with two ex wives and no home could be worse. I don't know how, but it could #oilandgas #optimism
Emotion: joy
Intensity score: | 0.250 |
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: @CurtisJobling Yes indeed! We know masses of students would be so excited to see you! We need to get this sorted! #haunt
This tweet contains emotions: | fear, joy, optimism |
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 need some to help with my anger
Emotion: anger
Intensity score: | 0.574 |
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: alternate reality where @PoetryFound has a comments section and you can give poems a cheery thumbs up or a disappointed thumbs down
Emotion: joy
Intensity score: | 0.246 |
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: It's so breezy I love it π¬οΈππ
Emotion: joy
Intensity class: | 2: moderate amount of joy can be inferred |
Task: Assess the magnitude of emotion E in the tweet using a real number between 0 and 1, where 0 denotes the least intensity and 1 denotes the most intensity. | Tweet: i excepted the eclipse to make me believe in an omniscience force #dissapointed
Emotion: anger
Intensity score: | 0.641 |
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: @thatradiogeek That is a tremendous thing to wake up to and read, man. Glad to hear it, as we need WAY more people helping with this.
Emotion: sadness
Intensity class: | 0: no 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: @MLB @JoeyBats19 Sam Dyson is probably having flashbacks right about now. #nightmare
Emotion: fear
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: A #new day to #live and #smile. Hope all the #followers a nice #night or #day. :D
Emotion: joy
Intensity score: | 0.688 |
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: Michelle, who did NOTHING is hating on Nicole's game hahaha.... #bb18
This tweet contains emotions: | disgust, joy |
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: A good thing about being sick is that coughing is like an ab workout. Maybe my abs will be more defined by the time I'm better ππ
Emotion: joy
Intensity class: | 1: low amount of joy can be inferred |
Task: Classify the tweet's emotional intensity into one of four ordinal levels of emotion E, providing insights into the mental state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: Lol Adam the Bull with his fake outrage...
Emotion: anger
Intensity class: | 1: low amount of anger 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: Be happy not because everything is good, but because you can see the good side of everything
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: As if he heard my thought on the ether, my #ex has just posted #facebook pic of himself snuggling up with said #cats... now Im just #angry
Emotion: anger
Intensity score: | 0.521 |