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Task: Categorize the tweet into an intensity level of the specified emotion E, representing the mental state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: I feel like an appendix. I don't have a purpose. #sad #depressed #depression #alone #lonely #broken #sadness #cry #hurt #crying #life
Emotion: sadness
Intensity class: | 3: high amount of sadness 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: @cazzrhughes its reflective of the current political debate
Emotion: fear
Intensity class: | 0: no 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: I seriously hope these chances Celtic are missing are going to come back to haunt them with an Alloa sucker punch
Emotion: fear
Intensity class: | 0: no fear can be inferred |
Task: Determine the dominant emotion in the tweet and classify it as either 'neutral or no emotion' or one of the eleven provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust). | Tweet: Zero help from @ups customer service. Just pushing the buck back and forth and promising callbacks that don’t happen. #anger #loathing
This tweet contains emotions: | anger, disgust |
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: Come to the @BullSkitComedy FUNdraiser this Fri. at 8pm @TheScottBlock. Because #pie + #face = !
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: What we fear doing most is usually what we most need to do.' ~Tim Ferriss #inspiring #inspired #motivation #fear #success #hustle
Emotion: fear
Intensity score: | 0.292 |
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: @Bickley_Marotta yea because forcing 5 turnovers and holding a pretty good offense to 7 points is concerning.....oh wait. NO!!
Intensity score: | 0.301 |
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: so many 'protests for peace' going on lately but all i see is people burning down they're own cities and hometowns. Practice what u preach.
This tweet contains emotions: | anger, disgust, sadness |
Task: Assign a numerical value between 0 (least E) and 1 (most E) to represent the intensity of emotion E expressed in the tweet. | Tweet: We're very busy #coding a whole network manager for #unity3d based on #steamworks networking. #gamedev #indiedev #3amDeadTime #horror #game
Emotion: fear
Intensity score: | 0.417 |
Task: Assess the sentiment intensity or valence level of the tweet, ranging from 0 (extremely negative) to 1 (extremely positive). | Tweet: @amstrado_CPC @ShittySUFanart the single tear is him being joyous that he's deleted the monster that has brought generations of despair
Intensity score: | 0.667 |
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: @Deadspin @Rlblack1Rob My guess is he's just a convenient target for misplaced anger. What they're really mad at is how they played.
This tweet contains emotions: | anger |
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: Being #happy means letting go of the clinging and attachment to things in your life. #WednesdayWisdom #life
Intensity score: | 0.688 |
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: Well stock finished & listed, living room moved around, new editing done & fitted in a visit to the in-laws. #productivityatitsfinest #happy
This tweet contains emotions: | joy |
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E). | Tweet: @Aurena1701 @AngryOrchard he didn't sting me luckily. He just flew off happy and drunk. Lolololol
Emotion: anger
Intensity score: | 0.146 |
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: @RogueCoder250 We are in so much trouble!! I don't think the Rev will see the funny side of our project.
This tweet contains emotions: | fear, joy, 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: I told myself i wouldn't talk about this but i need to bring it up. I'm slightly bitter about the tøp cover of cancer
Emotion: anger
Intensity class: | 2: moderate amount of anger 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: This anger inside I turned to fuel, I burned and watched myself spin down, like inferno types,
Emotion: anger
Intensity class: | 3: high amount of anger 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: I am just so bitter today 😐
This tweet contains emotions: | anger, disgust, pessimism, sadness |
Task: Calculate the intensity of emotion E in the tweet as a decimal value ranging from 0 to 1, with 0 representing the lowest intensity and 1 representing the highest intensity. | Tweet: Feeling #gloomy
Emotion: sadness
Intensity score: | 0.793 |
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: Jorge deserves it, honestly. He's weak. #revolting #90dayfiance
Emotion: fear
Intensity score: | 0.229 |
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: Halfway to work and I realize I forgot to put on underwear....It's going to be one of those days! #mombrain #toomuchgoingon #longday
This tweet contains emotions: | anger, disgust, pessimism |
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: @JimRichMoriarty + I am in your life! *He yells* Surprise, surpriiise! *He chirps cheerfully, with a wicked grin on his lips*
This tweet contains emotions: | joy, optimism, surprise |
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: Good morning joyful people. Choose happiness to have a great day today #morning #happiness #grandmercurejktkemayoran
Intensity score: | 0.917 |
Task: Measure the intensity of sentiment or valence in the tweet, assigning it a score between 0 (highly negative) and 1 (highly positive). | Tweet: @fixindk @RevoltRazor @dragons1015 Guys don't use that type of language. Save it for raging...
Intensity score: | 0.328 |
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: y'all shabazz's name in my phone is 'easy breezy beautiful' & I will not apologize.
Emotion: joy
Intensity score: | 0.300 |
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: These #NewEnglandPatriots jerseys look like some whack ones that you tried to make when you made custom jerseys on #madden 04
Emotion: anger
Intensity score: | 0.271 |
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: A pessimist sees the difficulty in every opportunity, an optimist sees the opportunity in every difficulty' -Sir Winston Churchill-
Intensity class: | 1: slightly positive emotional state can be inferred |
Task: Evaluate the tweet for emotional cues and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that indicate the tweeter's state of mind. | Tweet: Saga: When all of your devices and teles fail just in time for bake off #gbbo
This tweet contains emotions: | anger, disgust, 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: @GOT7Official @jrjyp happy birthday jin young!!!!!! #PrinceJinyoungDay #happyjinyoungday #got7 #happy #birthday
Intensity class: | 3: very positive emotional state 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: @Yoshi_OnoChin can you please not have Canadian players play US players, that lag is atrocious. #fixthisgame #trash #sfvrefund
Emotion: anger
Intensity score: | 0.646 |
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: @WilsonsWorld I was in high school and remember helping neighbors clean up back home in Greenville. Pretty sobering stuff. #sadness
Emotion: sadness
Intensity score: | 0.688 |
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: @tonygoldmark Yeah I won't mourn it but I'm glad I rode it the last time I visited.
Emotion: sadness
Intensity score: | 0.333 |
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: @PAULROVlA the first resulted in me angrily sobbing and ranting about finnick in the cinema
Emotion: anger
Intensity score: | 0.562 |
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: Cause fail or pass I refuse to be sober
Emotion: sadness
Intensity class: | 2: moderate amount of sadness 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: Noooooo @GBBOUK without #MaryBerry will be #awful #endofanera going 2b so #lost @Channel4 have bought a #lameduck there #notallaboutthemoney
This tweet contains emotions: | anger, disgust, pessimism |
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: Special thanks to @hamsterwatch & @UgotBronx for keeping us updated & entertained this dismal BB season 💕
Emotion: sadness
Intensity class: | 0: no sadness 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: Nawaz Sharif's UN should start #सत्य_बोध_यात्रा as after all his #UNGA speech has awaken the world about their role in sponsoring #terrorism
Emotion: fear
Intensity class: | 1: low amount of 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: @YahooFantasy update may have been the worst mistake of my day #horrible
Emotion: fear
Intensity class: | 2: moderate amount of fear 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: Thank you @twitter for the balloons today. #smile #goodday #48
Emotion: joy
Intensity score: | 0.833 |
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: so I picked up my phone!!!' #shocking 😳
Emotion: fear
Intensity score: | 0.542 |
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: Val reminds me of one of the cheerful witches that looks after Aurora in Disney’s Sleeping Beauty. #GBBO
Emotion: joy
Intensity score: | 0.521 |
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: @megalvz literally was gloomy for an hour
Intensity class: | -3: very 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: @Apple thanks for ios10 update, even the best app @telegram freezing and crashing on SE.
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: If a cop is going to pull a gun on you for no reason at all and threaten you, you should be able to merk his ass and walk away.
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: It is a solemn thing, and no small scandal in the Kingdom, to see God’s children starving while seated at the Father’s table. -AW Tozer
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: Your lion's heart\nWill protect you under stormy skies\nAnd I will always be listening for your laughter and your tears
This tweet contains emotions: | joy, optimism, trust |
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: ok, ok.. I know.. my last tweet was
This tweet contains emotions: | joy |
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: This shit hurting my heart 😪 that's how serious it is .
This tweet contains emotions: | anger, 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: @komal_sidhnani true...\nThey r burning with other's pleasure!\nPpl in true love happiness everywhere _😃
Emotion: anger
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: @jjskeffington @foodbelfast I dread to think!
Emotion: fear
Intensity score: | 0.583 |
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: Watching driven by food and @andrewzimmern going to Devon Ave to eat nihari makes me gleeful af
Emotion: joy
Intensity score: | 0.780 |
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: Use your smile to change the world. Don't let the world change your smile.' #quote #actorslife #love #hardworkpaysoff #fun
Emotion: joy
Intensity score: | 0.745 |
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: @Zen1dfabflake You are all our angelic comrades!
Emotion: fear
Intensity score: | 0.188 |
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E). | Tweet: Southampton playing really well here. Youngsters Matty Targett and Jake Hesketh in particular and Austin and Long formidable as a front two
Emotion: fear
Intensity score: | 0.271 |
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: It's a beautiful day today. Cloudy but sunny and breezy.
Emotion: joy
Intensity class: | 2: moderate amount of joy 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: I hate those sugar cookies shit is awful
This tweet contains emotions: | anger, disgust |
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: @TiburonChamber plus a hearty pour of #yachtrock by #mustacheharbor !
Emotion: joy
Intensity class: | 1: low amount of joy 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: Watch this amazing live.ly broadcast by @maisiev #lively #musically
This tweet contains emotions: | joy, love, surprise |
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: Jimmy Carr makes me want to cry and cry *shiver*
Emotion: fear
Intensity class: | 2: moderate amount of 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: #soywax limited edition horror candles going up @scentedscreams! Follow us for all the latest news!!
Emotion: fear
Intensity score: | 0.396 |
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: @niceoneWern @Alotta_Pain the gleesome threesome
Intensity score: | 0.422 |
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: @cburt43 turn that frown upside down
Emotion: anger
Intensity score: | 0.125 |
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: Who actually chooses to drink sparkling water 🤔
This tweet contains emotions: | anticipation |
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: Ever been really lonely and your phone keeps blowing up, but you just can’t pick it up and respond to people? #anxiety #recluse #issues
Emotion: fear
Intensity class: | 3: high amount of 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: Well that was exhilarating. I didn't know you could have goosebumps for 2 hrs 5m straight.
Emotion: joy
Intensity class: | 2: moderate amount of joy can be inferred |
Task: Determine the valence intensity of the tweeter's mental state on a scale of 0 (most negative) to 1 (most positive). | Tweet: @homoaesthetics YESYESYES like jd is the closest cahracter that is similar to blaine!! the optimism and ability to crack tough characters
Intensity score: | 0.683 |
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: The object of literature is to make man a wiser and happier being. The poet makes us happy because he tells us how we may become so.
This tweet contains emotions: | joy, optimism, trust |
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: Don't be disheartened if you didn't get the cards you wanted, it's not the end of the world......E-Eh...? Y-You want me to cheer you up?
Emotion: sadness
Intensity class: | 1: low amount of sadness 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: 2 biggest fears: incurable STD's and pregnancy...I mean, they're basically the same thing anyway #forlife #annoying #irritation #weirdsmells
This tweet contains emotions: | anger, disgust, fear |
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: @saclivin @MrsCagg specific & intentional way. And part of that intention is to provoke conversation around systemic racism towards blacks.
Emotion: anger
Intensity score: | 0.583 |
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: Oh my. Watching #rage. It's been like, ages
This tweet contains emotions: | anger, joy |
Task: Determine the valence intensity of the tweeter's mental state on a scale of 0 (most negative) to 1 (most positive). | Tweet: Liam is too distant makes me mourn 😪
Intensity score: | 0.240 |
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: @zombieisIand yeah friends of minw have witnesse accidents and a road near me like??? cars hav like sunk?? but ih gosh be safe okay !!
Emotion: sadness
Intensity class: | 2: moderate amount of 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: #ArchangelSummit @sethgodin Anyone can be brave but you just have to last 5 mins longer than everyone else. #leadership
This tweet contains emotions: | anticipation, joy, optimism, trust |
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: She gave a playful wink, taking the goggles off her head, swinging them around her finger. 'I would never~' @VerminEngineer
Emotion: joy
Intensity score: | 0.534 |
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E). | Tweet: Glasgow Girls' is a real tonic @stratfordeast:an eclectic range of songs, barbed humour and eloquence in its fiery rage against injustice
Emotion: anger
Intensity score: | 0.583 |
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: @kevinmenzel annual reminder that i don't care and will cheerfully eat anything so labeled
This tweet contains emotions: | |
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: @Geminiak @LondonNPC you're welcome! #wordgeek \nAlso, good to put a face to the twitter feed, even if it was only a cheery hello! 😀
This tweet contains emotions: | anticipation, joy, optimism |
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 either look like a raging bitch, or I'm obnoxiously laughing at something not that funny. I don't think there's any middle ground.
This tweet contains emotions: | anger, disgust |
Task: Classify the tweet into one of four ordinal intensity levels, indicating the degree of emotion E experienced by the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: Your future is bright. #Remember
Emotion: joy
Intensity class: | 2: moderate amount of joy can be inferred |
Task: Measure the intensity of sentiment or valence in the tweet, assigning it a score between 0 (highly negative) and 1 (highly positive). | Tweet: All the bright places :(
Intensity score: | 0.565 |
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: #GetSmartWithARQ is a smart way to start investing and #whiteicenetwork is smart source 2 #start #skilled #manpower #recruitment for ur firm
Emotion: fear
Intensity score: | 0.169 |
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: @footballmcd agreed. Memphis looks lively also
Emotion: joy
Intensity score: | 0.395 |
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: An @amityaffliction kind of drive home from work today #dailyfeels
Emotion: fear
Intensity score: | 0.458 |
Task: Classify the tweet into one of four ordinal classes of intensity of emotion E that best represents the mental state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: Bilal Abood, #Iraq #immigrant who lives in Mesquite, Texas, was sentenced to 48 months in prison for lying to the Feds about .
Emotion: fear
Intensity class: | 0: no fear 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: Love this! Laughing while crying works too! #katherinemansfield #failure #dealingwithfailure
Intensity score: | 0.533 |
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: @LeKingCoq @MistaAggy @GiovanniiDC The way my blood is boiling, little bastards!
Emotion: anger
Intensity score: | 0.792 |
Task: Quantify the sentiment intensity or valence level of the tweet, giving it a score between 0 (highly negative) and 1 (highly positive). | Tweet: The feeling of taking someone's life is either scarring or exhilarating, but for people need to realize that we're going to die at some--
Intensity score: | 0.367 |
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: Ffs dreadful defending
Emotion: sadness
Intensity class: | 1: low amount of sadness can be inferred |
Task: Analyze the tweet's emotional connotations and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best portray the tweeter's mental state. | Tweet: @twojacksdetail @bluelivesmtr Very rare an officer just shoots without regard. They don't want that on their conscience. #incite #inflame
This tweet contains emotions: | anger, disgust |
Task: Place the tweet into a specific ordinal class, which captures the tweeter's mental state by considering different levels of positive and negative sentiment intensity. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred. | Tweet: Benefit out exhilaration called online backing off: JkUVmvQXY
Intensity class: | 1: slightly positive emotional state can be inferred |
Task: Calculate the intensity of emotion E in the tweet as a decimal value ranging from 0 to 1, with 0 representing the lowest intensity and 1 representing the highest intensity. | Tweet: @BroggersM19 @Calum250284 He had been retired 20 minutes ago by most blues on here 😊
Emotion: sadness
Intensity score: | 0.280 |
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: repentance, and trusting in Christ. It is lowly and painful, but it is also joyous, peaceful, and absolutely glorious. (2/2)
Emotion: joy
Intensity score: | 0.479 |
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: @Twitch how do I stop that horror movie themed commercial? Suddenly hearing screams is really not making me want to watch twitch.
Emotion: fear
Intensity class: | 2: moderate amount of 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: @pronounced_ing However I am pretty sure my over excitement did not help your bullet journal fright. 🙃
This tweet contains emotions: | anticipation, joy, optimism |
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: Fellaini has been playing ahead of this guy...just let that sink in
Intensity class: | 0: neutral or mixed emotional state can be inferred |
Task: Measure the intensity of sentiment or valence in the tweet, assigning it a score between 0 (highly negative) and 1 (highly positive). | Tweet: @ThatBritishDude no okay you don't not need to be going out of your way to make sure you are pleasing everyone do what makes you happy
Intensity score: | 0.548 |
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: Only God knows why things happen, sometimes it's just hard to understand. #sad #prayingforyou
Emotion: sadness
Intensity score: | 0.875 |
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: Riding at night has got to be one of the most exhilarating, refreshing things I have ever done.
This tweet contains emotions: | joy, optimism |
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: @fillegrossiere @PeasParsley @tombrodude bobs burgers is an animated show. Maybe Bob looks like him. They would cast him based on voice too
Emotion: joy
Intensity score: | 0.333 |