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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: Punchline king is back! @Paedeezy π₯π₯π₯π₯π₯π₯π₯π―π―π― #bright city lights
Emotion: joy
Intensity score:
|
0.542
|
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: @philjame5 @spoke_bros wow! that looks bright
Emotion: joy
Intensity class:
|
1: low amount of joy can be inferred
|
Task: Measure the level of emotion E in the tweet using a real-valued score between 0 and 1, where 0 represents the lowest intensity and 1 represents the highest intensity.
|
Tweet: Texans played horrible. Bad play calling, bad protection of the ball, bad coaching, bad defense, bad overall performance. #Texans
Emotion: fear
Intensity score:
|
0.375
|
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 wanna go to blithe and read w the goats :((
Emotion: joy
Intensity class:
|
0: no joy can be inferred
|
Task: Assess the emotional content of the tweet and classify it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best represent the tweeter's mental state.
|
Tweet: @EASPORTSFIFA EA sports technical support team really suprised me π SUPRISED ME AT HOW SHIT THEY WERE
This tweet contains emotions:
|
anger, disgust, surprise
|
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: Fingers crossed I can finish all my work early enough this Friday in time to catch @Raury at LIB π¦ #timetogrind
This tweet contains emotions:
|
anticipation, 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: Body is sleepy but the mind is active. So sad... Have to get ready for work in 30 minutes. Damn!
Emotion: fear
Intensity score:
|
0.604
|
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: Metal keeps you young and spry and keeps your hair luxurious.\n\nYES\n\nSHUT UP AND LISTEN TO ME
Emotion: joy
Intensity score:
|
0.460
|
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: Puzzle investing opening portland feodal population is correlative straight a snorting infuriate: XLzjYhG
This tweet contains emotions:
|
anger, anticipation
|
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E).
|
Tweet: @The_East_End And the air raid alarm was actually false. There was no attack inbound at the time.
Emotion: fear
Intensity score:
|
0.438
|
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: @WYSdaily I'm confident they will NEVER experience our successes of last 50yrs. Best they can hope for is to be another Bournemouth
This tweet contains emotions:
|
joy, optimism
|
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: Am I the only one with parking sensors who still manages to reverse into things? #nightmare
Emotion: fear
Intensity score:
|
0.528
|
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: @LaneWoolery @FFKazman experience all plays a role in that, it's education and preparedness not fear
Emotion: fear
Intensity score:
|
0.396
|
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: Whatt a trailerrrr !!! @karanjohar @AnushkaSharma #RanbirKapoor #AishwaryaRaiBachchan i am COMPLETELY BLOWN !! #awestruck #longingformore
This tweet contains emotions:
|
anticipation, joy, optimism, surprise, trust
|
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: All I'm learning about at college atm is Sylvia Plath, Stalin's purges and natural disasters, gloomy af
Emotion: sadness
Intensity class:
|
3: high amount of sadness 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: You have a #problem? Yes! Can you do #something about it? No! Than why #worry
Emotion: fear
Intensity score:
|
0.250
|
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: 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: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E).
|
Tweet: I'm tired of everybody telling me to chill out and everythings ok. no the fuck its not. I'm tired of faking a a fucking smile
Emotion: joy
Intensity score:
|
0.042
|
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: You know you're in love when all you can do is smile whenever you talk about how he is to someone.
Intensity class:
|
1: slightly positive 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: Men in rage strike those that wish them best. #rage #emotions #negative #positive #wish #strike #martial #arts #control #believe #best #hope
Emotion: anger
Intensity class:
|
3: high amount of anger can be inferred
|
Task: Categorize the tweet based on the intensity of the specified emotion E, capturing the tweeter's mental state. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.
|
Tweet: I asked Jared to marry me and he said no.
Emotion: anger
Intensity class:
|
2: moderate amount of anger can be inferred
|
Task: Classify the tweet into one of four ordinal classes of intensity of emotion E that best represents the mental state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.
|
Tweet: @stephtikkanen oh so true, so true.
Emotion: fear
Intensity class:
|
0: no fear 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: My two older boys were elated, my toddler was terrified. I have pics of his poor little face peeping through the hole in the basket.
This tweet contains emotions:
|
fear, 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: Update: I have yet to hang out with @MisElizaJane, but I'm still hopeful! #optimism
Emotion: joy
Intensity class:
|
1: low 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: Lol little things like that make me so angry x
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: @_Mrs_Peel @lp_lisa @PaulRGoulden @LisaLuscious Might be the pout of a star baker tho !
This tweet contains emotions:
|
anticipation, joy
|
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: hitting your children as discipline because you're being quite a raging hypocrite if you're not.
This tweet contains emotions:
|
anger, disgust, pessimism, sadness
|
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: @JMRescue not brilliant lol! Hoping seeing my horse tomorrow will cheer me up π #equestrianhour
Emotion: joy
Intensity score:
|
0.385
|
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: @Lexual__ @jdspielman10 RIP to the 100s of black men,, women,CHILDREN killed in Chicago. Where is the outrage?
Emotion: anger
Intensity score:
|
0.562
|
Task: 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: @judahandthelion TONIGHT. Legit can't wait to rage π€π»π€π»π€π»π€π»π€π»π₯
Emotion: anger
Intensity score:
|
0.417
|
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: @jadelalaa_ hahaha and u da best bro ever luv u hearty hearts
Emotion: joy
Intensity class:
|
3: high 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: @LoisJoanneLane Wagging his tail at the praise, he paused, tilting his head as she took the frisbee from him, letting out a playful -
Emotion: joy
Intensity class:
|
2: moderate amount of 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: Currently unfollowing anything relating to disneyworld or Florida! #holidayblues #depressing #wantogoback ππ
Emotion: sadness
Intensity class:
|
3: high amount of 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: We're going to get City in the next round for a revenge.
This tweet contains emotions:
|
anger
|
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: @TrevorHMoore @paget_old In Scotland, the right-wingers are the most rabid anti-nationalists. Socialists are mostly in favour.
Emotion: anger
Intensity score:
|
0.604
|
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: @aIakazamjackass been better. It's really stupid don't worry
This tweet contains emotions:
|
disgust, 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: Ugh I want to punch a wall every time I have to use @windows 10. Literally the worst product ever made #windows10 #killme
Emotion: fear
Intensity class:
|
1: low amount of 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: #Hudcomedy #AdamRowe #insult Slutfaceshlongnugget
Emotion: anger
Intensity class:
|
2: moderate amount of anger can be inferred
|
Task: Assign a suitable level of intensity of emotion E to the tweet, representing the emotional state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.
|
Tweet: @JonathanHatfull Iβll look forward to it. Hoping for lots of stetson-tilting and rueful looks into whiskey glasses.
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: How do you ever stop being #afraid of someone that you live with
Emotion: fear
Intensity score:
|
0.771
|
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: It's always depressing to sort WordPress plugin recommendations not by 'best' but by 'least offensive in terms of premium features.'
This tweet contains emotions:
|
anger, disgust, 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: @comcast you charge 150 extra for sending someone out and your cable service still doesn't work. That's robbery. #cable #service
Intensity score:
|
0.200
|
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: Peter is aesthetically pleasing to look at
Emotion: joy
Intensity score:
|
0.583
|
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: @VosachResrus ^'ll just #wobble carry you #sink
Emotion: sadness
Intensity class:
|
0: no sadness 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: Late night #thoughts. Feeling .
This tweet contains emotions:
| |
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: @jimadair3 Guitar shop owners everywhere rejoice
Intensity class:
|
1: slightly positive emotional state 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: It's meant to be!! #happy #happy
This tweet contains emotions:
|
joy, love, optimism
|
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: @iStoleFreeHugs @stephlaris lol I'm happy with my negative, realistic ass self. Sorry to offend you
Emotion: anger
Intensity class:
|
1: low 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: me: tis a dreary day today\nfriend: he's a teenager not Shakespeare's reincarnation \n\nim such a dumbass lol
This tweet contains emotions:
|
anger, disgust, joy
|
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: Public products: high downhearted price tag consumer survey sum and substance: OVth
Emotion: sadness
Intensity class:
|
0: no sadness can be inferred
|
Task: Classify the mental state of the tweeter based on the tweet, determining if it is 'neutral or no emotion' or characterized by any of the provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).
|
Tweet: βDonβt burn out; keep yourselves fueled and aflame. Be alert servants of the Master, cheerfully expectant.' Romans 12:11-12
This tweet contains emotions:
|
joy, optimism, trust
|
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: gifs on iOS10 messaging app are hilarious.
Emotion: joy
Intensity score:
|
0.673
|
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: @charles_gaba No, I am probably the person most likely to completely understand how gobsmacked you were to learn how true that is. #sadly
Intensity score:
|
0.141
|
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 little nose irritation and a little more chills on my body. I'm so not into flu, into flu, into flu #FallSongs
Intensity class:
|
-2: moderately negative emotional state 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: Tweeting from the sporadic wifi on the tube #perilous
Emotion: fear
Intensity class:
|
0: no fear can be inferred
|
Task: Assess the sentiment intensity or valence level of the tweet, ranging from 0 (extremely negative) to 1 (extremely positive).
|
Tweet: Honestly, there are some awful people on the internet... smh...
Intensity score:
|
0.145
|
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: On bedrest since I got out of the hospital. U find in unopened beer.. what do I do. Pour that shit out! No alcohol at all for me #sober
This tweet contains emotions:
|
optimism, sadness
|
Task: Determine the dominant emotion in the tweet and classify it as either 'neutral or no emotion' or one of the eleven provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).
|
Tweet: @wahrbear @marinarchy @diam0ndsapph1re There is some hilarity in someone who is literally openly anti-science calling others anti-science.
This tweet contains emotions:
|
joy
|
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: Brendan Rodgers looks fuming π
Intensity class:
|
-2: moderately negative emotional state can be inferred
|
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 truly believe in my heart right now that Satan is rejoicing because we are all against one another
Intensity class:
|
0: neutral or mixed emotional state 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: Like he really just fucking asked me that.
Emotion: anger
Intensity class:
|
3: high amount of anger 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: @EE your website is making me feel violent rage and your upgrade options aren't helping either. #Aaaaarrrrgghhh #iwanttocancel
Emotion: anger
Intensity score:
|
0.934
|
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: schneiderlin taking his revenge for the 2 fouls
This tweet contains emotions:
|
anger
|
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: I would like to congratulate the people of Saudi Arabia a happy and a joyous national day. May you all have a great time! #Ψ§ΩΩΩΩ
_Ψ§ΩΩΨ·ΩΩ
Intensity class:
|
2: moderately 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: I'm so nervous
Emotion: fear
Intensity score:
|
0.854
|
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: @metalAndTheGeek @astoldbyfANGIRL SAME! I always say it was the best time of my life. I closed my store down and it was so depressing
Emotion: sadness
Intensity class:
|
3: high amount of sadness 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: Literally had a guy (a some-would-say-successful guy) tell me 'this ship will sail' kay guy, first, you're working with a sub, last, it sunk
Emotion: sadness
Intensity class:
|
1: low amount of sadness 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: Once I have sent a pitch to a brand I close all tabs relevant to them instantly. Thats the kind of detachment I create for myself. #serious
Emotion: sadness
Intensity class:
|
2: moderate amount of sadness can be inferred
|
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: @1barkcom Thank you for the #follow. Looking forward to your tweets as they look entertaining! #smile #socialmedia
Intensity class:
|
2: moderately positive emotional state 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: @MarianKeyes maybe he had constipation issues..? Not that I KNOW dates relieve such an affliction! No way jose!
This tweet contains emotions:
|
joy, pessimism
|
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: me: i've actually been doing pretty well! i'm learning to manage my depression and-\nlife: yeah that's over. that's cancelled.
Emotion: sadness
Intensity class:
|
2: moderate amount of sadness 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: @grahnort wonderful experience watching you yesterday at. @BBCLetItShine thankyou for the
Emotion: joy
Intensity score:
|
0.708
|
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: Celtic sure know how to send a wild shiver down your spine
This tweet contains emotions:
|
fear
|
Task: Measure the intensity of sentiment or valence in the tweet, assigning it a score between 0 (highly negative) and 1 (highly positive).
|
Tweet: I have no clue where my charger is... #lost
Intensity score:
|
0.243
|
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: Look at me. Made it through the day without a meltdown. #anxiety
Emotion: fear
Intensity class:
|
1: low amount of fear can be inferred
|
Task: Determine the dominant emotion in the tweet and classify it as either 'neutral or no emotion' or one of the eleven provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).
|
Tweet: I just got murdered in madden. π€
This tweet contains emotions:
| |
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: Stk is expensive but i'f rather take a bigger female there than tiff. You all see how slim she is and how she loves to eat.
Emotion: anger
Intensity class:
|
0: no anger can be inferred
|
Task: Assign a numerical value between 0 (least E) and 1 (most E) to represent the intensity of emotion E expressed in the tweet.
|
Tweet: Favourite quote of the year so far is by @ameliameech 'I swore at a parsnip' π #raging
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: interesting that we,an Authentic Afghan Restaurant,R getting calls from the media over resent tragedy that happened in NJ@latimes @NBCNews
Emotion: anger
Intensity score:
|
0.438
|
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: So I just opened This message Brooke sent me got me I am weak as the fuck π© she is a fucking bully for no reason ππππππ
Emotion: fear
Intensity class:
|
2: moderate 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: What terrible thing to see and have no vision-\n\nHelen Keller-\n\n-Begin with the end in mind-\n\nStephen Covey-\n\n #whereareugoing
Emotion: anger
Intensity class:
|
1: low amount of anger 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: I added Paul Walker on Xbox but he just spends all of his time on the dashboard. #dark #humor #funny
Emotion: sadness
Intensity score:
|
0.271
|
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: imagine if teppu got animated by madhouse tho >_<
Intensity class:
|
0: neutral or mixed 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: I can't believe this day hasn't been horrible BLESS
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: sorry Main twitter im in depress
Emotion: sadness
Intensity class:
|
3: high amount of sadness 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: @1ChiefsDan Is that pessimism or do you just want him to get another week of rest and healing?
Emotion: sadness
Intensity class:
|
0: no sadness 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: @Dolla_DeLotta They wanna bully the Inhuman.
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: @bt_uk broadband is shocking regretting signing up now #shouldofgonewithvirgin
This tweet contains emotions:
|
disgust, surprise
|
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: And with rich Fumes his sullen sences cheer'd.
Intensity class:
|
0: neutral or mixed 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: @reinervshunter you got thisπ #staystrong #yourebeautiful
This tweet contains emotions:
|
joy, love, optimism
|
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: Awe produces gratitude, gratitude instills joy, & the harvest of joy is contentment.' \n\nβ@PaulTripp #awe πππ
Emotion: fear
Intensity score:
|
0.167
|
Task: Determine the valence intensity of the tweeter's mental state on a scale of 0 (most negative) to 1 (most positive).
|
Tweet: @Lil_PowWow @jweiler0528 More fat = more buoyant. Day 1 water stuff
Intensity score:
|
0.518
|
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: | At home sick... πΌThe bluesπΌ won't cure it so I need ideas πΈπ | #sorethroat #sick #blues #music #fallweather #carletonuniversity #ottawa
This tweet contains emotions:
|
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: A guy was raging so hard during a rocket league game, when i beat him he started crying and i was laughing so hard lol
Emotion: anger
Intensity class:
|
0: no anger can be inferred
|
Task: Categorize the tweet based on the intensity of the specified emotion E, capturing the tweeter's mental state. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.
|
Tweet: @TrussElise Obama must be fuming.. lol
Emotion: anger
Intensity class:
|
2: moderate amount of anger 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: I'm not sure if burning and looting really can positively impact a community
Emotion: anger
Intensity score:
|
0.312
|
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: i cant live anymore my roblox got termianted :(((((((((((((((((((((((( #sad #killme #lol #robloxgamer
Emotion: sadness
Intensity class:
|
3: high amount of sadness 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: @Bungie spent over 2 fucking hours and still can't get that dam SIVA fragment on Fellwinters peak mountain
Emotion: anger
Intensity score:
|
0.812
|
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: @brendancoots where's your outrage that your party nominated a lying, corrupt person? And received donations from nations who support terror
Emotion: fear
Intensity score:
|
0.583
|
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: This is a joke @SomersetCCC #fuming
This tweet contains emotions:
|
anger, disgust
|
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