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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: @NessaMatthews he's perfect. But not even in that way where you sort of resent him or suspect that he leads a double life. Just perfect.
This tweet contains emotions: | joy, love, optimism |
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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: You have a #problem? Yes! Can you do #something about it? No! Than why
Emotion: fear
Intensity class: | 0: no fear can be inferred |
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Your task is to measure the intensity of anger in the tweet: "@virginmedia I've been disconnected whilst on holiday ๐ค but I don't move house until the 1st October ๐ค". Rate it on a scale from 0 (least intense) to 1 (most intense). | 0.396 |
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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'm wearing yellow today to bring a little sunshine to this gloomy day #yourewelcome
Emotion: sadness
Intensity class: | 0: no sadness can be inferred |
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Analyze the tweet "@Mysteri759 @Ren102e906 @slb42jcb @swoozyqyah Well, I'm too old, and too stubborn about facts & history to be discouraged." to classify the intensity of the emotion sadness. Your options are: 0: no sadness can be inferred, 1: low amount of sadness can be inferred, 2: moderate amount of sadness can be inferred, 3: high amount of sadness can be inferred. | 1: low amount of sadness can be inferred |
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Determine how strongly fear is expressed in the following tweet. Use the scale: 0: no fear can be inferred, 1: low amount of fear can be inferred, 2: moderate amount of fear can be inferred, 3: high amount of fear can be inferred.
Tweet: @TJ_FASHO lmao clown my own hair I'm going to dread lmao | 0: no fear can be inferred |
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Read the tweet "@kcbbcxo don't get discouraged! it's early on & it can get overwhelming. keep reading & use cue cards ๐ it'll get better!!" and determine the level of fear present. Select from these options: 0: no fear can be inferred, 1: low amount of fear can be inferred, 2: moderate amount of fear can be inferred, 3: high amount of fear can be inferred. | 0: no fear can be inferred |
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Please analyze the tweet "@Montel_Williams If this ban goes through, it will harm so many people, disabled veterans, people who have #chronicpain, #anxiety #iamkratom" and classify its emotional content. Choose from the following emotions: anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust. If no emotions are detected, respond with "neutral or no emotion". | anger, fear, sadness |
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Assess the level of joy present in the following tweet: "#happiness #recipe: an open mind, #laughter, a kind #heart & #optimism". Provide a real number between 0 and 1, with 0 representing the least intensity and 1 representing the highest intensity. | 0.833 |
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Given the tweet "#smackdev #ptp #start oh yeah!", identify any present emotions from this list: anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust. If none are present, answer "neutral or no emotion". | joy, optimism |
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Given the tweet "#Muslims are the principle victims of #terrorism. More Muslims are dying at the hands of these #terrorists than anyone else. #YounusAlGohar" and the emotion fear, how intense is this emotion? Assign a numerical value between 0 and 1 to represent the intensity level. | 0.583 |
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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: James: no 500k, no 50k, no 25k, no 10k. You fucked up. #bb18 #bitter #shouldofVotedforNicole
Emotion: anger
Intensity score: | 0.708 |
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Read the tweet "@JaredLeto Jared + #snap? ๐" and determine the level of anger present. Select from these options: 0: no anger can be inferred, 1: low amount of anger can be inferred, 2: moderate amount of anger can be inferred, 3: high amount of anger can be inferred. | 0: no anger can be inferred |
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For the tweet "im thoroughly in love w zen and jumin and i dont think id even have the patience for either of them irl im old and weary", assess the intensity of the emotion sadness. Choose one of the following: 0: no sadness can be inferred, 1: low amount of sadness can be inferred, 2: moderate amount of sadness can be inferred, 3: high amount of sadness can be inferred. | 1: low amount of sadness can be inferred |
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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: @beingbrilliant @johnmurrays you're welcome. It's genuinely made me give my head a wobble and realise what's important in life. #smiling
Emotion: joy
Intensity score: | 0.625 |
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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: @localblactivist I'm always a little bit weary of speaking up because 1. I don't want to hijack the convo - as an LGBT person, I've seen
Emotion: sadness
Intensity score: | 0.438 |
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Task: Assess the emotional content of the tweet and classify it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best represent the tweeter's mental state.
Tweet: It's been a week of awful connectivity with @TMobile no service or only 4G is not what Im paying for. #unhappy #poorservice
This tweet contains emotions: | anger, disgust, sadness |
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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: Quote_Soup: Be happy not because everything is good, but because you can see the good side of everything. #optimism
This tweet contains emotions: | joy, optimism |
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Based on the given tweet, determine the level of joy the author is experiencing. Choose from the following options: 0: no joy can be inferred, 1: low amount of joy can be inferred, 2: moderate amount of joy can be inferred, 3: high amount of joy can be inferred.
Tweet: It's all about #redwine and | 0: no joy can be inferred |
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Task: Classify the tweet into one of four ordinal classes of intensity of emotion E that best represents the mental state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.
Tweet: I swear if @devincameron23 blocks me I'm going to hit her back #revenge
Emotion: anger
Intensity class: | 3: high amount of anger can be inferred |
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Assess the emotional intensity of joy in the following tweet: "@deadlyjokester *she let out a playful gasp and slowly wrapped her arms around his neck, kissing him back*". Answer with a number between 0 (least intense) and 1 (most intense). | 0.620 |
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Assess the sentiment intensity of the tweet "Hey u never know, Channel 4's version of #GBBO might actually be quite good. A few adverts aren't the end of the world. #optimism" based on the mood of the author. Provide a rating from 0 to 1, where 0 signifies extremely negative and 1 signifies extremely positive. | 0.641 |
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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: Proverbs 27:9 Ointment and perfume rejoice the heart: so doth the sweetness of a man's friend by hearty counsel.\n#TruthfmDawnBreak
Emotion: joy
Intensity class: | 2: moderate amount of joy can be inferred |
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Analyze the tweet "@NM_NickNocturne Incentivise people to roam the Internet being morally offended, as if they didn't do it enough already." and indicate which emotions from the list (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) are expressed. If no emotions are found, answer with "neutral or no emotion". | anger, disgust, sadness |
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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: @BBCPolitics @BBCNews I'd rather leave my child with @BorisJohnson
Emotion: fear
Intensity class: | 0: no fear can be inferred |
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Assess the level of fear present in the following tweet: "watching my first Cage of Death and my word this is tremendous". Provide a real number between 0 and 1, with 0 representing the least intensity and 1 representing the highest intensity. | 0.562 |
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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: @maggyvaneijk Old age?! No hope for the rest of us. Destined to become deatheaters by 50
Emotion: fear
Intensity class: | 0: no fear can be inferred |
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Review the tweet "@PixelMonsterYT @TeamGE0 @IZEDEPTIC @ztumtum @CrimtideTV @LtGrandslam @Slinkercorn Bahahahaha Dean looks hilarious and damn I got fat" and assign it to one of the emotional state categories. The categories are: 3: very positive emotional state can be inferred, 2: moderately positive emotional state can be inferred, 1: slightly positive emotional state can be inferred, 0: neutral or mixed emotional state can be inferred, -1: slightly negative emotional state can be inferred, -2: moderately negative emotional state can be inferred, -3: very negative emotional state can be inferred. | 0: neutral or mixed emotional state can be inferred |
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Please analyze the tweet "Panda eyed jaunty after watching jaws until late!" and classify its emotional content. Choose from the following emotions: anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust. If no emotions are detected, respond with "neutral or no emotion". | joy |
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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: The little sniffle at the end of the song gets me every time.
This tweet contains emotions: | joy, sadness |
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Given the emotion joy and the tweet "@MillieetylerX I thought everyday was a glee day??", classify the intensity of the emotion displayed in the tweet. The classification options are: 0: no joy can be inferred, 1: low amount of joy can be inferred, 2: moderate amount of joy can be inferred, 3: high amount of joy can be inferred. | 0: no joy can be inferred |
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Let's gauge the sentiment intensity of the tweet "@ctp It's daunting trying to follow Swift news/trends, and facing mind-shattering patterns/terms left and right. I'm trying to adopt gently.". Assign a real number within the range of 0 to 1, with 0 representing highly negative and 1 representing highly positive. | 0.431 |
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Please analyze the tweet "@katethecursed @shannonrdk LOL this day is too gloomy for being people, should've canceled and stayed in bed" and classify its emotional content. Choose from the following emotions: anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust. If no emotions are detected, respond with "neutral or no emotion". | disgust, fear, joy, sadness |
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Please determine the intensity of the emotion anger in the tweet "@Sirenja_ @JaxOfBo (like, hope i didn't offend with my commentary - it wasn't what I was intending!)". Provide a score between 0 and 1, where 0 means very low intensity and 1 means very high intensity. | 0.500 |
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For the tweet "@realDonaldTrump She blamed Benghazi on a YouTube video. She blamed emails on #ColinPowell. Now she blames #terrorism on you. #weakHillary", classify the emotional tone using the following list: anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust. If no emotion is discernible, state "neutral or no emotion". | anger, disgust, fear, sadness |
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Determine how strongly fear is expressed in the following tweet. Use the scale: 0: no fear can be inferred, 1: low amount of fear can be inferred, 2: moderate amount of fear can be inferred, 3: high amount of fear can be inferred.
Tweet: Americans as a whole are, for the most part, feeling borderline despair at the very least. Looking at a situation out of control. | 0: no fear can be inferred |
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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: First day of fall quarter tomorrow. ๐ฐ #excited #anxious #blargh
Emotion: fear
Intensity class: | 0: no fear can be inferred |
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Analyze the tweet "@Chic_Happens_ @Sean_Okeeffe1 @royalmusing I dread the comparisons to Queen Mรกxima. Guarantee I will lose followers when that happens." and quantify the intensity of the emotion fear. Use a scale from 0 to 1, with 1 representing the highest intensity. | 0.646 |
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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: Fucking hell. Rush for the damn train also no use. Fucking 4min wait. Still sweating. #smrtruinslives
This tweet contains emotions: | anger, disgust |
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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: @Tomstarling86 He didn't have many chances to show what he can do but looked lively and had a good shot tipped over the bar before the end.
Emotion: joy
Intensity score: | 0.360 |
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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 emotional state can be inferred. 2: moderately positive emotional state can be inferred. 1: slightly positive emotional state can be inferred. 0: neutral or mixed emotional state can be inferred. -1: slightly negative emotional state can be inferred. -2: moderately negative emotional state can be inferred. -3: very negative emotional state can be inferred.
Tweet: @OpentheDoorRadi thanks for playing Crock Pot Going #radio #blog #blues #music #indiemusic
Intensity class: | 3: very positive emotional state can be inferred |
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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: @p_dortch7 I make sacrifices to make you happy
This tweet contains emotions: | joy, optimism |
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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: haww I think Nawaz should have spoken about Indian funding to BLA in Balochistan, Kulbhoshan Yadhav and how India used TTP for terror!
Emotion: fear
Intensity class: | 0: no fear can be inferred |
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Determine which emotions are present in the tweet "#ThisIsUs has messed with my mind & now I'm anticipating the next episode with #apprehension & ! #isthereahelplineforthis". Choose from anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust. If no emotions are evident, state "neutral or no emotion". | anticipation, fear |
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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: Virtually every statement by other countries at UN has referred to #terror as main threat to peace, #Pak still in denial: MEA.
This tweet contains emotions: | disgust, fear |
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Your task is to measure the intensity of anger in the tweet: "โ Self-hatred gives rise to fury, fury to the desire for self-change.". Rate it on a scale from 0 (least intense) to 1 (most intense). | 0.458 |
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Assess the emotional intensity of anger in the following tweet: "2 biggest fears: incurable STD's and pregnancy...I mean, they're basically the same thing anyway #forlife #annoying #weirdsmells". Answer with a number between 0 (least intense) and 1 (most intense). | 0.417 |
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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've seen the elder watching me during my community hours and i honestly don't have an idea about what my assignment will be.
Emotion: fear
Intensity class: | 0: no fear can be inferred |
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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 emotional state can be inferred. 2: moderately positive emotional state can be inferred. 1: slightly positive emotional state can be inferred. 0: neutral or mixed emotional state can be inferred. -1: slightly negative emotional state can be inferred. -2: moderately negative emotional state can be inferred. -3: very negative emotional state can be inferred.
Tweet: Early morning cheerfulness can be extremely obnoxious #ALDUB62ndWeeksary
Intensity class: | 0: neutral or mixed emotional state can be inferred |
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Task: Gauge the intensity of sentiment or valence in the tweet, indicating a numerical value between 0 (extremely negative) and 1 (extremely positive).
Tweet: @KWAYNTjoia it's exhilarating
Intensity score: | 0.589 |
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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: Like hello? I am your first born you must always laugh at my jokes. #offended
Emotion: anger
Intensity class: | 2: moderate amount of anger can be inferred |
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For the tweet "Watch this amazing live.ly broadcast by @swagrman_fan #musically", classify the emotional tone using the following list: anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust. If no emotion is discernible, state "neutral or no emotion". | anticipation, joy |
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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: @CUTEFUNNYANIMAL @luvcaps19 My sister's dog does this. I think it's because she knows it'll provoke a reaction
Emotion: anger
Intensity class: | 0: no anger can be inferred |
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Analyze the tweet "@shopgreenwich #ldf16 what shall we do this weekend? #spraypainting in #greenwichmarket with @SNUB23 #core246 #lilylou #fret & #benoakley" and quantify the intensity of the emotion anger. Use a scale from 0 to 1, with 1 representing the highest intensity. | 0.271 |
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Determine the emotional tone of the following tweet: "I have learned over the years that when one's mind is made up, this diminishes fear. โRosa Parks #quotes #motivation". Use the provided emotions: anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust. Respond with the emotions you identify or "neutral or no emotion". | optimism, trust |
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Task: Assess the sentiment intensity or valence level of the tweet, ranging from 0 (extremely negative) to 1 (extremely positive).
Tweet: TheNiceBot: IndyMN I thought the holidays could not get any more cheerful, and then I met you. #TheNiceBot #ุงูุฎูุฌู
Intensity score: | 0.600 |
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Assess the valence intensity of the tweeter's emotional state given the tweet: "Thank you @twitter for the balloons today. #goodday #48". Provide a numerical score ranging from 0 to 1, where 1 signifies highly positive and 0 indicates highly negative. | 0.786 |
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Assess the emotional intensity of sadness in the following tweet: "@kikibug13 Don't look. You'll only be very, very unhappy. \n\n(NNGH. I got the email notif THANK YOU.)". Answer with a number between 0 (least intense) and 1 (most intense). | 0.438 |
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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: @Jen_ny69 People will always get offended everyone's situation is different! Just because we have kids doesn't mean we have to settle
This tweet contains emotions: | anger, disgust, sadness |
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Examine the tweet "6 might be a serious number, but 10 sounds better. Wild card race!!" and determine which of these emotions are present: anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust. If there are no identifiable emotions, reply with "neutral or no emotion". | anticipation |
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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: @p4pictures it would be great but what if the card crashes ๐ฑ. It's happened to me twice
This tweet contains emotions: | fear, sadness |
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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: @Dak2future decorations are up all over Jersey already
Emotion: anger
Intensity class: | 0: no anger can be inferred |
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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: @LazyBoiSam blues... blues? ๐ค
This tweet contains emotions: | neutral or no emotion |
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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: @marksandspencer Where has your 50% grapefruit squash gone,not been able to get for weeks #unhappy
Emotion: sadness
Intensity score: | 0.562 |
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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: I would like to congratulate the people of Saudi Arabia a happy and a joyous national day. May you all have a great time! #ุงูููู
_ุงููุทูู
Emotion: joy
Intensity score: | 0.771 |
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Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E).
Tweet: I wish harry would start tweeting people again
Emotion: fear
Intensity score: | 0.195 |
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Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E).
Tweet: induction day tomorrow for pizza express
Emotion: fear
Intensity score: | 0.275 |
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Please analyze the tweet "@typicalmoony Yes Lia!! Join the dark side!!" and classify its emotional content. Choose from the following emotions: anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust. If no emotions are detected, respond with "neutral or no emotion". | joy, trust |
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Please analyze the tweet "Howard Webb always held up as knowing the answers. No red. Sutton and Craigan raging! Hahaha" and classify its emotional content. Choose from the following emotions: anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust. If no emotions are detected, respond with "neutral or no emotion". | anger, joy |
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Consider the emotion joy and the tweet "@johnwintertweet dudes who wanna play some bass but not buy a bass (me) rejoice". Evaluate the intensity of this emotion in the tweet, assigning a value between 0 (least intense) and 1 (most intense). | 0.308 |
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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: When you've still got a whole season of Wentworth to watch and a stupid cunt in work ruins it for us ๐ญ๐ญ @__KirstyGA #oldcunt
Emotion: anger
Intensity class: | 3: high amount of anger can be inferred |
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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: @iTriborg โ make him feel vigorous. 'Fine. You can kill me now.' Said Hestia with a display of only despair rather than her joyful โ
This tweet contains emotions: | anger, disgust, sadness |
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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: One more step in long work #visa process is over. Relief. Onto next step. #expat
This tweet contains emotions: | joy, optimism |
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Based on the given tweet, determine the level of joy the author is experiencing. Choose from the following options: 0: no joy can be inferred, 1: low amount of joy can be inferred, 2: moderate amount of joy can be inferred, 3: high amount of joy can be inferred.
Tweet: I'm still laughing 'Bitch took my pillow' line #kurt | 2: moderate amount of joy can be inferred |
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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: Nice to see Balotelli back to his best, good player.. Just lost his way a bit!
Emotion: sadness
Intensity score: | 0.167 |
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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: Job interview tomorrow ๐ #bright side
Emotion: joy
Intensity score: | 0.640 |
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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: That feel when you travel 700 miles to pick up a form that arrives in the post two days after you leave.
This tweet contains emotions: | anger, disgust, joy |
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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: Good morning lovely people. Not gonna lie I've woken up feeling pretty glum.
This tweet contains emotions: | joy, sadness |
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Analyze the tweet "Sister: (Canadian player does something shady.) Jonathan Toews is frowning and he doesn't know why. #WorldCupOfHockey" and quantify the intensity of the emotion sadness. Use a scale from 0 to 1, with 1 representing the highest intensity. | 0.404 |
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Using the tweet "This week's Massacre Theatre pert by @LarsenOnFilm is the first one I can think of that requires subtitles.", identify any emotions from the list: anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust. If none apply, answer "neutral or no emotion". | anticipation, trust |
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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 emotional state can be inferred. 2: moderately positive emotional state can be inferred. 1: slightly positive emotional state can be inferred. 0: neutral or mixed emotional state can be inferred. -1: slightly negative emotional state can be inferred. -2: moderately negative emotional state can be inferred. -3: very negative emotional state can be inferred.
Tweet: @SteveBryantArt I was pretty sure it was a Golden Ticket. Get a tour. Make a mistake. Something horrific will happen to you. Good day sir.
Intensity class: | 0: neutral or mixed emotional state can be inferred |
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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: @hotpatooties more like quickie divorce
Emotion: fear
Intensity class: | 0: no fear can be inferred |
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Examine the tweet "Try to find the good in the negative. The negative can turn out to be good.\n #anxietyrelief #openminded" and determine which of these emotions are present: anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust. If there are no identifiable emotions, reply with "neutral or no emotion". | optimism |
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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: @buzzlightbeard2 If you don't love yourself... Honesty is the best policy
This tweet contains emotions: | anticipation, optimism, trust |
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Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E).
Tweet: I wish the next madden has a story mode too. Just like Fifa 17 #madden
Emotion: anger
Intensity score: | 0.312 |
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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 was so shy freshman year this guy introduced himself to me by asking if I spoke any English
Emotion: fear
Intensity class: | 0: no fear can be inferred |
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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: @HillaryClinton Americans for HRC! Now maybe, as you see the world getting rid of terror to save their countries you'll get the DEMS out.
This tweet contains emotions: | anticipation, joy, optimism |
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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: Sky news still pushing the Brexit gloom line, managing to ignore the fact it's simply not happening. 'But in the future.....'
This tweet contains emotions: | disgust |
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Your task is to measure the intensity of joy in the tweet: "Check out this #film Robocoq 301 #animated #shortfilms". Rate it on a scale from 0 (least intense) to 1 (most intense). | 0.440 |
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Evaluate the tweet for the intensity of the emotion fear. The categories are as follows: 0: no fear can be inferred, 1: low amount of fear can be inferred, 2: moderate amount of fear can be inferred, 3: high amount of fear can be inferred.
Tweet: A country that gave safe house to #Osama Bin #Laden is dangerous if not contained. #Pakistan is a #terror heaven, declare so @BanKimoon_amdg | 2: moderate amount of fear can be inferred |
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For the tweet "@MrsCassonC @15_jordyn WAS THERE A CLOWN IN YOUR NEIGHBORHOOD? #nightmare #creepy #EnoughIsEnough", assess the intensity of the emotion fear. Choose one of the following: 0: no fear can be inferred, 1: low amount of fear can be inferred, 2: moderate amount of fear can be inferred, 3: high amount of fear can be inferred. | 3: high amount of fear can be inferred |
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Task: Assess the sentiment intensity or valence level of the tweet, ranging from 0 (extremely negative) to 1 (extremely positive).
Tweet: @ADenkyirah Happy birthday! Hope you have a wonderful day filled with lots of joy and laughter <3 (despite tumblr being a jerk- once again)
Intensity score: | 0.850 |
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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: Let us not burden our remembrances with a heaviness that's gone.\n- William Shakespeare (1564-1616)\n#forge ahead.
Emotion: sadness
Intensity class: | 2: moderate amount of sadness can be inferred |
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Let's gauge the sentiment intensity of the tweet "Retweeted GunnySmith93 (@Stephen21Smith):\n\nDays like today I am happy to be alive! #blessed #rejoice". Assign a real number within the range of 0 to 1, with 0 representing highly negative and 1 representing highly positive. | 0.897 |
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Assess the emotional intensity of joy in the following tweet: "Lets get this Astros/A's game going already! We're going to need all 5 of you in attendance to cheer the A's to victory!". Answer with a number between 0 (least intense) and 1 (most intense). | 0.625 |
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Assess the level of anger present in the following tweet: "im 16 if you want to see my dick snap/kik me at hiya2247 ๐ #kik #kikme #snapchat #snap #snapme #horny #porn #naked #young". Provide a real number between 0 and 1, with 0 representing the least intensity and 1 representing the highest intensity. | 0.375 |
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Analyze the tweet "I think they may be #offended" and quantify the intensity of the emotion anger. Use a scale from 0 to 1, with 1 representing the highest intensity. | 0.500 |
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Assess the level of the emotion joy in the tweet provided. Use the following categories: 0: no joy can be inferred, 1: low amount of joy can be inferred, 2: moderate amount of joy can be inferred, 3: high amount of joy can be inferred.
Tweet: I'm still laughing 'Bitch took my pillow' line #kurt | 2: moderate amount of joy can be inferred |
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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: @TheRevAl please tell us why 'protesting' injustice requires #burning #beating and #looting terrible optics #toussaintromain is true leader!
This tweet contains emotions: | anger, fear |
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Based on the emotional content of the tweet provided, classify it into one of these categories: 3: very positive emotional state can be inferred, 2: moderately positive emotional state can be inferred, 1: slightly positive emotional state can be inferred, 0: neutral or mixed emotional state can be inferred, -1: slightly negative emotional state can be inferred, -2: moderately negative emotional state can be inferred, -3: very negative emotional state can be inferred. Here is the tweet: @m_warner21 Yikes. The wrath of Maddie... | -1: slightly negative emotional state can be inferred |