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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: AQW should've always stayed in the 08 art style, now it's just a competition to create more detailed art each time.
Emotion: sadness
Intensity class: | 0: no sadness can be inferred |
Task: Evaluate the tweet for emotional cues and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that indicate the tweeter's state of mind. | Tweet: @eileen_davidson on RHOBH, you just do not want to assume an affair while you were married so you criticize @LisaVanderpump! #awful
This tweet contains emotions: | anger, disgust |
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: Just popped a half bottle of 2014 @Bellawines #sparkling #gamaynoir from Westbank. Evenin', folks! \n#bcwinechat
Emotion: joy
Intensity score: | 0.620 |
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: I feel so blessed to work with the family that I nanny for ❤️ nothing but love & appreciation, makes me smile.
Emotion: joy
Intensity score: | 0.938 |
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: Watch this amazing live.ly broadcast by @mrgummyking #musically
This tweet contains emotions: | joy, love |
Task: Gauge the intensity of sentiment or valence in the tweet, indicating a numerical value between 0 (extremely negative) and 1 (extremely positive). | Tweet: Latest on new optimism on keeping #Raiders in #Oakland, live right now on @KCBSNews: @NFL meets here w/Lott & Schaaf to talk new stadium
Intensity score: | 0.677 |
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 2 teens sons just left in the car to get haircuts. I'm praying up a storm that they make it home safely!! #sad #TerenceCrutcher
This tweet contains emotions: | fear, sadness |
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: @everycolorbot more like every color looks the same #triggered #colorblind #offended
Emotion: anger
Intensity class: | 2: moderate 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: Accept the challenges so that you can feel the exhilaration of victory. George S. Patton #quote #yeg
Emotion: joy
Intensity score: | 0.440 |
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: Trying to think positive, and not let this situation discourage me ✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨
Emotion: sadness
Intensity class: | 1: low amount of sadness can be inferred |
Task: Determine the most suitable ordinal classification for the tweet, capturing the emotional state of the tweeter through a range of positive and negative sentiment intensity levels. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred. | Tweet: @JordySloan love that Jordy #revenge ⚽️
Intensity class: | 0: neutral or mixed 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 not afraid of clowns but I'm really hoping they don't make an appearance around my hometown.
Emotion: fear
Intensity score: | 0.600 |
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: @MrMalky @kwr66 How awful! Switched off!
Emotion: fear
Intensity score: | 0.667 |
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: @UKLittleKitchen Defo a hearty root veg gratin. Nice comfort food as Autumn kicks in
Emotion: joy
Intensity score: | 0.480 |
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: If my luck the rest of Fall goes anything like today, I think I'm going to like this season. #bestdayever #magic #work
This tweet contains emotions: | joy, 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: @FieldYates @MatthewBerryTMR @Stephania_ESPN @MikeClayNFL @FrankCaliendo goddamn...the 'celebrity' draft at the end was classic. #hilarious
Emotion: joy
Intensity class: | 2: moderate amount of joy can be inferred |
Task: Determine the sentiment intensity or valence score of the tweet, representing the tweeter's mental state on a continuum from 0 (highly negative) to 1 (highly positive). | Tweet: @glacierqxeen \n\n'Whoo, welcome~!' He greeted cheerfully.
Intensity score: | 0.719 |
Task: Gauge the level of intensity for emotion E in the tweet, assigning it a score between 0 and 1. A score of 0 indicates the lowest intensity, while a score of 1 indicates the highest intensity. | Tweet: i miss the guy who always make me sulk
Emotion: sadness
Intensity score: | 0.604 |
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: @Miami4Trump Yeah, but bad part is the #terrorism #terror Muslims won't be the ones leaving #ObamaLegacy #nationalsecurity #disaster #Obama
This tweet contains emotions: | anger, disgust, fear |
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 had Matty Dawson not scored there!!!!! #terrible
Emotion: fear
Intensity score: | 0.375 |
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'm just a fuming ball of anger today 🙃
This tweet contains emotions: | anger, disgust |
Task: Classify the tweet into one of four ordinal classes of intensity of emotion E that best represents the mental state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: 😳The intensity that @sydneyswans play at is extraordinary #relentless #AFLCatsSwans #AFLFinals 🏉👏🏿
Emotion: anger
Intensity class: | 0: no anger 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: ok, ok.. I know.. my last tweet was #terrible
Emotion: fear
Intensity class: | 0: no fear can be inferred |
Task: Analyze the tweet's sentiment and assign it to either 'neutral or no emotion' or one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust). | Tweet: What's a Kali's kitten? [She asked, a frown curling on her fair skinned forehead as he showed her the scar] A cat did - (@ScarredTiger)
This tweet contains emotions: | |
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: @iAmSJ I'm so mad for our clients I'm furious lmao
Intensity class: | -2: moderately negative 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: Wishing i was rich so i didnt have to get up this morning #poor #sleepy #restless #sad #needsmoresleep
Emotion: fear
Intensity score: | 0.469 |
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: Time for some despair #SDR3 #despair #fuckthisanime
This tweet contains emotions: | anger, sadness |
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: This world has some serious issues we should all go to therapy
Emotion: sadness
Intensity score: | 0.750 |
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: @_JuliaSteiner : YES ! Right ? I mean I wish you hadn't been discouraged to see #MikeandMolly because so many parallels really -
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: @gurrie_j thanks for making me super sad about Pizza. #freepizza
This tweet contains emotions: | joy, optimism, 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: And the weather so breezy, man why can't life always be this easy
Emotion: joy
Intensity score: | 0.562 |
Task: Categorize the tweet based on the intensity of the specified emotion E, capturing the tweeter's mental state. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: What I would give\nTo feel the sunlight on my face\nWhat I would give\nTo be lost in your embrace 🎧\n\n#Fallen
Emotion: sadness
Intensity class: | 2: moderate amount of sadness can be inferred |
Task: Assign the tweet to a specific ordinal class that corresponds to the tweeter's mental state, considering various levels of positive and negative sentiment intensity. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred. | Tweet: @RevTrevK @Wolfman93011 @Daraidernation @EROCKhd Take 2k out of it the numbers on madden are low and have dropped and people are unhappy
Intensity class: | -3: very negative emotional state 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: 😑😑😑<---- that moment you finish a Netflix series and have nothing else to watch. #depression
Emotion: sadness
Intensity class: | 3: high amount of 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: @RobdotThom @sulphurhoops in fact they need to start making all holidays! Maybe even e dry month pick a theme so we can have them all year
Emotion: fear
Intensity score: | 0.229 |
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: Onus is on #Pak to act against #terror groups which find all types of support for cross border terror: #MEA
This tweet contains emotions: | fear |
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: @xxnogard_G88 Welcome to the dark honey !
This tweet contains emotions: | |
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: Beginning the process to see if working is an option. #mentalhealth #complexptsd
Emotion: fear
Intensity class: | 1: low amount of fear 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: @comcast you charge 150 extra for sending someone out and your cable service still doesn't work. That's robbery. #cable #horrible #service
Emotion: fear
Intensity score: | 0.333 |
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: @UltimateBoxer My heart because you left me for so long again\n\n*slight pout but it turned to a smile*\n\nheheh just kidding, no I'm fine-
Emotion: sadness
Intensity class: | 0: no sadness 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: @jaybusbee Well, not Archie. No offense but he's kinda old.
This tweet contains emotions: | anger |
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: @GOT7Official @jrjyp happy birthday jin young!!!!!! #PrinceJinyoungDay #happyjinyoungday #got7 #happy #birthday
This tweet contains emotions: | joy, love, optimism |
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: #Terrorism can be destroyed easily if #wholeworld came together great strength..they could destroy this #fear from #humanity..
Emotion: fear
Intensity class: | 0: no fear 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: #Appreciate what you have & enjoy your life. \nUse your #smile 😃 to help others use theirs. ☺️
Emotion: joy
Intensity class: | 2: moderate 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: ♪OLD FISH #discourage
Emotion: sadness
Intensity score: | 0.656 |
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: Paul forever. Paul should have won! Paul played such a better game! #BB18
Emotion: anger
Intensity score: | 0.438 |
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: @_Hallospaceboy_ @DailyGrindhouse I respect when someone can give a second chance to a movie they aren't a fan of. Why #horror is diverse.
Emotion: fear
Intensity score: | 0.375 |
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E). | Tweet: You will never find someone who loved you like I did. And that my love, will be my revenge.
Emotion: anger
Intensity score: | 0.583 |
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: People always tell me that they don't expect me to have anxiety because I'm generally cheerful and don't act the way they expect me to.
Intensity class: | 0: neutral or mixed emotional state can be inferred |
Task: Classify the tweet into one of four ordinal intensity levels, indicating the degree of emotion E experienced by the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: @schokokitsune As much as I always eat....so no. -w- \n\nBut I shake all the time, so eeeeh. Maybe I should go see a doctor 'cause of it .w.
Emotion: fear
Intensity class: | 2: moderate amount of fear 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: @SEPTA 45 minutes late & counting! #horrible CTT Service sucks!
Emotion: fear
Intensity class: | 0: no fear can be inferred |
Task: Determine the appropriate intensity category of emotion E for the tweet, reflecting the emotional state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: life is hard., its harder if ur stupid #life #love #sadness #sadderness #moreofsad #howdoestears #whatislife
Emotion: sadness
Intensity class: | 3: high amount of sadness 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: i will never watch greys anatomy ever ever ever ever ever again if Shonda Rimes takes away another OG character☹️☹️☹️☹️☹️☹️☹️☹️☹️☹️
This tweet contains emotions: | anger, disgust, sadness |
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: I think I must scare my coworkers when I'm eating like a rabid animal on my breaks #srry
Emotion: fear
Intensity score: | 0.583 |
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: @rupindxr my heart actually sunk looooool I was so confused
Emotion: sadness
Intensity score: | 0.625 |
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: How could such a crooked,stuck up,delusional,dim& #dark hearted dud be surprised losing&prob also ppl won't let their crimes drop! #nwo imo
This tweet contains emotions: | anger, disgust, fear, sadness |
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: @p0stcap I've still been trying to sort through it all, but I suppose I also shouldn't have had such high expectations. #sadness
This tweet contains emotions: | pessimism, sadness |
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: Everyday gay panic is STUNNING: I drew 1 guy's att'n to it when he blocked up a toilet stall's cracks w/paper towels. TOTAL INCOMPREHENSION.
Emotion: fear
Intensity score: | 0.562 |
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: @TheRachelFisher i've seen a bunch of that on another twitter feed and I remember you had an opinion on it #shocking
Emotion: fear
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: @CrystiCaro yeah agree - I think it was a family member and they covered up #sad
Emotion: sadness
Intensity class: | 3: high amount of sadness can be inferred |
Task: Evaluate the strength of emotion E in the tweet, providing a real-valued score from 0 to 1. A score of 0 denotes the absence of the emotion, while a score of 1 indicates the highest degree of intensity. | Tweet: Knowing I have my hair to wash and dry is like knowing you had that English close reading in your school bag to do
Emotion: fear
Intensity score: | 0.553 |
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: @ankitaverma45 @honey5991 rejoicing over someone's sadness is bad but when #Karma is cencerned then definitely some people deserve it..
Emotion: joy
Intensity score: | 0.229 |
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: Hey folks sorry if anything offensive got posted on here yesterday my account got hacked. All fixed now though. I hope :-/ #angry #annoyed
Emotion: anger
Intensity score: | 0.479 |
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: The 2nd step to beating #anxiety or #depression is realising that it's not about waiting for ...., Take action yourself now.
Emotion: sadness
Intensity class: | 1: low amount of sadness 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: @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: Assign the tweet to a specific ordinal class that corresponds to the tweeter's mental state, considering various levels of positive and negative sentiment intensity. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred. | Tweet: Gas prices are hilarious. Cause they're simultaneously super subsidised and taxed
Intensity class: | 0: neutral or mixed emotional state 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: @Arsenal Giroud's beard is making me angry.
Emotion: anger
Intensity score: | 0.625 |
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: It's a gloomy ass day
Emotion: sadness
Intensity class: | 3: high amount of sadness 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: @SouthernRailUK delays from Streatham Cmn to Clap Junc & now train took 20 mins for 9 mins journey. Missed 2 trains to Reading #fuming
This tweet contains emotions: | anger |
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: Seeing an old coworker and his wife mourn the loss of their 23 year old daughter was one of the saddest things I've ever seen 😢
Emotion: sadness
Intensity score: | 0.833 |
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: And she got all angry telling me 'but what would be doing a 40 year old guy looking for a girl like you' and I felt #offended
Intensity class: | -3: very negative 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: @AlaskaGurus @adventuretweets agreed! 😍 an awe to meet such beautiful, powerful animals.
This tweet contains emotions: | joy, 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: I'm just doing what u should b doing just minding my business and grinding relentless @LITO615
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: @Girlandlurchers Yep, peeps on here always out to cheer others up! I'm fine, drooling at GBBO x
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: @BartholomewD It's -terrible-! We're going to the local fish/chip place in Kirribilli #terrible
Emotion: fear
Intensity score: | 0.667 |
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: @ArcadianLuthier -- taking out his feelings on Kei unfairly. His lips form a frown as he tries to walk away.
Intensity score: | 0.266 |
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: nooooo. Poor Blue Bell! not again.
Emotion: sadness
Intensity class: | 2: moderate 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: I hate that a black lady is painting herself white on the internet for laughs and likes... #BadForm #DidntLaugh
This tweet contains emotions: | anger, disgust, 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: Unbelievable takes 10 minutes to get through to @BarclaysUK then there's a fault and the call hangs up #fuming #treatcustomersfairly
Emotion: anger
Intensity score: | 0.792 |
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: @JohnRMoffitt This is the most grim piece of laughter I was stricken with all day.
Intensity score: | 0.844 |
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E). | Tweet: should I #start posting #photos?
Emotion: fear
Intensity score: | 0.146 |
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: @AldiToHarrods I'm still too nervous to try it. I need to man up and give it ago.
Emotion: fear
Intensity score: | 0.750 |
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: What we think, we become. -Buddha #recovery #addiction #sober #sobriety
This tweet contains emotions: | joy, optimism, trust |
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: Can't believe @haven ring my parents NOW when they go tomorrow to say no disabled washing facility for my wheelchair bound dad #shocking
This tweet contains emotions: | disgust, surprise |
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: @KseniaSolo hi little late to lost girl but think you awesome from South Afrikaans:-)
This tweet contains emotions: | joy, love, optimism |
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: why yall hyped abt that girl getting to hang out w JB, he clearly looks so unhappy and bored in the pics no offense LOL, plus he hates yall
This tweet contains emotions: | anger, disgust |
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E). | Tweet: @GCC_DiscGolf lost my xt nova around hole 8 or 9 #sadness
Emotion: sadness
Intensity score: | 0.708 |
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: @TheSandraGal Glad to see that you're having fun in the sun. Water sports are always fun, challenging, and exhilarating. #happiness #beauty
Intensity class: | 3: very positive emotional state 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: remember when glee did a take me or leave me cover but it was between two girls who werent even friends why did that do that
Emotion: joy
Intensity score: | 0.167 |
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: Each day is what you make of it! #goals #challenges #business #goals #success #photographer #photography #ThursdayThoughts
Emotion: joy
Intensity score: | 0.604 |
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: @alisontis otherwise you're committing a crime against your soul only sober ppl know what is good or bad for themselves
Emotion: sadness
Intensity score: | 0.438 |
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: Swear all of my guy friends are scaredy cats. You don't do horror movies. You don't do haunted houses. Wtf do you do then?
Emotion: fear
Intensity class: | 0: no fear can be inferred |
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: This whole #VanRE + extradition might turn into a Pandora's box. JT has no idea about that murky corrupt guanxi in China; Toad vs Dada ;-)
Intensity score: | 0.379 |
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'm getting use to not having a phone it's sad ..
Emotion: sadness
Intensity class: | 2: moderate amount of 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: @Myahrissavietta I'm cheery now 😘😉
This tweet contains emotions: | joy, love, optimism |
Task: Categorize the tweet's emotional expression, classifying it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that reflect the tweeter's state of mind. | Tweet: Tiller and breezy should do a collab album. Rapping and singing prolly be fire
This tweet contains emotions: | joy, love |
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'm just always too shy
Emotion: fear
Intensity class: | 1: low amount of fear 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: Now that I have my ex's number now its time to prank him. #revenge #prank #whatprankIshoulddo seriously what prank I should I do
Emotion: anger
Intensity score: | 0.500 |
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: @space_gayz high fantasy , i feel like you could make a melancholy college age slice of life thing work too
Emotion: sadness
Intensity class: | 0: no sadness 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: @Sargon_of_Akkad It'll be like burning rap albums; they'll have to buy it first, but gosh darn it, they have to get rid of it.
Emotion: anger
Intensity class: | 1: low amount of anger can be inferred |