instruction
stringclasses 50
values | input
stringlengths 32
202
| output
stringlengths 0
55
|
|---|---|---|
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: Shanghais chief distracting levity pampa - proper dingle carry away: uUDQujcia
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: @DeltaAssist Tried 2 get earlier flt 2day @BWI Turnd away bcuz it was 2 late Then agent let other pas on #silvereliteleftbehind
This tweet contains emotions: | disgust, sadness |
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: @humeraslam @MehrTarar @sherryrehman , yes, already he spoke so many lies with timid body language. Baluchistan could have been his own trap
This tweet contains emotions: | |
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: Mood : Happy 🙂 #blessing
This tweet contains emotions: | joy, love, optimism |
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: Omg. You've got to watch the new series 'This is Us'.....wow. Best tv show I've seen in a long time.\n #tears #moretears
This tweet contains emotions: | joy, love |
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: @mysarazaman Ya it makes me be more selfish and disheartened
Emotion: sadness
Intensity score: | 0.600 |
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: Well this is flipping great! Flipping standstill on the freeway! #stepofftheledge #youvegottobekiddingme
This tweet contains emotions: | anger, joy |
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: Marcus Roho is dreadful
Emotion: fear
Intensity score: | 0.458 |
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: #haikuchallenge #haiku\n\nThe crisp autumn air\nMy freedom purchased through death\nNo one will mourn me
This tweet contains emotions: | pessimism, sadness |
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: Why the FUCK have i just saw a Game of Thrones spoiler on snapchat? SOME OF US HAVENT SAW IT YET 🖕🏻🖕🏻🖕🏻🖕🏻🖕🏻 #arsehole
Emotion: sadness
Intensity class: | 1: low 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: Houston might lose a coach tomorrow or by midnight. #yikes #offense?
Emotion: anger
Intensity score: | 0.271 |
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: no offense but could troye start dming people so i can feel like less of an idiot when i dm him thanks
Emotion: anger
Intensity class: | 0: no anger can be inferred |
Task: Estimate the strength of emotion E in the tweet by assigning it a real-valued score between 0 and 1, where 0 signifies the least intensity and 1 signifies the greatest intensity. | Tweet: @620wtmj Seriously @620wtmj !? This is news to you?!? #sad \n\nWhy not focus on important issues??
Emotion: sadness
Intensity score: | 0.700 |
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: and claimed that all of the same things could scare us\nbut we were tough because of ancestry
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: I don't know what's worse, the new Pizza Hut commercials or the pizza that Pizza Hut makes.
This tweet contains emotions: | anger, disgust, pessimism |
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: @kerophibian depressing
Emotion: sadness
Intensity score: | 0.729 |
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: Corbyn loses and I walk up to a crying Corbyn supporter and whisper\n\n'Don't mourn. Organise'\n\nAnd laugh and laugh
This tweet contains emotions: | joy, optimism, 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: Post TRNSMT blues
Intensity score: | 0.400 |
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: US lady in foyer - 'Am I not #afraid to be tweeting in #Moscow?' Fortified by d good #Lord & #JD I reply 'I fear no Russian. 'cept my #wife😅
Emotion: fear
Intensity class: | 0: no fear 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: Sickness bug!
Emotion: fear
Intensity score: | 0.500 |
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: There goes the butterflies in my stomach. #anxietyproblems
This tweet contains emotions: | fear, sadness |
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: @JonnyDunn93 and Gerrard was awful then
This tweet contains emotions: | anger, disgust |
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: @1720maryknoll I was #fuming Kenny.
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: @itsyourgirl_Z happy birthday :) have a blessed day love from Toronto :) #bday
Emotion: joy
Intensity score: | 0.868 |
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!!
This tweet contains emotions: | love |
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: @KatieBurnett ha freshers blues would love to re do all again ... ha nice tshirt .. vote for Pedro
Emotion: sadness
Intensity score: | 0.167 |
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E). | Tweet: dammit @TMobile whays going on!!! 😤😤😤😤 lol #smh #mobilefails
Emotion: anger
Intensity score: | 0.792 |
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: @jamiesmart Huh! It's always my fault isn't it >:( #sulk
Intensity class: | -2: moderately negative 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: procrasting is fun until im an hour away from the time its due and i still havent finished so i have a panic attack
Emotion: fear
Intensity score: | 0.920 |
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: Eve, Izzy, and Paige cheerfully sing songs together.
This tweet contains emotions: | joy, love, optimism |
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: But right now I'm feeling pretty desolate.
Emotion: sadness
Intensity score: | 0.833 |
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: It’s lack of #faith that makes #people #afraid of #meeting #challenges …\n\n#MuhammadAli
Emotion: anger
Intensity score: | 0.242 |
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: “When we give cheerfully and accept gratefully, everyone is blessed.”―Maya Angelou
Intensity score: | 0.683 |
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: I'm scared that my coworkers are going to submit me to one of those 'wardrobe makeover' shows. #fashion
This tweet contains emotions: | fear, pessimism |
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E). | Tweet: @bt_uk why does tracking show my equipment delivered, when it wasn't? Why is my service suddenly delayed? We've already 3 weeks. #fuming
Emotion: anger
Intensity score: | 0.875 |
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: It's not that the man did not know how to juggle, he just didn't have the balls to do it. \n #funny #pun #punny #lol
Emotion: joy
Intensity score: | 0.604 |
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 listening to @ScottFoxonair & @KatCallaghan @Z1035Toronto podcasts!! Can you guys please move to #yvr ? #hilarious #missyou
Emotion: joy
Intensity class: | 3: high amount of joy 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: At a groovy restaurant. Got a cheeseburger and fries. I don't discriminate. Rating; 5/7 #yummy #delicious #politicallycorrect
Emotion: joy
Intensity score: | 0.636 |
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 guess #bradangelina > #anger > #blacklivesmatter
This tweet contains emotions: | anger |
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E). | Tweet: I came to work for no reason 😩🔫\nI could've stayed in bed
Emotion: sadness
Intensity score: | 0.833 |
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: The #chiropractor makes me so #happy.
This tweet contains emotions: | joy, optimism, surprise, trust |
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: HartRamsey'sUPLIFT If you're still discouraged it means you're listening to the wrong voices & looking to the wrong source.Look to the LORD!
Emotion: sadness
Intensity class: | 0: no sadness can be inferred |
Task: Classify the tweet's emotional intensity into one of four ordinal levels of emotion E, providing insights into the mental state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: Did men call themselves shy and mean it? So I reassure him that I'm just making sure he's a good investment and alla that 🙄
Emotion: sadness
Intensity class: | 0: no sadness 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: Can't believe @virginmedia are putting their prices up!! They already know I'm struggling to pay my bill & won't change my package!! #raging
Emotion: anger
Intensity class: | 3: high amount of anger can be inferred |
Task: Evaluate the tweet for emotional cues and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that indicate the tweeter's state of mind. | Tweet: @UndeadLayne @Lauren_Southern all the bully
This tweet contains emotions: | anger, disgust |
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: mustache_harbor: TiburonChamber plus a hearty pour of #yachtrock by #mustacheharbor !
Intensity class: | 1: slightly positive emotional state 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: @elevens_eggos_ 'El?' He turned around to her, smiling before hugging her gently.
Emotion: joy
Intensity score: | 0.667 |
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: Why can't you just be mine. #forlorn
This tweet contains emotions: | joy, love |
Task: Assign a suitable level of intensity of emotion E to the tweet, representing the emotional state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: Honestly depression is kicking my ass lately.. 😔
Emotion: sadness
Intensity class: | 3: high amount of sadness can be inferred |
Task: Determine the dominant emotion in the tweet and classify it as either 'neutral or no emotion' or one of the eleven provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust). | Tweet: i wonder how a guy can broke his penis while having sex? #serious
This tweet contains emotions: | surprise |
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: Baby, I'm dancing in the dark
Emotion: anger
Intensity class: | 0: no anger 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: @Delta stuck on runway after being diverted to Fargo. Continuously told just 10 more mins for the past 4 hours. No food/water offered #awful
Emotion: fear
Intensity score: | 0.667 |
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: Did you know apples turn brown when a enzyme called polyphenol oxidase reacts with oxygen! Well I do #dull #applefacts 🤓🍏
This tweet contains emotions: | joy, optimism |
Task: Rate the valence intensity of the tweeter's mental state expressed in the tweet, assigning it a score on a scale of 0 (most negative) to 1 (most positive). | Tweet: It's so breezy I love it 🌬️🍃💛
Intensity score: | 0.806 |
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: And 9/10 the character is a woman. Because if a man is fat he's jovial. If a woman is fat she's useless and maybe evil amirite?
Emotion: joy
Intensity class: | 0: no joy 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: I was cheering for NA team. Now I just want this is over and Gaudreau comes back in one piece. It is getting way too risky
Intensity class: | 0: neutral or mixed 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: Like he really just fucking asked me that.
This tweet contains emotions: | anger, disgust, pessimism |
Task: Categorize the tweet into an intensity level of the specified emotion E, representing the mental state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: @kymwhitley hello Miss Lady I'm sure today brings you happiness and laughter use your voice also to make us laugh god knows we need it
Emotion: joy
Intensity class: | 2: moderate amount of joy can be inferred |
Task: Classify the tweet's emotional intensity into one of four ordinal levels of emotion E, providing insights into the mental state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: If I'm working and I know you're working., keep in touch with other woman cuz you make me nervous... #OffTop
Emotion: fear
Intensity class: | 2: moderate amount of fear can be inferred |
Task: Measure the level of emotion E in the tweet using a real-valued score between 0 and 1, where 0 represents the lowest intensity and 1 represents the highest intensity. | Tweet: Good morning chirpy #SpringEquinox and your pensive sister #AutumnEquinox A perfect day however it is expressed 🌹🍁🌓☯️ #theBeautyofBalance
Emotion: sadness
Intensity score: | 0.167 |
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: My bus was in a car crash... I'm still shaking a bit... This week was an absolute horror and this was the icing on the cake...
Emotion: fear
Intensity class: | 3: high amount of fear 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: Georgia Tech's Secondary is as soft as a marshmallow.
Emotion: fear
Intensity score: | 0.125 |
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: Imagine suffering chronic depression and being told 'you have an unattractive chip on your shoulder' #DWP #WRAG #WWW.GOV.UK #Mentalhealth
Emotion: sadness
Intensity score: | 0.729 |
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: Pops are joyless, soulless toys which look nearly identical. They are the perfect expression of consumerism. 'I enjoy this franchise'
This tweet contains emotions: | joy, love |
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: You don't know what to expect by Brendon's video lmao LA devotee video got me shook
Emotion: fear
Intensity class: | 0: no fear 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: @AOLUK @JamesHayr @TheDrum Anychance of addressing the communication I sent to you yesterday??? I still haven't had any contact #shocking
Emotion: fear
Intensity class: | 0: no fear can be inferred |
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: Jay Z and Brad Pitt cheated ..Bey stayed Angie left #cheaters #love #lust #sex #couples #relationships #date #marriage #divorce
Intensity class: | 0: neutral or mixed emotional state can be inferred |
Task: Rate the valence intensity of the tweeter's mental state expressed in the tweet, assigning it a score on a scale of 0 (most negative) to 1 (most positive). | Tweet: @maidinaustralia D: That's horrid. *hugs*
Intensity score: | 0.350 |
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: Literally dying & living at the same time as I catch up on @adrian_ver 's twitter. If you aren't following him your life is BASIC.
Emotion: joy
Intensity score: | 0.354 |
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E). | Tweet: Migraine hangover all day. Stood up to do dishes and now I'm exhausted again. GAD, depression & chronic pain #anxiety #depression #pain
Emotion: fear
Intensity score: | 0.880 |
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: How do you feel about @Snapchat new feature #SnapMap 👎👍❓ #twitterpoll #polls #vote #Poll #Snapchat #twitter #tech #technology
Emotion: fear
Intensity class: | 0: no fear can be inferred |
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: Mate the thing I get excited about in my profession are mad. A client said she opened her bowels, I'm rejoicing
Intensity score: | 0.767 |
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: @mtailor “20% Better Than a Tailor”? Least a tailor would know #navy vs. #blue. $500 and 4 weeks for an #innacurate suit?
Emotion: sadness
Intensity class: | 0: no sadness can be inferred |
Task: Evaluate the strength of emotion E in the tweet, providing a real-valued score from 0 to 1. A score of 0 denotes the absence of the emotion, while a score of 1 indicates the highest degree of intensity. | Tweet: @CestLouLeLoup okay, not dead, but if I were, I'd come back to lovingly haunt your sweet asses
Emotion: fear
Intensity score: | 0.354 |
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: #PeopleLikeMeBecause of some unknown reason but I try to discourage it
Emotion: fear
Intensity score: | 0.417 |
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: @SheenKL I assume the manga is #good?
Emotion: joy
Intensity class: | 0: no joy can be inferred |
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: just saw a guy litter out of his Prius😅 #ironic
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: I'm Black, 43. I read books, p/u my kids from school....'My prayer is that u wl lv a long, fulfilling, joyous, peaceful, GOD-pleasing life!
Emotion: joy
Intensity class: | 2: moderate amount of joy can be inferred |
Task: Assess the magnitude of emotion E in the tweet using a real number between 0 and 1, where 0 denotes the least intensity and 1 denotes the most intensity. | Tweet: #ThingsIveLearned The wise #shepherd never trusts his flock to a #smiling wolf. #TeamFollowBack #fact #wisewords
Emotion: joy
Intensity score: | 0.348 |
Task: Rate the valence intensity of the tweeter's mental state expressed in the tweet, assigning it a score on a scale of 0 (most negative) to 1 (most positive). | Tweet: Happy Birthday @Brooke56_56 #cheerchick #jeep #jeepgirl #IDriveAJeep #jeepjeep #Cheer
Intensity score: | 0.839 |
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: 'You're here to feed me. I won't die of starvation,' he said, slightly smiling. I frowned. Panira. Kainis.
This tweet contains emotions: | anger, anticipation, disgust, joy |
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: @ItWontCostMuch_ 'Bed done... floor will be done last... curtains! A-hah!' She tried to sound all happy and cheery but she really wasn't.--
Emotion: joy
Intensity class: | 0: no 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: It's so gloomy outside. I wish it was as cold as it looked
This tweet contains emotions: | 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: @Max_Kellerman it also helps that the majority of NFL coaching is inept. Some of Bill O'Brien's play calling was wow, ! #GOPATS
Emotion: fear
Intensity score: | 0.214 |
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: @coltonflurry @StrangeFacesLA I cancelled by CBS all access live feeds before JC even said Vic won AFP. Paul.should have won IMO
This tweet contains emotions: | disgust, sadness |
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: @fpuebla3 @Osbaldo_A lost a friend too
Emotion: sadness
Intensity class: | 2: moderate 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: @SRuhle @MSNBC Sebestian Gorka, what a arrogant A~hole! Has no business speaking!
Intensity class: | -2: moderately negative emotional state can be inferred |
Task: Categorize the tweet based on the intensity of the specified emotion E, capturing the tweeter's mental state. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: @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.
Emotion: fear
Intensity class: | 1: low amount of fear can be inferred |
Task: Determine the prevailing emotional tone of the tweet, categorizing it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that most accurately represent the tweeter's mental state. | Tweet: @billmaher @realDonaldTrump was right and you two have very similar stances against #radical #islamic #terror. Time to anoint the Orange one
This tweet contains emotions: | disgust, fear |
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: No one wants to win the wild card because you have to play the Cubs on the road. #sadness
Emotion: sadness
Intensity class: | 3: high amount of sadness can be inferred |
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: The next time I go to Lagos I will gate crash somebody's owambe dressed in lace and gele to eat amala and shake my waist😑
Intensity score: | 0.648 |
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: Got a $20 tip from a drunk Uber passenger. Today I get a $25 parking ticket. I'd blame karma but my dumb ass forgot to pay the meter. #rage
Emotion: anger
Intensity score: | 0.708 |
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: Everything I see of American police training seems calculated to trample human dignity, inflame outrage, and escalate confrontations.
Emotion: anger
Intensity score: | 0.604 |
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: Awake at 5.30am with a seriously bad throat 😩😩😩😩😷🤒 glands feel huuuuuuuge and I'm in uni soon! #grim
This tweet contains emotions: | anger, disgust, sadness |
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: @FakingALeto Gerard finally made it up the stairs with a little huff, his face a little more red than it was before. Having little legs --
Emotion: anger
Intensity score: | 0.500 |
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've got some new pens to break in. Name an animated series and I'll draw you in that style 🖍
Emotion: joy
Intensity class: | 1: low amount of joy 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: Men in rage strike those that wish them best. #emotions #negative #positive #wish #strike #martial #arts #control #believe #best #hope
This tweet contains emotions: | anger, disgust, optimism |
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: @thetroche94 @ramiro_cedeno yeah if you want to become obese it is! 😅 I can afford it so I don't think it's that serious haha
This tweet contains emotions: | joy, optimism, pessimism |
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: gifs on iOS10 messaging app are hilarious.
This tweet contains emotions: | joy, surprise |
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: I'm so #glad my #baby can't hear what I'm #thinking
This tweet contains emotions: | joy, optimism |