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Task: Gauge the level of intensity for emotion E in the tweet, assigning it a score between 0 and 1. A score of 0 indicates the lowest intensity, while a score of 1 indicates the highest intensity.
|
Tweet: @StarklyDark 'I know you trusted me.' His words were soft as he ignored the anger and focused on the hurt beneath. 'I know I screwed up.' --
Emotion: anger
Intensity score:
|
0.562
|
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: @PhilGlutting Hey There Phil Glutting thank you for following us, it's appreciated :)
This tweet contains emotions:
|
joy, optimism
|
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: @patthemanager how could I work with @chancetherapper . ? #serious
Emotion: sadness
Intensity score:
|
0.354
|
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: my haters are like crickets. they chirp all day but when I walk past them they shut the fuck up.- @DritaDavanzo (my idol)
This tweet contains emotions:
|
anger, anticipation, disgust
|
Task: Assign a suitable level of intensity of emotion E to the tweet, representing the emotional state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.
|
Tweet: Well i did hear once before that girls are attracted to men that look like their dad! π #serious
Emotion: sadness
Intensity class:
|
0: no sadness can be inferred
|
Task: Categorize the tweet's emotional tone as either 'neutral or no emotion' or identify the presence of one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).
|
Tweet: @LeahSKahn honestly. All I care about is Selasi not messing this up. His lackadaisical attitude isn't good for danishes.
This tweet contains emotions:
|
anger, 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: Sigh. I got a B- .. #depressing
Emotion: sadness
Intensity class:
|
3: high amount of sadness can be inferred
|
Task: Evaluate the tweet for emotional cues and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that indicate the tweeter's state of mind.
|
Tweet: @LFScott57 Miss Cookie sends her thanks! She's not as spry as she used to be - like me! She doesn't have the adventures the young pups do!
This tweet contains emotions:
|
joy, love, pessimism
|
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: @RoseTintMyWorId fucking hell mate absolute nightmare π
Emotion: fear
Intensity score:
|
0.854
|
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: All the bright places :(
This tweet contains emotions:
|
sadness
|
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: #Terencecutcher #Tulsa the man onthe helicopter said he looks like a bad dude, that is the problem, when they see black they see bad, #sad
Emotion: sadness
Intensity class:
|
2: moderate amount of sadness can be inferred
|
Task: Assess the magnitude of emotion E in the tweet using a real number between 0 and 1, where 0 denotes the least intensity and 1 denotes the most intensity.
|
Tweet: Finally have all my braces on and I can't stop smiling πππππ
Emotion: joy
Intensity score:
|
0.940
|
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 asked Jared to marry me and he said no.
Emotion: anger
Intensity score:
|
0.521
|
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: On the drive home today I heard a censored version of Spirits by The Strumbellas. 'Guns' replaced with 'dreams'. Just NO. #awful #censorship
This tweet contains emotions:
|
anger, disgust
|
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: Marcus Roho is dreadful
Intensity class:
|
-2: moderately negative emotional state 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: IΒve learnt that a #smile and good #morning goes a long way, and saying #thankyou goes even further. #quote #retweet #inspire
Emotion: joy
Intensity score:
|
0.646
|
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: @spamvicious I've just found out it's Candice and not Candace. She can pout all she likes for me π
Emotion: anger
Intensity class:
|
0: no anger can be inferred
|
Task: Categorize the tweet's emotional tone as either 'neutral or no emotion' or identify the presence of one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust).
|
Tweet: i started glee from the beginning n i'm crying they were such babies i love my children
This tweet contains emotions:
|
joy, love, 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: #Zumba, #PiYo and #HIIT sessions. Sweaty, burning but sooooooo good! #missedoutonsummerbikinibodybutwintersunbodywilldo
Emotion: anger
Intensity class:
|
0: no anger can be inferred
|
Task: Categorize the tweet based on the intensity of the specified emotion E, capturing the tweeter's mental state. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.
|
Tweet: @casillasbreanna awe thanks girl ππ
Emotion: fear
Intensity class:
|
0: no fear can be inferred
|
Task: Categorize the tweet into an intensity level of the specified emotion E, representing the mental state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.
|
Tweet: I love this hearty negro laugh jade and @XavierDLeau let out re:lochte ππ
Emotion: joy
Intensity class:
|
3: high amount of 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: @rclemmons much #sadness and #heartbreak
This tweet contains emotions:
|
disgust, sadness
|
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: @mrfisher81 Just my attempt at levity π
Intensity class:
|
0: neutral or mixed emotional state 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: Epicurus~ The man least dependent upon the morrow goes to meet the morrow most cheerfully.
Emotion: joy
Intensity score:
|
0.400
|
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: why is @Iongroadhome so aesthetically pleasing every single day they're even pretty when they just woke up, when they're tired, just. always
Emotion: joy
Intensity class:
|
0: no joy 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: Watch this amazing live.ly broadcast by @jaredhorgan #musically
This tweet contains emotions:
|
joy, surprise, trust
|
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: So excited to watch @RuPaulsDragRace #allstars \n#RuPaul #revenge
Emotion: anger
Intensity class:
|
0: no anger 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: This is the scariest American Horror Story out of all of them... I'm gonna have to watch in the daytime.
This tweet contains emotions:
|
anticipation, fear, surprise
|
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: Obama admin rejects Texas plan to have refugees vetted for terrorism so Texas pulls of of fed refugee resettlement program. Aiding .
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: I don't get what point is made when reporting on Charlotte looting @CNNAshleigh. Why not explore what looting businesses symbolizes
Emotion: anger
Intensity score:
|
0.438
|
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: And girl I love your perfume there's something bout you π§
Emotion: joy
Intensity score:
|
0.729
|
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: #survivor is back! #SurvivorMillennialsVsGenX so happy to see you @JeffProbst #happy
This tweet contains emotions:
|
joy, love, optimism, trust
|
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: Avoiding #fears only makes them scarier. Whatever your #fear, if you face it, it should start to fade. #courage
Emotion: fear
Intensity score:
|
0.705
|
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: @TokyoSexPolice can I get away of this wrath by reading manga instead of watching overdone anime
Emotion: anger
Intensity score:
|
0.468
|
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: I love my family so much #lucky #grateful #smartassfamily #hilarious #love
Emotion: joy
Intensity class:
|
3: high amount of joy 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: God hears your voice optimism at the moment that you think that everything has failed you β¨.
Emotion: joy
Intensity score:
|
0.312
|
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: @kcbbcxo don't get discouraged! it's early on & it can get overwhelming. keep reading & use cue cards π it'll get better!!
Emotion: sadness
Intensity score:
|
0.229
|
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: @BuzzFeed so this houses will get into my instestines and scare my poop and I'll shit my pants?
This tweet contains emotions:
|
anger, disgust, fear
|
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E).
|
Tweet: @eMilsOnWheels I'm furious π©π©π©
Emotion: anger
Intensity score:
|
0.708
|
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: Elinor,' she laughed so little known, all over every body at the brilliant cheerfulness of sweetmeats and a fashion.
Emotion: joy
Intensity score:
|
0.604
|
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: @GambieRanger @David__Osland which is why a leader who is encouraging his supporters to deselect is such a concern for many of us.
Emotion: fear
Intensity class:
|
0: no fear can be inferred
|
Task: Assign a suitable level of intensity of emotion E to the tweet, representing the emotional state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.
|
Tweet: Probs spent a grand total of five minutes sober since Sunday evening :) #freshers
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: @aradsliff don't know I'm from nj we are the worst on purpose. #laughter
Emotion: joy
Intensity score:
|
0.462
|
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: @Its_just_Huong I will beat you !!! Always thought id be gryffindor so this is a whole new world for me π¨π¨π¨ #excited
Emotion: fear
Intensity score:
|
0.250
|
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: @EE your website is making me feel violent rage and your upgrade options aren't helping either. #Aaaaarrrrgghhh #iwanttocancel #rage
Intensity score:
|
0.086
|
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: If angry, bash out your frustration on the pastry #GBBO
Emotion: anger
Intensity class:
|
2: moderate amount of anger 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: Always do sober what you said you'd do drunk. That will teach you to keep your mouth shut. \nβ Ernest Hemingway #quote
This tweet contains emotions:
|
optimism, trust
|
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: Sometimes The Worst Place You Can Be Is In Your Own Head.'\n\n#quotes #worstenemy #depression #thinktoomuch
This tweet contains emotions:
|
anger, disgust, fear, pessimism, 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: @EurekaForbes U got to b kidding me. Anu from your firm responded when I sent the contact details. #customerexperience
Emotion: fear
Intensity class:
|
0: no fear can be inferred
|
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: @ahtareen1 @ReginalAleman @krelifa @zamansj64 @AwiexaB Very pleasing ty!
Intensity class:
|
2: moderately positive emotional state 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: @1xfly you sir are hilarious
Emotion: joy
Intensity score:
|
0.602
|
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E).
|
Tweet: @TheZantarin Then maybe we should keep our White mouths shut and let the people being targeted speak and mourn.
Emotion: sadness
Intensity score:
|
0.729
|
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: Virtually every statement by other countries at UN has referred to #terror as main threat to peace, #Pak still in denial: MEA.
Emotion: fear
Intensity score:
|
0.646
|
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: @SMalloy_LWOS that's not easy to blow up the LT on a run play. He created the seam for Sua to burst through
This tweet contains emotions:
|
joy
|
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: An hour played and @ASFCofficial have conceded less at West ham than @ManUtd have at northampton. Let that sink in.
Emotion: sadness
Intensity score:
|
0.420
|
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: @rickygervais my first time in Slough so checked out the new station floor #LifeOnTheRoad
Emotion: sadness
Intensity class:
|
0: no sadness 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: says, who are you to compared me with the others; I'm just human. #lit #fire
Emotion: anger
Intensity class:
|
2: moderate amount of anger can be inferred
|
Task: Assign one of four ordinal intensity classes of emotion E to a given tweet based on the emotional state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.
|
Tweet: @Dominos_UK worst thing is i have confimation from them
Emotion: anger
Intensity class:
|
2: moderate amount of anger can be inferred
|
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E).
|
Tweet: I need a syfy series to watch I literally have nothing to watch back to back. I already watched #heroes #lost #jericho #fallenskies etc etc
Emotion: sadness
Intensity score:
|
0.312
|
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: @Thebeast_ufc what happened to the suicide tweet it was a joke obviously how could that offend anyone?π€
Intensity score:
|
0.422
|
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: @m_t_f_72 I'm not surprised, I would be fuming! π€
Emotion: anger
Intensity class:
|
2: moderate amount of anger 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: @CNN Wait, didn't she get a case of the ass when Donald Trump called it terrorism BEFORE all the facts were in? I guess it's ok if she does
This tweet contains emotions:
|
anger, disgust
|
Task: Classify the tweet into one of four ordinal intensity levels, indicating the degree of emotion E experienced by the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.
|
Tweet: @zombieisIand yeah friends of minw have witnesse accidents and a road near me like??? cars hav like sunk?? but ih gosh be safe okay !!
Emotion: sadness
Intensity class:
|
2: moderate amount of sadness can be inferred
|
Task: 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: Imagine being bitter when your bias is dating & sending threats to their partner. Like why? That's nasty. And they don't even know you exist
Emotion: anger
Intensity score:
|
0.604
|
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: @brian5or6 turn that shit off! Home Button under Accessibility. \n\nWhen did innovation become mind fuckery? #rage. #iphonePhoneHome
This tweet contains emotions:
|
anger, disgust
|
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 in awe
Emotion: fear
Intensity class:
|
0: no fear 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: @jessebwatters lol. Love it when you aggravate Juan. Keep up the good work. Lol
This tweet contains emotions:
|
joy, trust
|
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: @lindseylouwho_ be nice if the Texans could hold onto the ball to give fuller and Hopkins a chance!!! #awful #TNF
Emotion: fear
Intensity score:
|
0.333
|
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: @mediacrooks @thenewshour @LodhiMaleeha @ndtv @IndiaToday This is hilarious ! Not a Freudian slip, eh !
This tweet contains emotions:
|
joy, love, optimism
|
Task: Measure the level of emotion E in the tweet using a real-valued score between 0 and 1, where 0 represents the lowest intensity and 1 represents the highest intensity.
|
Tweet: Have any of you ever stayed in hostels overseas? My only frame of reference is the movie Hostel, and we all know how that went.
Emotion: sadness
Intensity score:
|
0.229
|
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: Yeah I'm hot nigga, they say im burning uhhhhh
This tweet contains emotions:
|
anger, disgust
|
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: @SoCalValerie this one was Apples attempt to make muslims happy π
Intensity class:
|
0: neutral or mixed emotional state 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: I'm buying art supplies and I'm debating how serious is it to buy acrylic paint.
This tweet contains emotions:
|
joy, surprise
|
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: ο₯οοΌ- its lit having a class with you!!! Your such a great person and good at cheer!!
Emotion: joy
Intensity class:
|
3: high amount of joy can be inferred
|
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: ACT 4 #anxiety & #depression group. @livingwellihc beginning Mon October 17 for 6 weeks. Contact me to register now! #mindfulness #Halifax
Intensity class:
|
0: neutral or mixed emotional state 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: @alicereidy more of a hearty Italian man myself
This tweet contains emotions:
|
joy, optimism
|
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: Get to the gym and discover I forgot to put my gym shoes back in my bad π€ #wwhhyyy
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: We ashamed of being an ally to you. Pakistan sacrificed almost 50000 civilians by siding you in war on #terror @JudgeTedPoe
Emotion: fear
Intensity score:
|
0.667
|
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: @xiankiefer @TheLincoln Book 5! It's so sprightly & fun cuz he'd been reinvigorated by the Harry Potter series. I'm not kidding.
Intensity score:
|
0.781
|
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: @ImNotInfected β rather someone that could help her. Concern clouded her green eyes, not once having seen a girl alone in the woods and β
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: I'm so old next Friday. So super oldπ©π I dread birthdays
Emotion: fear
Intensity score:
|
0.646
|
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 get so angry at people that don't know that you don't have a stop sign on Francis and you do at Foster #road
Emotion: anger
Intensity class:
|
3: high amount of anger can be inferred
|
Task: Determine the degree of intensity for emotion E in the tweet, giving it a score between 0 and 1, where 0 signifies the least intensity and 1 signifies the greatest intensity.
|
Tweet: At #UNGA Pakistan clearly shows the face of cowardliness and blatant lies! Its time for #India to act upon terror.
Emotion: fear
Intensity score:
|
0.667
|
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: @zinabukvic_ cheer up
This tweet contains emotions:
|
joy
|
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: Your future is bright. #Remember
Emotion: joy
Intensity score:
|
0.577
|
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: Wont use using @mothercareuk @Mothercarehelp again!! These guys cant get nothing right!!
This tweet contains emotions:
|
anger, disgust
|
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: the day they disclosed they caught her googling cholroform we were fucking aghast
Emotion: fear
Intensity score:
|
0.632
|
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: Wow... One of my dads top favorite throwback rappers just died in a fiery car crash today in Atlanta, so sad so sad π·π·
Emotion: anger
Intensity score:
|
0.396
|
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 know few will mourn the loss of Stitch's Great Escape, but...see, THIS is the kind of cost-cutting at parks I really don't care for.
Emotion: sadness
Intensity score:
|
0.619
|
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: 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 #laughter #moretears
This tweet contains emotions:
|
joy, love, optimism, sadness
|
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: @OniLink86 @DarekMeridian lmao awe... #sad
Emotion: sadness
Intensity class:
|
1: low amount of sadness can be inferred
|
Task: Classify the tweet's emotional intensity into one of four ordinal levels of emotion E, providing insights into the mental state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.
|
Tweet: @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.
Emotion: anger
Intensity class:
|
0: no anger 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: @marielleblaine8 @princesskeilani I told pine I didn't want it so I didn't have to have it
Emotion: sadness
Intensity class:
|
0: no sadness can be inferred
|
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: @AphoticSanguine βbut be a little playful. \n\nHe hesitantly pulls away, just enough so he could get words out, lips brushing againstβ
Intensity class:
|
2: moderately positive emotional state can be inferred
|
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: @ruthwalford95 you may be right, but since year the bad events begin with B, I'm privately hoping we've got at least C-Z to go 1st #optimism
Emotion: joy
Intensity class:
|
0: no joy 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 how people can binge watch horror films ...ALONE!ππ°
This tweet contains emotions:
|
fear, pessimism
|
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: @WildRoverTours Thank you for follow and its a good website you have and cheering with no hassle.
This tweet contains emotions:
|
joy, trust
|
Task: Classify the tweet into one of four ordinal intensity levels, indicating the degree of emotion E experienced by the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.
|
Tweet: I should really study today for chemistry but playing madden is just way more fun.
Emotion: anger
Intensity class:
|
0: no anger 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: So excited to watch @RuPaulsDragRace #allstars \n#RuPaul #revenge
Emotion: anger
Intensity score:
|
0.167
|
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: @ETimsNet I wanted him dropped a while ago. Its a concern for us no doubt
Emotion: fear
Intensity score:
|
0.500
|
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