instruction
stringclasses 50
values | input
stringlengths 32
202
| output
stringlengths 0
55
|
|---|---|---|
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: Gen 8:21 NIV—The Lord smelled the pleasing aroma and said in his heart: “Never again will I… lifelong depravity
This tweet contains emotions:
|
pessimism
|
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: @JohnRMoffitt This is the most grim piece of laughter I was stricken with all day.
Emotion: sadness
Intensity score:
|
0.604
|
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: @Zak_Atif two congressional hearings in USA stopped financial aid to Pak and asked it to prove that it is doing enough to stop terrorism 1n
This tweet contains emotions:
|
fear
|
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: So I went to a different grocery store, and they had no @DukesMayonnaise\nI had to buy Helmann's.\nLiterally shaking right now.
Emotion: fear
Intensity score:
|
0.438
|
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: @Kim_is__bored exactly what I have been saying on fb.. #bitter
Intensity class:
|
-2: moderately negative emotional state 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: jk. started this week strong and it's still going strong.
Intensity class:
|
2: moderately positive 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: Come to the @BullSkitComedy FUNdraiser this Fri. at 8pm @TheScottBlock. Because #pie + #face = #hilarity!
This tweet contains emotions:
|
joy, love, optimism
|
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: @SouthernRailUK delays from Streatham Cmn to Clap Junc & now train took 20 mins for 9 mins journey. Missed 2 trains to Reading
This tweet contains emotions:
|
anger, disgust, 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: Last night I had a dream that today was Christmas. I woke up screaming because I wasn't ready. #nightmare
Emotion: fear
Intensity class:
|
3: high amount of fear 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: Wish I was a kid again. The only stressful part was whether Gabriella and Troy would get back together or not. #hsm2 #nightmare
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: Height of irritation when a person makes a hilarious chusssss.... Plz die....😬😬
This tweet contains emotions:
|
anger, disgust
|
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: @twojacksdetail @bluelivesmtr Very rare an officer just shoots without regard. They don't want that on their conscience. #incite #inflame
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: @rohan_connolly i think your high-profile female colleague would be one in yhat category... #massexodus #bitter
Emotion: anger
Intensity class:
|
1: low 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: @ManUtd it was a terrible Freekick...
Emotion: fear
Intensity score:
|
0.347
|
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: Sky news still pushing the Brexit gloom line, managing to ignore the fact it's simply not happening. 'But in the future.....'
Emotion: sadness
Intensity score:
|
0.396
|
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E).
|
Tweet: every day i have to think in my mind will this be pleasing to God. my decision making, the way i react, treat ppl, speak, am i pleasing God.
Emotion: joy
Intensity score:
|
0.354
|
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: Embarrassing lack of defensive depth coming back to haunt us.
Emotion: fear
Intensity class:
|
0: no fear can be inferred
|
Task: Identify the primary emotion conveyed in the tweet and assign it to either 'neutral or no emotion' or one or more of the provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best capture the tweeter's mental state.
|
Tweet: its so unfortunate that after all these years im still struggling with depression smh
This tweet contains emotions:
|
pessimism, sadness
|
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: Am I the only person who dislikes fall? #FirstDayofFall #leaves #thingsdie #depressing #cold #noflipflops 👎🏾👎🏽👎🏻🍂🍁
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: Omg he kissed her🙈 #shy #w
Emotion: fear
Intensity score:
|
0.312
|
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: Paul forever. Paul should have won! Paul played such a better game! #BB18 #angry
Emotion: anger
Intensity class:
|
2: moderate amount of anger 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: @daemondave @paulkrugman Hey stupid, that was bad intel to take Bin Laden out. Try again with your faux outrage. I bet u admire Putin right?
This tweet contains emotions:
|
anger, disgust
|
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: Asked one thing from our guys tonight and got it! #happy #proud #disappointed - THAT IS FOOTBALL #timetoclimbthetable
Emotion: joy
Intensity score:
|
0.580
|
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: @ikhras @benglaze Amal Clooney should try to prosecute #Bush/ #Blair for #war crimes that turned our World upside down&created #terrorism
Emotion: fear
Intensity score:
|
0.688
|
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: Better mood today! Bring me #teasing, #flirting, #xdressers, #laughter, and #roleplayers! Also #confessions and #secrets @underdeskloser
Intensity class:
|
2: moderately positive emotional state 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: @JessicaZ00 @ZRlondon ditto!! Such an amazing atmosphere! #PhilippPlein #cheerleaders #stunt #LondonEvents #cheer
Emotion: joy
Intensity score:
|
0.740
|
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: #NawazSharif says India poses unacceptable conditions to dialogue.#India's only condition is an end to #terrorism. :@MEAIndia
Emotion: fear
Intensity score:
|
0.680
|
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: @lennyabrahamson May I send you a copy of #HeroTheGreyhound? Either e-book or real paper one! A boy and a greyhound #smiles #tears #laughter
This tweet contains emotions:
|
joy, love, sadness
|
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 ghost of Stefano reflects on the grim indignity of being murdered by corrupt cops in faux love. #days
Emotion: sadness
Intensity class:
|
2: moderate 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: Starting at 22 minutes, this week's @bestshow4life is straight-up paradigm shift level mirth.
This tweet contains emotions:
|
anticipation, joy, love, optimism
|
Task: Rate the intensity of emotion E in the tweet on a scale of 0 to 1, with 0 indicating the least intensity and 1 indicating the highest intensity.
|
Tweet: @AaronGoodwin seriously dude buy some bubble tape for your phones. #snap broke another phone
Emotion: anger
Intensity score:
|
0.458
|
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: Police Officers....should NOT have the right to just 'shoot' human beings without provocation. It's wrong.\n\n@ORConservative @MichaelaAngelaD
Emotion: anger
Intensity class:
|
3: high amount of 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: @npagliaro1 That's awesome! p.s. ok, what are the odds of that, swapping neighborhoods? #hilarious
Emotion: joy
Intensity class:
|
3: high amount of joy 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: Seeing double am so tired but I always grudge getting off my phone at night 🙄
Emotion: anger
Intensity score:
|
0.479
|
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: 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: 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: Why does @dapperlaughs have to come to Glasgow on a night I am working. I am fucking gutted, been waiting for an appearance for ages
Emotion: anger
Intensity class:
|
3: high amount of anger can be inferred
|
Task: Determine the appropriate intensity class for the tweet, reflecting the level of emotion E experienced by the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.
|
Tweet: @PhilRosenthal Perhaps I've missed it, are you doing another season of IHWPH???\nYou are so joyous and gleeful at the the prospect of eating!
Emotion: joy
Intensity class:
|
3: high amount of joy 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: @ryanwilson2015 That's why compatibility is key as it lowers hedonic volatility.
Emotion: joy
Intensity score:
|
0.250
|
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: Bunk ur class📚 at least once in your life time cuz later when u look back good marks will not make u happy but memories😊 will' -APJ
Emotion: joy
Intensity score:
|
0.646
|
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: @jk_rowling never thought an angry oompa loompa would be my Boggart, but there you have it. #boggart #PresidentTrump
This tweet contains emotions:
|
anger, anticipation, disgust, 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: @Kailyew hahah tiff sent me that too😂
Emotion: anger
Intensity score:
|
0.208
|
Task: Assess the sentiment intensity or valence level of the tweet, ranging from 0 (extremely negative) to 1 (extremely positive).
|
Tweet: Star trek online has a update to download oh fuming yay
Intensity score:
|
0.641
|
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: chirp chirp! what a beautiful white and red bird! 🐦
Emotion: joy
Intensity class:
|
2: moderate 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: TONIGHT - Fulford Arms, York \nTOMORROW - Bank Top Tavern, Oldham\nNEXT SATURDAY- Big Hands, Manchester \n\n#livemusic #punk #blues #rockandroll
Emotion: sadness
Intensity score:
|
0.188
|
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: Thank you @RachelPlatten for teaching me how to live again. It's been so long since & this ride is about to be exhilarating. I just know it
Emotion: joy
Intensity class:
|
3: high amount of 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: Stop tracking back you fucking potato faced cunt errrr infuriating 😠😠😠😠😠 #Rooney #mufc
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: @TurtleTitan2003 (She laughed a bit. Of course it was! Aria shook her head, calming her mirth so she could listen to Mikey.) No, actually. +
Emotion: joy
Intensity class:
|
1: low 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: .@morningmika & her @HillaryClinton Super PAC @Morning_Joe @MSNBC in full #panic mode over @realDonaldTrump #momentum!\n\n#TrumpPence16 #MAGA
Emotion: fear
Intensity score:
|
0.723
|
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: Sanatana Lopez is definitely me 😂
This tweet contains emotions:
|
joy, optimism
|
Task: Rate the intensity of emotion E in the tweet on a scale of 0 to 1, with 0 indicating the least intensity and 1 indicating the highest intensity.
|
Tweet: When you make a great tasting shake and no words can describe it!😃👌🏻 #herbalifenutrition #tastesogood #nowords
Emotion: fear
Intensity score:
|
0.125
|
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: @JohnVerdejo Mannn I can't count how many times I've had the '#PR's power grid needs some serious updating' conversation...
Emotion: sadness
Intensity class:
|
1: low amount of sadness 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: #NawazSharif says lets end #terror. Sure, let #IndianArmedForces target the bases without #Pakistan interference #Karma?
This tweet contains emotions:
|
anger, disgust, fear
|
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: Tend the sick, Lord Christ; give rest to the weary, bless the dying, soothe the suffering, pity the afflicted, shield the joyous;
Intensity class:
|
1: slightly positive emotional state 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: Don't depress yourself by comparing yourself. No comparisons.
This tweet contains emotions:
|
optimism, 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: Gotta hit up breezy every day to make sure he's breaking in my boots. First class friend right there
Emotion: joy
Intensity class:
|
1: low amount of joy can be inferred
|
Task: Categorize the tweet's emotional expression, classifying it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that reflect the tweeter's state of mind.
|
Tweet: It's dark
This tweet contains emotions:
|
fear
|
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: Jay Z and Brad Pitt cheated ..Bey stayed Angie left #cheaters #love #lust #sex #couples #relationships #date #marriage #divorce
Emotion: sadness
Intensity class:
|
0: no sadness can be inferred
|
Task: Place the tweet into a specific ordinal class, which captures the tweeter's mental state by considering different levels of positive and negative sentiment intensity. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred.
|
Tweet: HUGE CONGRATULATIONS TO NICOLE WINNING BIG BROTHER 18! @BBNicole #BB18 sorry not sorry #bbmichelle
Intensity class:
|
3: very positive emotional state can be inferred
|
Task: Assign a suitable level of intensity of emotion E to the tweet, representing the emotional state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred.
|
Tweet: The kid at the pool yelling is about to get a foot up his ass. #shutup #parents #kids
Emotion: fear
Intensity class:
|
0: no fear 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: @PAULROVlA the first resulted in me angrily sobbing and ranting about finnick in the cinema
Emotion: anger
Intensity score:
|
0.562
|
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: @memorie_holiday @AngryOrchard about 2 wks ago,playing pokemon and not paying attention. Placed my elbow on a rail 3 inches from 4 no sting.
Emotion: anger
Intensity score:
|
0.500
|
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: Whatever you decide to do make sure it makes you .
Emotion: joy
Intensity score:
|
0.440
|
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: The book im riteing about wots happond has made them moor angry but im not here to plese man or hide the eval deeds of some
Emotion: anger
Intensity class:
|
2: moderate amount of anger 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: @Rovers what highlights ? I would imagine you will only have 30 seconds of highlights for the whole season so far #shocking. #venkysout
Emotion: fear
Intensity class:
|
0: no fear 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: Y'all do the most on twitter and snap
Emotion: anger
Intensity class:
|
1: low 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: Who got madden 17 or 2k17 ps4 add TrackdawgT lets run it
This tweet contains emotions:
| |
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: not to be That Person™ but i get bitter seeing some ravi stans
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: @BluesfestByron second artist announcement looking good #bluesfest2017 #blues #Music #byronbay
Emotion: sadness
Intensity score:
|
0.083
|
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: @BigBossPeltonen \nLikewise #death #cutting #despair
Emotion: fear
Intensity class:
|
3: high amount of fear can be inferred
|
Task: Assess the sentiment intensity or valence level of the tweet, ranging from 0 (extremely negative) to 1 (extremely positive).
|
Tweet: @npagliaro1 That's awesome! p.s. ok, what are the odds of that, swapping neighborhoods? #hilarious
Intensity score:
|
0.766
|
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: Traditionalists say it should be bored by or bored with, but not bored of, a 'rule' cheerfully ignored
Intensity class:
|
0: neutral or mixed 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: @dc_mma @ChampionsFight think shes afraid to fight Holly. One can only imagine what goes through her head when she thinks of Cyborg
Emotion: fear
Intensity score:
|
0.688
|
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: @SurfaceSupport A profoundly disappointing experience. I have 2 pay almost $500 2 remedy a defect n the product @Microsoft sold me #terrible
Emotion: fear
Intensity score:
|
0.480
|
Task: Classify the tweet into one of seven ordinal categories, indicating the intensity of positive or negative sentiment expressed by the tweeter and reflecting their current mental state. 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: The 'banter' from Craigen and Sutton on BT is fucking horrid
Intensity class:
|
-3: very negative emotional state 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: With that draw, the scum must be rubbing their hands with glee! Typical draw for the Woolwich lot!!! #jammygunnerscum
Emotion: joy
Intensity class:
|
0: no joy 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: @littlepieces Customer services got involved and eventually completely wash their hands of it. #dreamornightmare
Emotion: fear
Intensity score:
|
0.479
|
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: I thought I wouldn't have to deal with that fire alarm again today and then I stepped into Mesa during their fire drill👀
Emotion: fear
Intensity score:
|
0.521
|
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: My #anxiety is rising tonight and I'm not sure why. Sometimes I wonder if I'm a magnet for any free-floating anxiety in the universe.
This tweet contains emotions:
|
fear, pessimism
|
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: @TheBarmyArmy all the optimism...
Intensity score:
|
0.534
|
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: Val got a little too big for her hiking boots with that bakewell, the little terror #GBBO
This tweet contains emotions:
|
fear, joy, love
|
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 a great training course, lots of photos, fun and laughter. Photo's will be up soon #Boostercourse #fun
This tweet contains emotions:
|
anticipation, joy, love, optimism
|
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: hate to see y'all frown but I'd rather see him smiling 💕✨
This tweet contains emotions:
|
joy, optimism
|
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: repentance, and trusting in Christ. It is lowly and painful, but it is also joyous, peaceful, and absolutely glorious. (2/2)
This tweet contains emotions:
|
joy, 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: @cxmbeferre so you WOULDNT date me????? #offended
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: Thank you @twitter for the balloons today. #goodday #48
Emotion: joy
Intensity score:
|
0.562
|
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: hate overthinking e v e r y t h i n g like i jus' wanna be happy pls
Emotion: joy
Intensity class:
|
0: no joy 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: Yo Yo Yo,my name is #DarthVader \nI feel like I need to puff on my inhaler (I'm no rapper but that was some sick bars) #breathless #bars #rap
Emotion: fear
Intensity score:
|
0.208
|
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: @bldmovs sadly beautiful photo.
Emotion: sadness
Intensity score:
|
0.375
|
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: Thanks for ripping me off again #Luthansa €400 not enough for a one way flight to man from Frk then €30 for a bag then free at gate #awful
Emotion: fear
Intensity score:
|
0.521
|
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: #terribledebatequestions has given me so many laughs this afternoon! Thanks Twitter! #hilarious #cleverpeople
Intensity class:
|
3: very 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: “Worry is a down payment on a problem you may never have'. Joyce Meyer. #motivation #leadership
Emotion: fear
Intensity score:
|
0.292
|
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: 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...
This tweet contains emotions:
|
anger, disgust, fear, pessimism, 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: Love being made to feel bad about being scared of the dark
This tweet contains emotions:
|
disgust, fear, joy, love, sadness
|
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: @jackmegawphoto what if lives are attached to real estate? Shall I come trash your cameras because I'm angry with what your race is doing?
This tweet contains emotions:
|
anger, disgust
|
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: @lesyoung01 a rabid dog being ridden by the child who has eaten all the flesh off one fellow and the limbs of the other adults.
Emotion: anger
Intensity score:
|
0.583
|
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: Taguchi engineering fashionable hale and hearty little game optimization: MqnAOcU
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: @littlepieces Customer services got involved and eventually completely wash their hands of it. #awful #dreamornightmare
This tweet contains emotions:
|
anger, disgust
|
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: @BluesfestByron second artist announcement looking good #bluesfest2017 #blues #Music #byronbay
Emotion: sadness
Intensity score:
|
0.083
|
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: @Taniel @LOLGOP That'll be gosh darn terrific if they only check the brown people. Shucks, let's make a law to say only brown people.
This tweet contains emotions:
|
anger, anticipation, 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: What an actual nightmare
Emotion: fear
Intensity class:
|
2: moderate amount of fear can be inferred
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.