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Task: Gauge the intensity of sentiment or valence in the tweet, indicating a numerical value between 0 (extremely negative) and 1 (extremely positive).
Tweet: This rain had me dancing in the street #rejoice #rejoice #thetimeofgreatsorrowisover
Intensity score: | 0.783 | 2 | v_reg | 768 |
|
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: @realDonaldTrump says the guy who revealed \n#topsecret information to the #Russians #irony also, it's unverified, you punk.
Intensity score: | 0.258 | 7 | v_reg | 769 |
|
Task: Measure the intensity of sentiment or valence in the tweet, assigning it a score between 0 (highly negative) and 1 (highly positive).
Tweet: @MartinPincot Haha @MartinPincot - just sent a sext to the vicar with a holy, holy, twist --- My bad 😂\n \n#Fun #joy #laughter \n👿 ..... 😇
Intensity score: | 0.875 | 4 | v_reg | 770 |
|
Task: Determine the valence intensity of the tweeter's mental state on a scale of 0 (most negative) to 1 (most positive).
Tweet: @realDonaldTrump PS. I thoight your investigation was the: 'greatest witch hunt.?' Wow, something is better than yours! #sarcasm
Intensity score: | 0.500 | 6 | v_reg | 771 |
|
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: Found out the peraon i liked wanted to that someone else #sadness
Intensity score: | 0.153 | 7 | v_reg | 772 |
|
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: finnish 'table manners', to the extent they exist, seem to include only self sufficiency and not getting in people's way so it's hilarious
Intensity score: | 0.625 | 7 | v_reg | 773 |
|
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: @gogreen18 Trans people love being reminded that they'll never be complete. #sarcasm #comicsans
Intensity score: | 0.481 | 9 | v_reg | 774 |
|
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: @Walu2go @ThisisLukeOwen Yes it is. I especially love the ramble chat love when they go off topic for like ten minutes. #awesomeness
Intensity score: | 0.806 | 0 | v_reg | 775 |
|
Task: Measure the intensity of sentiment or valence in the tweet, assigning it a score between 0 (highly negative) and 1 (highly positive).
Tweet: The enjoyment of seeing the same thing your ex did to you happen to them! #karma #😂 #whatgoesaroundcomesaround
Intensity score: | 0.778 | 4 | v_reg | 776 |
|
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: @prisonerben1 Try explaining to Joe Public these charities do not simply give offenders 'treats' #despair
Intensity score: | 0.145 | 3 | v_reg | 777 |
|
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: @Bombardier Joyeux anniversaire / Happy birthday Bombardier Inc. :)
Intensity score: | 0.828 | 5 | v_reg | 778 |
|
Task: Measure the intensity of sentiment or valence in the tweet, assigning it a score between 0 (highly negative) and 1 (highly positive).
Tweet: @executivegoth I tried a free Alpha trial to watch #dread and I'm sold. Worth the subscription alone. You all are incredible!
Intensity score: | 0.613 | 4 | v_reg | 779 |
|
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: @PuddlesPityP Witnessed #totality, overcome with insane awe & emotion. Son equated to witnessing your talent. #hegetsit #cry #eclipse2017
Intensity score: | 0.654 | 3 | v_reg | 780 |
|
Task: Gauge the intensity of sentiment or valence in the tweet, indicating a numerical value between 0 (extremely negative) and 1 (extremely positive).
Tweet: @KEEMSTAR I mean see tge point but it is a lively hood for some. Really the only ones that should complain are...
Intensity score: | 0.483 | 2 | v_reg | 781 |
|
Task: Gauge the intensity of sentiment or valence in the tweet, indicating a numerical value between 0 (extremely negative) and 1 (extremely positive).
Tweet: Signs of Incipient Faggotry are the arsehole quivering and puckering.
Intensity score: | 0.290 | 2 | v_reg | 782 |
|
Task: Assess the sentiment intensity or valence level of the tweet, ranging from 0 (extremely negative) to 1 (extremely positive).
Tweet: Beautiful morning at the beach on Anna Maria Island with my wife. #vacation #blessed #happy
Intensity score: | 0.923 | 1 | v_reg | 783 |
|
Task: Measure the intensity of sentiment or valence in the tweet, assigning it a score between 0 (highly negative) and 1 (highly positive).
Tweet: Tomorrow should be interesting if info is being released re away priority & Canalside membership! #outrage #htafc
Intensity score: | 0.483 | 4 | v_reg | 784 |
|
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: @whatthefarrugia still trembling
Intensity score: | 0.234 | 9 | v_reg | 785 |
|
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: @DaaruBaazMehta Prime Minister of India & Home Minister of India are responsible to take strict action against BJP 🙄 😄 #sarcasm
Intensity score: | 0.370 | 7 | v_reg | 786 |
|
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: @_lanimoreno and I had Chem, Anatomy, and now IB Sports together (': #amazing
Intensity score: | 0.970 | 9 | v_reg | 787 |
|
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: @WalmartToday your hitting it spot on with your commercials. Love the one with the town coming to eat and bringing chairs. #brilliant
Intensity score: | 0.740 | 7 | v_reg | 788 |
|
Task: Assess the sentiment intensity or valence level of the tweet, ranging from 0 (extremely negative) to 1 (extremely positive).
Tweet: @RegPCB I like a world where Love Island drarms is the worst thing I've got to worry about.
Intensity score: | 0.567 | 1 | v_reg | 789 |
|
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: @TimHortons Please please PLEASE make your jalapeño jack sandwich a regular! I LOOOVE it!!!
Intensity score: | 0.710 | 7 | v_reg | 790 |
|
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: Is it okay to think you are going to die alone? #sadness
Intensity score: | 0.052 | 5 | v_reg | 791 |
|
Task: Measure the intensity of sentiment or valence in the tweet, assigning it a score between 0 (highly negative) and 1 (highly positive).
Tweet: Thank you for the M line construction @MTA . Sincerely, all J train riders Essex to Bway Junction. #nycsubway
Intensity score: | 0.667 | 4 | v_reg | 792 |
|
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: Woke up to my neighbors singing Perfect by Ed Sheeran. 😊 My mood has been set. 😍
Intensity score: | 0.871 | 5 | v_reg | 793 |
|
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: @jaketapper So badly they talked adoption for 20 min. I would certainly trust what a Russian agent says. #sarcasm
Intensity score: | 0.350 | 5 | v_reg | 794 |
|
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: my name is sara, im 20 years old and i cant believe boiling an onion is making me cry
Intensity score: | 0.161 | 9 | v_reg | 795 |
|
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: Just seeing school idols fills me with energy, makes me want to cheer for them and makes me also want to sing and dance together with them!
Intensity score: | 0.821 | 0 | v_reg | 796 |
|
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: beautiful day Lord has made let us rejoice & be glad in it & rejoice Hillary NOT president! God bless POTUS & United States of America🇺🇸👍
Intensity score: | 0.833 | 3 | v_reg | 797 |
|
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: All the proud parents on fb about their kids school report and am shitting myself for Graces arriving 😂😂😂 #troublemaker
Intensity score: | 0.597 | 7 | v_reg | 798 |
|
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: @AppleSupport worst customer service. 3days to get a diagnostic appt?! #disappointing #ittakes3minutestorunadiagnostic
Intensity score: | 0.210 | 7 | v_reg | 799 |
|
Task: Measure the intensity of sentiment or valence in the tweet, assigning it a score between 0 (highly negative) and 1 (highly positive).
Tweet: @NathanSykes Happy Tuesday. I hope you have an amazing day. Proud of you & blessed to know you. You make my world better by being in it.❤️
Intensity score: | 0.897 | 4 | v_reg | 800 |
|
Task: Quantify the sentiment intensity or valence level of the tweet, giving it a score between 0 (highly negative) and 1 (highly positive).
Tweet: happy birthday girly, hope you have an amazing day :) @kkarlidawson
Intensity score: | 0.900 | 8 | v_reg | 801 |
|
Task: Assess the sentiment intensity or valence level of the tweet, ranging from 0 (extremely negative) to 1 (extremely positive).
Tweet: @cyclingweekly 'shocking' ??? Nah that's not Shocking . Richie Portes crash ...THAT WAS shocking . #tourdefrance2017
Intensity score: | 0.393 | 1 | v_reg | 802 |
|
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: Good Morning #start 2Wheel #free course *Pune *8888006565
Intensity score: | 0.581 | 0 | v_reg | 803 |
|
Task: Assess the sentiment intensity or valence level of the tweet, ranging from 0 (extremely negative) to 1 (extremely positive).
Tweet: Lugubrious face, crestfallen eyes, forlorn heart and an agitated soul seeking serenity.
Intensity score: | 0.234 | 1 | v_reg | 804 |
|
Task: Quantify the sentiment intensity or valence level of the tweet, giving it a score between 0 (highly negative) and 1 (highly positive).
Tweet: Just when you thought the weather would be peachy for the rest of the day, downpour happens. #murphysucks #ironic
Intensity score: | 0.210 | 8 | v_reg | 805 |
|
Task: Measure the intensity of sentiment or valence in the tweet, assigning it a score between 0 (highly negative) and 1 (highly positive).
Tweet: 13) mutual whos always online - @Lafa_YEET bc we have to bully her to get to sleep
Intensity score: | 0.419 | 4 | v_reg | 806 |
|
Task: Quantify the sentiment intensity or valence level of the tweet, giving it a score between 0 (highly negative) and 1 (highly positive).
Tweet: Stranger Things S2 25secs teaser! #excited 😲
Intensity score: | 0.891 | 8 | v_reg | 807 |
|
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: I'm extra lazy today 😟
Intensity score: | 0.317 | 7 | v_reg | 808 |
|
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: @weareremixes yeah he's delicious no need to threaten me
Intensity score: | 0.500 | 9 | v_reg | 809 |
|
Task: Determine the valence intensity of the tweeter's mental state on a scale of 0 (most negative) to 1 (most positive).
Tweet: Great start. Exciting new innovation = new challenges. @VisaSecurity #VSS2017 #brilliance
Intensity score: | 0.645 | 6 | v_reg | 810 |
|
Task: Gauge the intensity of sentiment or valence in the tweet, indicating a numerical value between 0 (extremely negative) and 1 (extremely positive).
Tweet: @KokuKokuBoo It's kay. They were my main healer/caster in HW...but not for SB (for now) sadly.
Intensity score: | 0.200 | 2 | v_reg | 811 |
|
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: trying my best to be happy :-)
Intensity score: | 0.617 | 0 | v_reg | 812 |
|
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: Any #GOP senator who refuses to #RepealAndReplace needs to bear the #wrath of their constituents @ polls home state! #healthcare #price2pay
Intensity score: | 0.347 | 7 | v_reg | 813 |
|
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: Ready to start my day after practising my daily #meditation.Today's focus was on #gratitude and there are so many things to be #grateful for
Intensity score: | 0.759 | 7 | v_reg | 814 |
|
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: @PaulCalafiore_ Absolutely ! Happy blessed Tuesday ❤️
Intensity score: | 0.947 | 0 | v_reg | 815 |
|
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: 2nd time this week I received services for free. It pays to be nice! #kindness #friendliness #bekind #smile
Intensity score: | 0.919 | 7 | v_reg | 816 |
|
Task: Determine the valence intensity of the tweeter's mental state on a scale of 0 (most negative) to 1 (most positive).
Tweet: @MarcMero Happy Anniversary!! Have a great day!!
Intensity score: | 0.911 | 6 | v_reg | 817 |
|
Task: Gauge the intensity of sentiment or valence in the tweet, indicating a numerical value between 0 (extremely negative) and 1 (extremely positive).
Tweet: A beautiful day starts with you being cheerful and letting the #joy of the #Lord spring out of you <3\n\nNelly Cruz
Intensity score: | 0.758 | 2 | v_reg | 818 |
|
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: I just tore my 2nd meniscus in 2 months what the fuck have you accomplished. But seriously, reaching maniacal laughter pain/WTF, self?-ness
Intensity score: | 0.305 | 3 | v_reg | 819 |
|
Task: Gauge the intensity of sentiment or valence in the tweet, indicating a numerical value between 0 (extremely negative) and 1 (extremely positive).
Tweet: @NRA The NRA deriding another sellout? #irony
Intensity score: | 0.467 | 2 | v_reg | 820 |
|
Task: Assess the sentiment intensity or valence level of the tweet, ranging from 0 (extremely negative) to 1 (extremely positive).
Tweet: @emilyhroderick Electronics also have foibles, personality faults, like to sulk and crash just like humans... switch off and desolder
Intensity score: | 0.534 | 1 | v_reg | 821 |
|
Task: Gauge the intensity of sentiment or valence in the tweet, indicating a numerical value between 0 (extremely negative) and 1 (extremely positive).
Tweet: #note8 #animated said pen. Amazing. Wife loves this one
Intensity score: | 0.741 | 2 | v_reg | 822 |
|
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: Do not linger too long near the howff or you risk the displeasure of a chuhaister with pubes more underwhelming than those of an aurochs.
Intensity score: | 0.281 | 0 | v_reg | 823 |
|
Task: Quantify the sentiment intensity or valence level of the tweet, giving it a score between 0 (highly negative) and 1 (highly positive).
Tweet: DC Young fly is hilarious man.
Intensity score: | 0.774 | 8 | v_reg | 824 |
|
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: @ledfordshyenne Little piggy 😂
Intensity score: | 0.581 | 5 | v_reg | 825 |
|
Task: Gauge the intensity of sentiment or valence in the tweet, indicating a numerical value between 0 (extremely negative) and 1 (extremely positive).
Tweet: This is the day that the lord has made I will rejoice and BE GLAD IN IT! 🙌🏿🌟 #blessed #favored #loved #
Intensity score: | 0.767 | 2 | v_reg | 826 |
|
Task: Gauge the intensity of sentiment or valence in the tweet, indicating a numerical value between 0 (extremely negative) and 1 (extremely positive).
Tweet: Stuck between a rock and a hard place #great
Intensity score: | 0.517 | 2 | v_reg | 827 |
|
Task: Determine the valence intensity of the tweeter's mental state on a scale of 0 (most negative) to 1 (most positive).
Tweet: i love his smile
Intensity score: | 0.741 | 6 | v_reg | 828 |
|
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: The formula of happiness rather than inertia. #elated
Intensity score: | 0.776 | 9 | v_reg | 829 |
|
Task: Quantify the sentiment intensity or valence level of the tweet, giving it a score between 0 (highly negative) and 1 (highly positive).
Tweet: A person #hates u for 1 of 3 reasons. They 1) want 2b U; 2) #hate themselves. 3) C U as a #threat. (& don't tell me hate doesn't exist!)
Intensity score: | 0.391 | 8 | v_reg | 830 |
|
Task: Gauge the intensity of sentiment or valence in the tweet, indicating a numerical value between 0 (extremely negative) and 1 (extremely positive).
Tweet: mum got out of a rlly bad car crash completely not injured and i found a rlly sentimental piece of jewellery i thought i'd lost #blessed
Intensity score: | 0.643 | 2 | v_reg | 831 |
|
Task: Gauge the intensity of sentiment or valence in the tweet, indicating a numerical value between 0 (extremely negative) and 1 (extremely positive).
Tweet: It's okay sus. Let that hurt go 🤗 * that's me hugging ya bitter ass * 😂😂😂
Intensity score: | 0.667 | 2 | v_reg | 832 |
|
Task: Assess the sentiment intensity or valence level of the tweet, ranging from 0 (extremely negative) to 1 (extremely positive).
Tweet: oh no now that i'm back home i actually have to figure out what i'm gonna do with my life #brilliant 😟
Intensity score: | 0.407 | 1 | v_reg | 833 |
|
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: @edgeoforever @docrocktex26 I think I speak for all when I say 'not until @ggreenwald agrees!' Or at least, 'yeah but Clinton...' #sarcasm
Intensity score: | 0.383 | 3 | v_reg | 834 |
|
Task: Measure the intensity of sentiment or valence in the tweet, assigning it a score between 0 (highly negative) and 1 (highly positive).
Tweet: Life is great. #sarcasm
Intensity score: | 0.607 | 4 | v_reg | 835 |
|
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: Just a side #thought, everything takes #time and #effort ... #annoyed
Intensity score: | 0.323 | 3 | v_reg | 836 |
|
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: Just added a copy of CANDIDE to my local Little Free Library & a guy grabbed it literally 5 seconds later #optimism #BestOfAllPossibleWorlds
Intensity score: | 0.567 | 5 | v_reg | 837 |
|
Task: Quantify the sentiment intensity or valence level of the tweet, giving it a score between 0 (highly negative) and 1 (highly positive).
Tweet: @Mike_J_Lord You're welcome 😃
Intensity score: | 0.603 | 8 | v_reg | 838 |
|
Task: Assess the sentiment intensity or valence level of the tweet, ranging from 0 (extremely negative) to 1 (extremely positive).
Tweet: Why hasn't my alarm gone off... 🤔😩⏰
Intensity score: | 0.344 | 1 | v_reg | 839 |
|
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: Just finished writing 'thunder' on a graphic as thunder occurred #ironic
Intensity score: | 0.517 | 0 | v_reg | 840 |
|
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: @JYSexton Lucky you aren't a biased Lib-tard. All your tweets seem super-unbiased and legit. #sarcasm
Intensity score: | 0.516 | 7 | v_reg | 841 |
|
Task: Gauge the intensity of sentiment or valence in the tweet, indicating a numerical value between 0 (extremely negative) and 1 (extremely positive).
Tweet: @COFFEECOWal Really Sad News, it's been a pleasure over the years, all the best for the future.
Intensity score: | 0.339 | 2 | v_reg | 842 |
|
Task: Determine the valence intensity of the tweeter's mental state on a scale of 0 (most negative) to 1 (most positive).
Tweet: Today is already off to a great start..... 🙄
Intensity score: | 0.786 | 6 | v_reg | 843 |
|
Task: Quantify the sentiment intensity or valence level of the tweet, giving it a score between 0 (highly negative) and 1 (highly positive).
Tweet: @fuzzbish @LouiseMensch @realDonaldTrump Ha ha! Trump supporter calls someone else a narcissist! #irony
Intensity score: | 0.422 | 8 | v_reg | 844 |
|
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: @KerryKatona7 Stunner cute like her mum 😃
Intensity score: | 0.810 | 5 | v_reg | 845 |
|
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: @NCSNorthEast @NCS It'll start on Sunday when the first groups depart :)
Intensity score: | 0.531 | 9 | v_reg | 846 |
|
Task: Quantify the sentiment intensity or valence level of the tweet, giving it a score between 0 (highly negative) and 1 (highly positive).
Tweet: @NationalGeoAr Waw so loyal and honorable 😒 #sarcasm
Intensity score: | 0.379 | 8 | v_reg | 847 |
|
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: TARED tabby abaci rabid each dabs
Intensity score: | 0.264 | 3 | v_reg | 848 |
|
Task: Gauge the intensity of sentiment or valence in the tweet, indicating a numerical value between 0 (extremely negative) and 1 (extremely positive).
Tweet: Just tried @GoodmanBakery for the 1st time... GF for 13 yrs & these are some of the best baked goods I've ever had! DF is a bonus! #yummy
Intensity score: | 0.845 | 2 | v_reg | 849 |
|
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: @DOBrienAJC What did you do to rile up all the Roberts?
Intensity score: | 0.429 | 3 | v_reg | 850 |
|
Task: Quantify the sentiment intensity or valence level of the tweet, giving it a score between 0 (highly negative) and 1 (highly positive).
Tweet: Life is a #blessing
Intensity score: | 0.783 | 8 | v_reg | 851 |
|
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: Thank you for sending random kind people into my life when I need them the most #smiling #grateful
Intensity score: | 0.859 | 0 | v_reg | 852 |
|
Task: Assess the sentiment intensity or valence level of the tweet, ranging from 0 (extremely negative) to 1 (extremely positive).
Tweet: never had a dull moment with u guys 💕
Intensity score: | 0.767 | 1 | v_reg | 853 |
|
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: @cnn please get Sebstian Gorka off of my tv. The whole trump admin. needs to stop deflecting by talking about Hillary. #awful
Intensity score: | 0.194 | 7 | v_reg | 854 |
|
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: I'm the wholesome drunk that sends people memes and compliments them at 2am on snap
Intensity score: | 0.743 | 9 | v_reg | 855 |
|
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: I feel like it's taken me like 6 months to understand what net neutrality is but like...fucking capitalists I'm
Intensity score: | 0.258 | 0 | v_reg | 856 |
|
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: Up early. Kicking ass and taking names. #offense.
Intensity score: | 0.603 | 0 | v_reg | 857 |
|
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: if jk realize what taehyung did can he do that to taehyung as a revenge? i would love to
Intensity score: | 0.483 | 7 | v_reg | 858 |
|
Task: Quantify the sentiment intensity or valence level of the tweet, giving it a score between 0 (highly negative) and 1 (highly positive).
Tweet: 'Too often we give children answers to remember rather than problems to solve' Roger Lewin Terrific :) Tuesday
Intensity score: | 0.411 | 8 | v_reg | 859 |
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Task: Assess the sentiment intensity or valence level of the tweet, ranging from 0 (extremely negative) to 1 (extremely positive).
Tweet: Well. At least #DonaldTrumpJr is finally the headline. The least of the #Trump children. Finally stepping up. #sarcasm
Intensity score: | 0.468 | 1 | v_reg | 860 |
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Task: Determine the valence intensity of the tweeter's mental state on a scale of 0 (most negative) to 1 (most positive).
Tweet: @eavesdropann My pleasure my dear. 😘
Intensity score: | 0.821 | 6 | v_reg | 861 |
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Task: Gauge the intensity of sentiment or valence in the tweet, indicating a numerical value between 0 (extremely negative) and 1 (extremely positive).
Tweet: The #buthisemails meme is hilarity.
Intensity score: | 0.694 | 2 | v_reg | 862 |
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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: Maggie Smith does not get the credit she deserves 😂 hilarious and brilliant actress!
Intensity score: | 0.900 | 9 | v_reg | 863 |
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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: @dwarsrivier_SA Welcome to the industry fellow #guides! Expect a future of #excitement, #hairraising tales and just allround #fun! :D
Intensity score: | 0.806 | 9 | v_reg | 864 |
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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: You turned my world with a smile, and you take my heart with a kiss
Intensity score: | 0.823 | 9 | v_reg | 865 |
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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: @GarimaGupta1508 @SHEROESIndia missing it! Look forward to seeing you all in #Bangalore soon 😀
Intensity score: | 0.734 | 5 | v_reg | 866 |
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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: @SylvesterTurner @HoustonMatters With all the other stuff going on in houston #crime you spend your time bullying the homeless #wonderful
Intensity score: | 0.259 | 7 | v_reg | 867 |