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index (int32)hashtag (string)segmentation (string)
0
"AajKiBaat"
"Aaj Ki Baat"
1
"soldoutABP"
"soldout ABP"
2
"DemocracyOcuupier"
"Democracy Ocuupier"
3
"HarbaarModisarkaar"
"Harbaar Modisarkaar"
4
"MemoriesToCherish"
"Memories To Cherish"
5
"TandurMLA"
"Tandur MLA"
6
"GoodBeerWeek"
"Good Beer Week"
7
"Capres02TukangTeror"
"Capres 02 Tukang Teror"
8
"FackMissionShakti"
"Fack Mission Shakti"
9
"FarkDikhRahaHai"
"Fark Dikh Raha Hai"
10
"ArmyDogs"
"Army Dogs"
11
"HitlarJihadi"
"Hitlar Jihadi"
12
"VisMaVie"
"Vis Ma Vie"
13
"LakshyHamaraModiDubara"
"Lakshy Hamara Modi Dubara"
14
"MainBhiCHOwkidaR"
"Main Bhi CH Owkida R"
15
"MaharashtraKalyanLokSabhaPradhanUddhavThakre"
"Maharashtra Kalyan Lok Sabha Pradhan Uddhav Thakre"
16
"MachinesRCompromised"
"Machines R Compromised"
17
"KodiRamaKrishna"
"Kodi Rama Krishna"
18
"KickOutRoGo"
"Kick Out Ro Go"
19
"EliminacaoPowerCouple"
"Eliminacao Power Couple"
20
"VoteBecauseYouCan"
"Vote Because You Can"
21
"SWoB"
"S Wo B"
22
"BombaySux"
"Bombay Sux"
23
"SupportDrArunSawant"
"Support Dr Arun Sawant"
24
"GadarekPremKatha"
"Gadarek Prem Katha"
25
"TraitorousTrump"
"Traitorous Trump"
26
"VotForVBA"
"Vot For VBA"
27
"AmjadKhan"
"Amjad Khan"
28
"JayshriRammamtadidi"
"Jayshri Rammamtadidi"
29
"WestminsterCourt"
"Westminster Court"
30
"TuesdayFeelings"
"Tuesday Feelings"
31
"WhySoShy"
"Why So Shy"
32
"unemployedIndia"
"unemployed India"
33
"2xThrashing"
"2 x Thrashing"
34
"ModiFied"
"Modi Fied"
35
"LootyensKePadheLikhe"
"Lootyens Ke Padhe Likhe"
36
"HeartHeart"
"Heart Heart"
37
"PMModiinBengal"
"PM Modiin Bengal"
38
"ChaukidarChorhai"
"Chaukidar Chorhai"
39
"JaydevGaykwad"
"Jaydev Gaykwad"
40
"InvestInYou"
"Invest In You"
41
"TakingTheJobSeriously"
"Taking The Job Seriously"
42
"HomelessnessIsNotNormal"
"Homelessness Is Not Normal"
43
"WarrenHasAPlanForThat"
"Warren Has A Plan For That"
44
"NairHospital"
"Nair Hospital"
45
"SoniaGandgi"
"Sonia Gandgi"
46
"SidhiLokSabhaSeat"
"Sidhi Lok Sabha Seat"
47
"DynPro"
"Dyn Pro"
48
"ApsaraRajahmundry"
"Apsara Rajahmundry"
49
"MainNahichowkidaar"
"Main Nahichowkidaar"
50
"IndiaVsCorruptMahagthbandan"
"India Vs Corrupt Mahagthbandan"
51
"delhiMCD"
"delhi MCD"
52
"ModiWaveElec"
"Modi Wave Elec"
53
"LokShabhaElections"
"Lok Shabha Elections"
54
"WhiteOldMen"
"White Old Men"
55
"CostofViraatvacation"
"Costof Viraatvacation"
56
"MalikRiaz"
"Malik Riaz"
57
"DerSpiegel"
"Der Spiegel"
58
"ugIns"
"ug Ins"
59
"PowerProject"
"Power Project"
60
"SamCooke"
"Sam Cooke"
61
"AntuNationals"
"Antu Nationals"
62
"20RupeesCoin"
"20 Rupees Coin"
63
"HampdenSurvey"
"Hampden Survey"
64
"MITEFArab"
"MITEF Arab"
65
"DDNewsGujararti"
"DD News Gujararti"
66
"confusedRajdeep"
"confused Rajdeep"
67
"VIPs"
"VI Ps"
68
"MainBhiBagga"
"Main Bhi Bagga"
69
"MaiBhiChaukidar"
"Mai Bhi Chaukidar"
70
"ScreenShotSaturday"
"Screen Shot Saturday"
71
"igersOttawa"
"igers Ottawa"
72
"RahulPriyankaatKozhikodeAirport"
"Rahul Priyankaat Kozhikode Airport"
73
"JamshedpurinNews"
"Jamshedpurin News"
74
"SeparateBranch"
"Separate Branch"
75
"indiaExposedAtBalakot"
"india Exposed At Balakot"
76
"DataAnalytics"
"Data Analytics"
77
"04LimitedSazabys"
"04 Limited Sazabys"
78
"RahulTripathiYouth"
"Rahul Tripathi Youth"
79
"CJreform"
"C Jreform"
80
"LanguageWars"
"Language Wars"
81
"CBSEPaperLeak"
"CBSE Paper Leak"
82
"Vote4KPG"
"Vote 4 KPG"
83
"ModiChorHaiSaysIndia"
"Modi Chor Hai Says India"
84
"PleaseSupport"
"Please Support"
85
"LandReform"
"Land Reform"
86
"SalutePakArmy"
"Salute Pak Army"
87
"TrafficMonthUPP"
"Traffic Month UPP"
88
"UdyogVihar"
"Udyog Vihar"
89
"PostDev"
"Post Dev"
90
"ChangeAmericaByVoting"
"Change America By Voting"
91
"PandavVsKaurav"
"Pandav Vs Kaurav"
92
"MamathaWitch"
"Mamatha Witch"
93
"EKPostNamoKeNaam"
"EK Post Namo Ke Naam"
94
"FastestGrowing"
"Fastest Growing"
95
"NamoGoodies"
"Namo Goodies"
96
"MYVoiceMyChoice"
"MY Voice My Choice"
97
"AadhaarThug"
"Aadhaar Thug"
98
"NoToRacism"
"No To Racism"
99
"AkalshwaniShimla"
"Akalshwani Shimla"
End of preview (truncated to 100 rows)

Dataset Card for HashSet Distant

Dataset Summary

Hashset is a new dataset consisiting on 1.9k manually annotated and 3.3M loosely supervised tweets for testing the efficiency of hashtag segmentation models. We compare State of The Art Hashtag Segmentation models on Hashset and other baseline datasets (STAN and BOUN). We compare and analyse the results across the datasets to argue that HashSet can act as a good benchmark for hashtag segmentation tasks.

HashSet Distant: 3.3M loosely collected camel cased hashtags containing hashtag and their segmentation.

Languages

Hindi and English.

Dataset Structure

Data Instances

{
  'index': 282559, 
  'hashtag': 'Youth4Nation', 
  'segmentation': 'Youth 4 Nation'
}

Dataset Creation

  • All hashtag segmentation and identifier splitting datasets on this profile have the same basic fields: hashtag and segmentation or identifier and segmentation.

  • The only difference between hashtag and segmentation or between identifier and segmentation are the whitespace characters. Spell checking, expanding abbreviations or correcting characters to uppercase go into other fields.

  • There is always whitespace between an alphanumeric character and a sequence of any special characters ( such as _ , :, ~ ).

  • If there are any annotations for named entity recognition and other token classification tasks, they are given in a spans field.

Additional Information

Citation Information

@article{kodali2022hashset,
  title={HashSet--A Dataset For Hashtag Segmentation},
  author={Kodali, Prashant and Bhatnagar, Akshala and Ahuja, Naman and Shrivastava, Manish and Kumaraguru, Ponnurangam},
  journal={arXiv preprint arXiv:2201.06741},
  year={2022}
}

Contributions

This dataset was added by @ruanchaves while developing the hashformers library.

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