tweet_id
stringlengths
19
19
assessment_option_id
class label
6 classes
1227261586521382913
063
1227435952961937413
265
1227510231569092610
063
1227527803312099328
063
1227549055724617728
467
1227594592863670279
265
1227595738747568129
164
1227603508276285440
467
1227729455323287552
063
1227742982725459969
164
1227744999346855936
063
1227751052566507520
164
1227778691352027136
164
1227756700934893568
063
1227802369037144064
265
1227764390104952832
164
1227812171125608448
265
1227824489376841731
164
1227843181267439617
063
1227874191065505792
063
1227884272050065408
265
1227876756696096768
063
1227878745651810304
063
1227906715871367168
265
1227921022118031360
265
1227924164192997378
063
1227924575117172736
265
1227925318020714496
265
1227930050466471938
265
1227934961254035457
265
1227941510609395713
265
1227946444155260936
265
1227968465153085441
265
1227969077521436673
265
1228099475916222465
265
1228115439017811970
265
1228259114481963008
265
1228473218601648128
063
1228556962075271171
265
1228575080629751808
063
1228645157802663936
063
1228705161096376321
063
1228817778578083841
063
1228840970143199233
265
1228861728173113345
265
1228869995146268672
265
1228873706266484737
265
1228884785939902464
063
1229193731242250241
265
1229196263343742979
063
1229337299332165632
265
1229264320539680768
265
1229316406665076736
265
1229320315336941573
265
1229349483365851136
265
1229410213113016322
063
1229413939332567041
265
1229418193585729537
063
1229557231017873408
265
1229628421778460672
265
1229473885164163073
063
1227956053012185088
265
1229523729853476864
063
1229087148944449536
063
1228712902942527490
265
1229001633796784135
265
1229705968167948288
063
1229730941892825088
265
1229734848467591168
265
1229862419901509633
063
1229864387449475072
063
1230122900021137408
265
1229901413926309888
265
1229943276855148545
063
1229951524115107840
265
1229964721492639750
063
1229989209936547841
265
1230001284498903040
265
1230054506861170688
265
1230053412567281665
063
1230059197502353409
265
1230129311794941952
063
1230280383553343488
265
1230284909626806273
265
1230324902315474944
265
1227898808006144000
063
1227910592662405121
063
1227922124716662785
063
1227922445958410240
063
1227926053739323392
063
1227935035291914240
063
1227879261253464064
265
1227938852829986816
063
1227941718797897728
265
1229215897300037632
063
1228891301791186944
063
1229389659765125121
063
1229691650391379968
063
1228648946097999873
265
1230316904197132288
265

Dataset Card for COVID-19 日本語Twitterデータセット (COVID-19 Japanese Twitter Dataset)

Dataset Summary

53,640 Japanese tweets with annotation if a tweet is related to COVID-19 or not. The annotation is by majority decision by 5 - 10 crowd workers. Target tweets include "COVID" or "コロナ". The period of the tweets is from around January 2020 to around June 2020. The original tweets are not contained. Please use Twitter API to get them, for example.

Supported Tasks and Leaderboards

Text-classification, Whether the tweet is related to COVID-19, and whether it is fact or opinion.

Languages

The text can be gotten using the IDs in this dataset is Japanese, posted on Twitter.

Dataset Structure

Data Instances

CSV file with the 1st column is Twitter ID and the 2nd column is assessment option ID.

Data Fields

  • tweet_id: Twitter ID.
  • assessment_option_id: The selection result. It has the following meanings:
    • 63: a general fact: generally published information, such as news.
    • 64: a personal fact: personal news. For example, a person heard that the next-door neighbor, XX, has infected COVID-19, which has not been in a news.
    • 65: an opinion/feeling
    • 66: difficult to determine if they are related to COVID-19 (it is definitely the tweet is not "67: unrelated", but 63, 64, 65 cannot be determined)
    • 67: unrelated
    • 68: it is a fact, but difficult to determine whether general facts, personal facts, or impressions (it may be irrelevant to COVID-19 since it is indistinguishable between 63 - 65 and 67).

Data Splits

No articles have been published for this dataset, and it appears that the author of the dataset is willing to publish an article (it is not certain that the splitting information will be included). Therefore, at this time, information on data splits is not provided.

Dataset Creation

Curation Rationale

[More Information Needed] because the paper is not yet published.

Source Data

Initial Data Collection and Normalization

53,640 Japanese tweets with annotation if a tweet is related to COVID-19 or not. Target tweets include "COVID" or "コロナ". The period of the tweets is from around January 2020 to around June 2020.

Who are the source language producers?

The language producers are users of Twitter.

Annotations

Annotation process

The annotation is by majority decision by 5 - 10 crowd workers.

Who are the annotators?

Crowd workers.

Personal and Sensitive Information

The author does not contain original tweets.

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

The dataset is hosted by Suzuki Laboratory, Gifu University, Japan.

Licensing Information

CC-BY-ND 4.0

Citation Information

A related paper has not yet published. The author shows how to cite as「鈴木 優: COVID-19 日本語 Twitter データセット ( http://www.db.info.gifu-u.ac.jp/data/Data_5f02db873363f976fce930d1 ) 」.

Contributions

Thanks to @forest1988 for adding this dataset.

Downloads last month
73

Models trained or fine-tuned on community-datasets/covid_tweets_japanese