Latvian user comment dataset 1.0

  Authors

Shekhar, Ravi ; Purver, Matthew ; Pollak, Senja ; Pelicon, Andraž and Krustok, Ivar

  Item identifier

http://hdl.handle.net/11356/1407

 Project URL

http://embeddia.eu/

 Referenced by

https://www.aclweb.org/anthology/2021.hackashop-1.14.pdf

 Date issued

2021-04-19

 Type

corpus, text

 Size

12412463 texts

 Language(s)

Latvian , Russian

 Description

The dataset is an archive of reader comments from the Delfi news site from 2014-2019, containing approximately 12M comments, mostly in the Latvian language, with some in Russian. Description of the Datasets There are 6 CSV files: * ``lv-comments-2014.csv`` contains **2 753 655** comments from year 2014 * ``lv-comments-2015.csv`` contains **2 221 122** comments from year 2015 * ``lv-comments-2016.csv`` contains **1 897 669** comments from year 2016 * ``lv-comments-2017.csv`` contains **1 896 083** comments from year 2017 * ``lv-comments-2018.csv`` contains **2 222 051** comments from year 2018 * ``lv-comments-2019.csv`` contains **1 421 883** comments from year 2019 **In sum: 12 412 463 comments** Columns: * ``comment_id`` (string) - the ID of the written comment * ``article_id`` (string) - the ID of the article for which the comment was written * ``created_time`` (string) - the time and date of the comment * ``subject`` (string) - the title of the comment * ``reply_to_comment_id`` (string) - the parent comments ID * ``content`` (string) - the comment itself * ``is_anonymous`` (string) - * 1 if the comment was published anonymously * 0 if the comment was published by a registered user * ``is_enabled`` (string) - * 1 if the comment was published (online) * 0 if it wasn’t published * Questionable field: not all have been manually moderated * No additional information from the moderators * ``channel_language`` (string) - the language of the channel * 'nat' for Latvian * 'rus' for Russian * ``create_user_id`` (string) - the user ID of the commentator * ``modereted_by`` (string) - the ID of the moderator

 Publisher

Ekspress Meedia Group

 Acknowledgement

European Union EC/H2020/825153 "EMBEDDIA - Cross-Lingual Embeddings for Less-Represented Languages in European News Media"

 Subject(s)

user comment offensive language comment moderation

 Collection(s)

CLARIN.SI data & tools

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