Ja

8 datasets tagged as the language “Ja”.

8 datasets.

COVID-19-TweetIDs (Ongoing Collection) Limited

A twitter dataset of 2.7B+ tweet IDs across 9+ languages (ongoing collection since Jan 2020), collected by Chen, Lerman, and Ferrara (USC Information Sciences Institute). Each record contains tweet IDs only — full content requires hydration. Largest ongoing COVID-19 Twitter collection with multilingual coverage and continuous updates since pandemic onset. Suitable for pandemic discourse, public health surveillance, infodemic analysis, multilingual NLP.

2.8B records2020

YTCommentVerse: Multi-Category YouTube Comment Corpus Analyzed

A YouTube (multi-category comment corpus) dataset of 40,824,926 comments from 20,568,637 unique commenters across 178,027 videos, collected by YTCommentVerse project team via YouTube Data API. Each record contains hashed video ID, hashed commenter channel ID, comment text, vote count, video category (entertainment/gaming/news/music/etc.). YTCommentVerse contains 40,824,926 YouTube comments spanning 25 categories with privacy-preserving hashed identifiers, enabling large-scale multilingual comment analysis. Suitable for YouTube comment analysis, multilingual NLP, engagement research, content moderation, commenter behavior modeling, cross-category platform analysis.

40.8M records20.7M nodes40.8M edges2025

MADOC: Bluesky / bluesky Analyzed

A MADOC (Bluesky, bluesky) dataset of 164,265 users and 894,917 reply edges from 2,814,352 interactions, collected by Dankulov et al. via platform APIs, published at ICWSM 2025. Each record contains user-user reply edges, post and comment text, per-record sentiment scores (VADER and TextBlob), subjectivity scores, and toxicity scores (ToxiGen). The dataset is notable for its FAIR-compliant dataset with pre-computed NLP quality labels (sentiment, subjectivity, toxicity) per record, enabling network analysis and content quality research without additional annotation. Intended for research into social network analysis, toxicity detection, cross-platform community dynamics, misinformation research, and hate speech propagation studies.

2.8M records164.3K nodes894.9K edges2025

2 Million Bluesky Posts Analyzed

A Bluesky Social dataset of approximately 1.8 million public posts, collected by Alpin Dale from the AT Protocol firehose API in 2024. Each record contains post text, author handle, timestamp, image presence flag, and reply-to URI for constructing directed reply-thread networks. multilingual corpus from a decentralized AT Protocol platform with English dominant alongside Spanish, Portuguese, Japanese, and other languages. Suitable for decentralized social media analysis, reply network structure, and multilingual content modeling.

1.9M records1.3M nodes929.3K edges2024

Wikipedia Hyperlinks (Japanese) Analyzed

The wikilink network of the Japanese Wikipedia, as distributed by KONECT (wikipedia_link_ja), built from the Wikimedia dumps: 1,610,638 articles and 71,055,717 directed links between them, where a link from A to B means article A links to article B (article namespace only; 6,153 pages link to themselves). Counts are those of ECHO's copy of the KONECT archive; KONECT's current release lists 1,767,268 articles and 83,202,622 links, including articles without links. One of eight language editions on ECHO (English, German, French, Italian, Japanese, Polish, Portuguese, Russian). Useful for knowledge-graph and hyperlink-structure analysis, link prediction, community detection and comparison across language editions.

1.6M records1.6M nodes71.1M edges2013

Stack Exchange — ja.stackoverflow.com Analyzed

A Stack Exchange (ja.stackoverflow.com) dataset of 11,176 users, 23,490 answer-collaboration edges, 31,119 questions, 36,454 answers, collected by Stack Exchange, Inc. via the annual Stack Exchange Data Dump. Each record contains user nodes (reputation, badge counts, vote history), directed weighted edges (answerer→asker, weight=answer score, count=interactions, accepted=bool), post text, tag distribution. User collaboration network from ja.stackoverflow.com — directed weighted graph where edges represent knowledge-sharing relationships (A answered B's question), with edge weight reflecting answer quality. Enables prestige hierarchy, community detection, and expertise flow analysis.. Suitable for expertise network analysis, reputation systems, community detection, knowledge flow, PageRank-based authority ranking, Q&A platform dynamics..

176K records11.2K nodes23.5K edges2025

TextDetox Multilingual Toxicity Dataset (All Languages) Analyzed

A TextDetox 2024/2025 shared task (15 languages) dataset of 71,374 posts across 15 languages with binary toxicity labels, collected by Dementieva et al. for PAN/CLEF TextDetox 2024. Each record contains post text, binary toxicity label (0=non-toxic, 1=toxic), language. Combined multilingual toxicity benchmark covering 15 languages including low-resource languages (Amharic, Tatar, Hindglish) — 71,374 balanced samples total. Suitable for multilingual toxicity detection, cross-lingual transfer learning, low-resource NLP, content moderation benchmarking.

71.4K records2024

TextDetox Multilingual Toxicity — Japanese Analyzed

A TextDetox 2024 shared task (Japanese) dataset of 5,000 Japanese posts (2,500 toxic, 2,500 non-toxic), collected by Dementieva et al. for PAN/CLEF TextDetox 2024. Each record contains post text, binary toxicity label (0=non-toxic, 1=toxic). TextDetox Japanese provides 5,000 balanced binary toxicity annotations — part of a 15-language multilingual benchmark for cross-lingual toxicity detection research. Suitable for toxicity detection, multilingual content moderation, cross-lingual NLP, hate speech classification, text detoxification.

5K records2024