TextDetox Multilingual Toxicity — Japanese

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.

#Detoxification#Japanese language#Pan clef#Shared task#Textdetox

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Analytics

Content metrics

5,000 records scored

is toxic50.0% true
true 50.0%false 50.0%
-2.4
Flesch–Kincaid grade
US school grade level
41.1
Automated readability index
Frequent terms
h30しかしだからというかチン力スネトウヨそうそうそしてつまりなるほどあれはだよね確かに゚д゚うーんそういやそりゃあホント韓国は韓国政府2019年7月16日16いやいやこれはそうだなそもそもそれともそれなそれにしてもなんかマジで同じく徴用工問題の第三国仲裁について受け入れられない2chetcいいねいらっしゃいしかもじゃあすまぬそうなのそりゃだってなんというかやっぱりオンラインヒント関わるな20代で死ぬやつもいるし20時以降は喫煙okとかさ222
Topic clusters

Topic 0

゚д゚
はい
次は
いやいや
いや
あれは
なるほど
まあ

Topic 1

韓国
04
韓国政府
id
もう
つまり
でも
反日

Topic 2

とか
まあ
外交
自由と責任は表裏一体
事件
だけ
ほんとそれ
テレビ

Topic 3

市民
すげー
twitter
今日
17
香山リカ
大丈夫
へー

Topic 4

あれ
なるほどな
わかる
どうやら
急いでカロリーメートをパサパサするけど水も買っておいてよかった
なんというか
なんか
それとも

Topic 5

ネトウヨ
23
捏造
以前
予報士がー
テレビ
とも思ったが
みんな

Topic 6

しかし
53
どうやら
ていうか
02
じゃ
速攻で
etc

Topic 7

それとも
近く
68
ありがとう
53
ほんとそう
31
うむ
Top hashtags
#walkaway1

Computed over the full corpus.

Record

Catalog key
textdetox-ja
Authors
Dementieva, Daryna; Moskovskiy, Daniil; Logacheva, Varvara; Dale, David; Ustalov, Dmitry; Panchenko, Alexander
Year
2024
Source paper
Overview of the Multilingual Text Detoxification Task at PAN 2024
DOI / arXiv
10.1007/978-3-031-71908-0_11
License
OpenRAIL++ (Hugging Face card) (LicenseRef-OpenRAIL-plus-plus)
Records
5,000
Languages
ja
Collected
2024 (2020s)
Tasks
Toxicity detection (binary; is_toxic) inferred
Region
East Asia (inferred: from the language of the data)

Provenance

Originally published at
https://huggingface.co/datasets/textdetox/multilingual_toxicity_dataset link checked
Hosted copy
Mirrored on echo.directory on 2026-10-02, 440.6 KB across 1 files. Checksums in MANIFEST.json.

Citations

Overview of PAN 2024: Multi-author Writing Style Analysis, Multilingual Text Detoxification, Oppositional Thinking Analysis, and Generative AI Authorship Verification Condensed Lab Overview
A. Ayele, N. Babakov, Janek Bevendorff, Xavier Bonet Casals, Berta Chulvi
Journal Article · Conference and Labs of the Evaluation Forum · 2024

26
citations
cited
2
influential citations
8% of all citations

Cited by

Show all 10

Citation data from Semantic Scholar, retrieved 2026-10-19.

How to cite

BibTeX

@misc{echo2026,
  title  = {ECHO: Exploratory Compendium of Humanity Online},
  author = {Switzer, Braden and Zafarani, Reza},
  year   = {2026},
  url    = {https://echo.directory},
  note   = {Syracuse University}
}

@inproceedings{dementieva2024overview,
  title     = {Overview of the Multilingual Text Detoxification Task at PAN 2024},
  author    = {Dementieva, Daryna and others},
  booktitle = {CLEF 2024 Working Notes},
  year      = {2024}
}

APA

Switzer, B., & Zafarani, R. (2026). ECHO: Exploratory Compendium of Humanity Online [Data repository]. Syracuse University. https://echo.directory

Dementieva, D., Moskovskiy, D., Logacheva, V., Dale, D., Ustalov, D., & Panchenko, A. (2024). TextDetox Multilingual Toxicity — Japanese [Data set]. https://doi.org/10.1007/978-3-031-71908-0_11

MLA

Switzer, Braden, and Reza Zafarani. ECHO: Exploratory Compendium of Humanity Online. Syracuse University, 2026, echo.directory.

Dementieva, Daryna, et al. TextDetox Multilingual Toxicity — Japanese. 2024, doi.org/10.1007/978-3-031-71908-0_11.

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