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.
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.
A Twitter (#NoMore hashtag campaign) dataset of 1,048,574 tweets from the Ethiopian #NoMore movement (2021-11 to 2022-08), collected by Zenodo contributors via Twitter API. Each record contains tweet text, language, timestamp; Amharic+English bilingual subset also available. 1,048,574 tweets covering the #NoMore solidarity movement in Ethiopia and Eritrea — one of few African social movement datasets with Amharic content, spanning 2021-11 to 2022-08. Suitable for African social movement analysis, multilingual NLP, Amharic text processing, political communication research, hashtag activism, Global South social media studies.
A Wikipedia (Portuguese edition talk pages) dataset of 541,355 nodes and 1,463,308 edges, collected by KONECT via Wikipedia XML dumps. Each record contains directed: True, weighted: True, signed: False, temporal: True. Directed temporal network of Wikipedia Portuguese talk page interactions between editors.. Suitable for wiki collaboration analysis, multilingual network analysis.
A Wikipedia (Spanish edition talk pages) dataset of 497,446 nodes and 1,250,097 edges, collected by KONECT via Wikipedia XML dumps. Each record contains directed: True, weighted: True, signed: False, temporal: True. Directed temporal network of Wikipedia Spanish talk page interactions between editors.. Suitable for wiki collaboration analysis, multilingual network analysis.
A Livemocha (language learning community) dataset of 104,103 users and 2,193,083 friendship edges, collected by Xia Hu (Ben) via Livemocha crawl, December 2010. Each record contains user-user friendship edges. The dataset is notable for its friendship network of the world's largest online language learning community, with 6M+ members across 200+ countries. Intended for research into social network analysis, community detection, and cross-cultural interaction studies.
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.
A Twitter (OffensEval 2020 — 5 languages) dataset of 61,922 tweets across 5 languages with offensive/non-offensive labels, collected by Zampieri et al. for SemEval-2020 Task 12. Each record contains tweet text, binary offensive label (OFF/NOT), language, split. Combined OffensEval 2020 benchmark across Arabic, Danish, English, Greek, and Turkish — 61,922 tweets from the most-participated SemEval task ever (528 teams). Suitable for multilingual offensive language detection, cross-lingual transfer, content moderation, NLP benchmarking.
A Twitter (Nigerian language communities) dataset of 60,823 tweet IDs across 4 Nigerian languages with sentiment labels, collected by Muhammad et al. via Twitter API (2022). Each record contains tweet ID, sentiment label (positive/negative/neutral), language, split (train/dev/test). First large-scale sentiment corpus for Nigerian languages — 60,823 annotated tweet IDs across Hausa, Igbo, Yoruba, and Nigerian Pidgin, enabling low-resource African NLP research.. Suitable for low-resource NLP, African language sentiment analysis, multilingual classification, cross-lingual transfer..
A Twitch.tv (live streaming platform) dataset of 34,118 users and 214,556 undirected friendship edges across 6 language communities (DE, ENGB, ES, FR, PTBR, RU) merged into one cumulative graph, collected by Rozemberczki et al. via Twitch API, distributed via MUSAE/SNAP. Each record contains undirected friendship edges between Twitch streamers within each language community; node IDs namespaced by language to avoid collision across subgraphs. The dataset is notable for its multilingual streaming platform social network covering 6 distinct language communities, enabling cross-community structural comparison and multilingual graph embedding research. Intended for research into community detection, graph embedding, node classification, cross-platform social network analysis, and multilingual network comparison.
A Multi-Platform (Social Media) dataset of 26,985 bilingual (Malay-English) social media posts, collected by Mendeley Data. Each record contains text, label (hate/non-hate), language. Balanced bilingual Malay-English hate speech dataset with cleaned text. Suitable for hate speech detection, multilingual NLP, content moderation.
A TextDetox 2024 shared task (Amharic) dataset of 5,000 Amharic 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 Amharic 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.
A TextDetox 2024 shared task (Spanish) dataset of 5,000 Spanish 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 Spanish 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.
A TextDetox 2024 shared task (Tatar) dataset of 5,000 Tatar 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 Tatar 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.
A TextDetox 2024 shared task (Hindglish) dataset of 4,363 Hindglish posts (2,200 toxic, 2,163 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 Hindglish provides 4,363 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.
A Unicode CLDR language data dataset of 868 nodes and 1,255 edges, collected by KONECT via Unicode CLDR. Each record contains directed: False, weighted: True. Bipartite weighted network of languages and Unicode scripts, with edge weights representing similarity scores.. Suitable for linguistic network analysis, language typology, script similarity.