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 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 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 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.
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