Global Civil Unrest on Twitter (G-CUT) [Full]

We collected geotagged tweets from the Twitter streaming API from 2014 to 2019 (inclusive) for 42 countries from Africa, the Middle East, and Southeast Asia. Only English tweets are included (as identified by langid). This release is the entire dataset. Used in the following papers: Abhinav Chinta, Jingyu Zhang, Alexandra DeLucia, Mark Dredze, and Anna L. Buczak. 2021. Study of Manifestation of Civil Unrest on Twitter. In Proceedings of the Seventh Workshop on Noisy User-generated Text (W-NUT 2021), pages 396–409, Online. Association for Computational Linguistics. Alexandra DeLucia, Mark Dredze, and Anna L. Buczak. 2023. A Multi-instance Learning Approach to Civil Unrest Event Detection on Twitter. In Proceedings of the 6th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text, pages 18–33, Varna, Bulgaria. INCOMA Ltd., Shoumen, Bulgaria.   Please cite the Chinta et al 2021 paper if you use this dataset: @inproceedings{chinta-etal-2021-study,    title = "Study of Manifestation of Civil Unrest on {T}witter",    author = "Chinta, Abhinav  and      Zhang, Jingyu  and      DeLucia, Alexandra  and      Dredze, Mark  and      Buczak, Anna L.",    editor = "Xu, Wei  and      Ritter, Alan  and      Baldwin, Tim  and      Rahimi, Afshin",    booktitle = "Proceedings of the Seventh Workshop on Noisy User-generated Text (W-NUT 2021)",    month = nov,    year = "2021",    address = "Online",    publisher = "Association for Computational Linguistics",    url = "aclanthology.org",    doi = "10.18653/v1/2021.wnut-1.44",    pages = "396--409"}