@inproceedings{cd0a3505cd544adf9f9b319258f8ba59,
title = "A Multi-instance Learning Approach to Civil Unrest Event Detection using Twitter",
abstract = "Social media has become an established platform for people to organize and take offline actions, often in the form of civil unrest. Understanding these events can help support pro-democratic movements. The primary method to detect these events on Twitter relies on aggregating many tweets, but this includes many that are not relevant to the task. We propose a multi-instance learning (MIL) approach, which jointly identifies relevant tweets and detects civil unrest events. We demonstrate that MIL improves civil unrest detection over methods based on simple aggregation. Our best model achieves a 0.73 F1 on the Global Civil Unrest on Twitter (G-CUT) dataset.",
author = "Alexandra DeLucia and Mark Dredze and Buczak, {Anna L.}",
note = "Publisher Copyright: {\textcopyright} CASE 2023 - Proceedings of the 6th Workshop on Challenges and Applications of Automated Extraction of Socio-Political Events from Text, associated with 14th International Conference on Recent Advances in Natural Language Processing, RANLP 2023.; 6th Workshop on Challenges and Applications of Automated Extraction of Socio-Political Events from Text, CASE 2023 ; Conference date: 07-09-2023",
year = "2023",
doi = "10.26615/978-954-452-089-2_003",
language = "English (US)",
series = "CASE 2023 - Proceedings of the 6th Workshop on Challenges and Applications of Automated Extraction of Socio-Political Events from Text, associated with 14th International Conference on Recent Advances in Natural Language Processing, RANLP 2023",
publisher = "Incoma Ltd",
pages = "18--33",
editor = "Ali Hurriyetoglu and Hristo Tanev and Vanni Zavarella and Reyyan Yeniterzi and Erdem Yoruk and Milena Slavcheva",
booktitle = "CASE 2023 - Proceedings of the 6th Workshop on Challenges and Applications of Automated Extraction of Socio-Political Events from Text, associated with 14th International Conference on Recent Advances in Natural Language Processing, RANLP 2023",
}