A task set proposal for automatic protest information collection across multiple countries

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Abstract

We propose a coherent set of tasks for protest information collection in the context of generalizable natural language processing. The tasks are news article classification, event sentence detection, and event extraction. Having tools for collecting event information from data produced in multiple countries enables comparative sociology and politics studies. We have annotated news articles in English from a source and a target country in order to be able to measure the performance of the tools developed using data from one country on data from a different country. Our preliminary experiments have shown that the performance of the tools developed using English texts from India drops to a level that are not usable when they are applied on English texts from China. We think our setting addresses the challenge of building generalizable NLP tools that perform well independent of the source of the text and will accelerate progress in line of developing generalizable NLP systems.

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Hürriyetoğlu, A., Yörük, E., Yüret, D., Yoltar, Ç., Gürel, B., Duruşan, F., & Mutlu, O. (2019). A task set proposal for automatic protest information collection across multiple countries. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11438 LNCS, pp. 316–323). Springer Verlag. https://doi.org/10.1007/978-3-030-15719-7_42

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