Towards automated protest event analysis

Makarov, Peter; Lorenzini, Jasmine; Rothenhäusler, Klaus; Wüest, Bruno

doi:10.5167/uzh-143877

Cited by 2 publications

(2 citation statements)

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“…Each study reports their own key term lists and the way they use it. Moreover, labelled documents are released in terms of their URLs or document IDs in some collection without their content [Makarov et al, 2015]. Accessing the dataset using this limited information is the responsibility of the people who want to use these resources.…”

Section: Relevant Workmentioning

confidence: 99%

Cross-context News Corpus for Protest Events related Knowledge Base Construction

Hürriyetoğlu¹,

Yörük²,

Yüret³

et al. 2020

Preprint

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We describe a gold standard corpus of protest events that comprise of various local and international sources from various countries in English. The corpus contains document, sentence, and token level annotations. This corpus facilitates creating machine learning models that automatically classify news articles and extract protest event-related information, constructing knowledge bases which enable comparative social and political science studies. For each news source, the annotation starts on random samples of news articles and continues with samples that are drawn using active learning. Each batch of samples was annotated by two social and political scientists, adjudicated by an annotation supervisor, and was improved by identifying annotation errors semi-automatically. We found that the corpus has the variety and quality to develop and benchmark text classification and event extraction systems in a cross-context setting, which contributes to the generalizability and robustness of automated text processing systems. This corpus and the reported results will set the currently lacking common ground in automated protest event collection studies.1. International sources were filtered based on meta-information to focus on the case countries. 2. https://emw.ku.edu.tr/clef-protestnews-2019/ , https://emw.ku.edu.tr/?event=challenges-and-opportunities-in-au

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Section: Relevant Workmentioning

confidence: 99%

Cross-context News Corpus for Protest Events related Knowledge Base Construction

Hürriyetoğlu¹,

Yörük²,

Yüret³

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…These studies provide their own keyword list and describe the way they use it. Moreover, labeled documents are presented as their URLs or document IDs in proprietary collections such as Lexis Nexis without their content [21]. Accessing the data set with such limited information, and the necessity of purchasing subscriptions to these databases are significant limitations.…”

Section: Relevant Workmentioning

confidence: 99%