Cross-Context News Corpus for Protest Event-Related Knowledge Base Construction

作     者：Ali Hürriyetoglu Erdem Yörük Osman Mutlu Fırat Durusan ÇagrıYoltar Deniz Yüret Burak Gürel 

作者机构：KoçUniversityRumelifeneri yoluSariyerIstanbul 34450Turkey 

出 版 物：《Data Intelligence》 (数据智能（英文）)

年 卷 期：2021年第3卷第2期

页      面：308-335页

核心收录：

学科分类：1205[管理学-图书情报与档案管理] 0502[文学-外国语言文学] 050201[文学-英语语言文学] 05[文学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：funded by the European Research Council(ERC)Starting Grant 714868 awarded to Dr.Erdem Yörük for his project Emerging Welfare 

主　　题：Event extraction Text classification Political science Social science News Contentious politics Protests Event coreference resolution 

摘      要：We describe a gold standard corpus of protest events that comprise various local and international English language sources from various *** corpus contains document-,sentence-,and token-level *** corpus facilitates creating machine learning models that automatically classify news articles and extract protest event-related information,constructing knowledge bases that enable comparative social and political science *** each news source,the annotation starts with random samples of news articles and continues with samples drawn using active *** batch of samples is annotated by two social and political scientists,adjudicated by an annotation supervisor,and improved by identifying annotation errors *** found that the corpus possesses the variety and quality that are necessary to develop and benchmark text classification and event extraction systems in a cross-context setting,contributing to the generalizability and robustness of automated text processing *** corpus and the reported results will establish a common foundation in automated protest event collection studies,which is currently lacking in the literature.