Constructing an Annotated Corpus for Protest Event Mining

Abstract

We present a corpus for protest event min-ing that combines token-level annotation with the event schema and ontology of entities and events from protest research in the social sci-ences. The dataset uses newswire reports from the English Gigaword corpus. The token-level annotation is inspired by annotation standards for event extraction, in particular that of the Automated Content Extraction 2005 corpus (Walker et al., 2006). Domain experts perform the entire annotation task. We report competi-tive intercoder agreement results. ii IntroductionLanguage is a profoundly social phenomenon, both shaped by the social context in which it is embedded (such as demographic influences on lexical choice) and in turn helping construct that context itself (such as media framing). Although this interdependence is at the core of models in both natural language processing (NLP) and (computational) social sciences (CSS), these two fields still exist largely in parallel, holding back research insight and potential applications in both fields.This workshop aims to advance the joint computational analysis of social sciences and language by explicitly connecting social scientists, network scientists, NLP researchers, and industry partners. Our focus is squarely on integrating CSS with current trends and techniques in NLP and to continue the progress of CSS through socially-informed NLP for the social sciences. This workshop offers a first step towards identifying ways to improve CSS practice with insight from NLP, and to improve NLP with insight from the social sciences.Areas of interest include all levels of linguistic analysis, network science, and the social sciences, including (but not limited to): political science, geography, public health, economics, psychology, sociology, sociolinguistics, phonology, syntax, pragmatics, and stylistics.The program this year includes 41 papers presented as posters. We received 47 submissions, and due to a rigorous review process, we rejected 6. There are also 5 invited speakers, Jason Baldridge The Doctoral Consortium event is part of a workshop at EMNLP, one of the top conferences in natural language processing. Doctoral consortium aims to bring together students and faculty mentors across NLP and the social sciences, to encourage interdisciplinary collaboration and cross-pollination. The consortium event is part of a workshop at EMNLP, one of the top conferences in natural language processing. Student participants will have the opportunity to present their dissertation work, and will be paired with a senior researcher as a mentor. Applications are welcome from doctoral students in both the social sciences and in computer science. Members of groups that are underrepresented in computer science are especially encouraged to apply.We would like to thank the Program Committee members who reviewed the papers this year. We would also like to thank the workshop participants. Last, a word of thanks also goes to the National Science Foundation for providing travel grant funding for travel gr...

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

“…For instance, the phenomena such as "bandh" and "dharna" are protest event types that are specific to India, and thus, are not covered by any general-purpose protest keywords list. Our evaluation of four keyword lists, which are utilized by Huang et al [25], Wang et al [12], Weidmann and Rød [4], and Makarov et al [26], yielded .68 and .80 precision and recall on our randomly sampled batches at best.…”

“…Consequently, protest-event specific annotation schemas and data sets were proposed for creating automated or semi-automated event knowledge bases [4,11,24,25]. In their corpus, Makarov et al [26] used the ontology of CP events which is very similar to ours and identified ten event types. They coded event actors and issues that correspond to each event.…”

Constructing Relational and Verifiable Protest Event Data: Four Challenges and Some Solutions

“…Many research teams interested in accurately capturing more detailed characteristics of protests have concluded that the best approaches for now are semi-automated or hybrid workflows that automate the pre-processing of articles to filter out irrelevant articles but rely on human coders at the final steps of identifying and coding events within articles. Major examples include Mass Mobilization in Autocracies (Croicu and Weidmann 2015;Hellmeier, Rød and Weidmann 2019;Weidmann and Rød 2018), the Cline Center's SPEED (Nardulli, Althaus and Hayes 2015), the Zurich-based team studying European protests (Lorenzini et al 2021;Makarov, Lorenzini and Kriesi 2016), Armed Conflict Location and Event Data (ACLED) 5 , Count Love (Leung and Perkins 2021) and Crowd Counting Consortium (CCC) (Fisher et al 2019).…”

Constructing Theory-Informed Relational and Verifiable Protest Event Data

“…Many research teams interested in accurately capturing the characteristics of protests have concluded that the best approaches for now are semi-automated or hybrid workflows that automate the pre-processing of articles to filter out irrelevant articles but rely on human coders at the final steps of identifying and coding events within articles. Major examples include the Mass Mobilization in Autocracies project (Croicu and Weidmann 2015, Hellmeier, Rød and Weidmann 2019, the Cline Center's SPEED project (Nardulli, Althaus and Hayes 2015) and the Zurich-based team interested in political contestation in Europe (Lorenzini et al 2021, Makarov, Lorenzini andKriesi 2016). Our own project has a similar orientation to these hybrid projects and was developed concurrently with them.…”