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        <title>Automatized Detection and Annotation for Calls to Action in Latin-American Social Media Postings</title>
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    <name type="personal">
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    <abstract>Voter mobilization via social media has shown to be an effective tool. While previous research has primarily looked at how calls-to-action (CTAs) were used in Twitter messages from non-profit organizations and protest mobilization, we are interested in identifying the linguistic cues used in CTAs found on Facebook and Twitter for an automatic identification of CTAs. The work is part of an on-going collaboration with researchers from political science, who are investigating CTAs in the period leading up to recent elections in three different Latin American countries. We developed a new NLP pipeline for Spanish to facilitate their work. Our pipeline annotates social media posts with a range of linguistic information and then conducts targeted searches for linguistic cues that allow for an automatic annotation and identification of relevant CTAs. By using carefully crafted and linguistically informed heuristics, our system so far achieves an F1-score of 0.72.</abstract>
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%0 Conference Proceedings
%T Automatized Detection and Annotation for Calls to Action in Latin-American Social Media Postings
%A Siskou, Wassiliki
%A Giralt Mirón, Clara
%A Molina-Raith, Sarah
%A Butt, Miriam
%S Proceedings of the 6th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature
%D 2022
%8 October
%I International Conference on Computational Linguistics
%C Gyeongju, Republic of Korea
%F siskou-etal-2022-automatized
%X Voter mobilization via social media has shown to be an effective tool. While previous research has primarily looked at how calls-to-action (CTAs) were used in Twitter messages from non-profit organizations and protest mobilization, we are interested in identifying the linguistic cues used in CTAs found on Facebook and Twitter for an automatic identification of CTAs. The work is part of an on-going collaboration with researchers from political science, who are investigating CTAs in the period leading up to recent elections in three different Latin American countries. We developed a new NLP pipeline for Spanish to facilitate their work. Our pipeline annotates social media posts with a range of linguistic information and then conducts targeted searches for linguistic cues that allow for an automatic annotation and identification of relevant CTAs. By using carefully crafted and linguistically informed heuristics, our system so far achieves an F1-score of 0.72.
%U https://aclanthology.org/2022.latechclfl-1.8
%P 65-69

Markdown (Informal)

[Automatized Detection and Annotation for Calls to Action in Latin-American Social Media Postings](https://aclanthology.org/2022.latechclfl-1.8) (Siskou et al., LaTeCHCLfL 2022)

• Automatized Detection and Annotation for Calls to Action in Latin-American Social Media Postings (Siskou et al., LaTeCHCLfL 2022)

ACL

• Wassiliki Siskou, Clara Giralt Mirón, Sarah Molina-Raith, and Miriam Butt. 2022. Automatized Detection and Annotation for Calls to Action in Latin-American Social Media Postings. In Proceedings of the 6th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, pages 65–69, Gyeongju, Republic of Korea. International Conference on Computational Linguistics.