Building social media observatories for monitoring online opinion dynamics

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• dc.contributor.author Willaert, Tom
• dc.contributor.author Van Eecke, Paul
• dc.contributor.author Beuls, Katrien
• dc.contributor.author Steels, Luc
• dc.date.accessioned 2020-06-08T06:49:04Z
• dc.date.available 2020-06-08T06:49:04Z
• dc.date.issued 2020
• dc.description.abstract Social media house a trove of relevant information for the study of online opinion dynamics. However, harvesting and analyzing the sheer overload of data that is produced by these media poses immense challenges to journalists, researchers, activists, policy makers, and concerned citizens. To mitigate this situation, this article discusses the creation of (social) media observatories: platforms that enable users to capture the complexities of social behavior, in particular the alignment and misalignment of opinions, through computational analyses of digital media data. The article positions the concept of “observatories” for social media monitoring among ongoing methodological developments in the computational social sciences and humanities and proceeds to discuss the technological innovations and design choices behind social media observatories currently under development for the study of opinions related to cultural and societal issues in European spaces. Notable attention is devoted to the construction of Penelope: an open, web-services-based infrastructure that allows different user groups to consult and contribute digital tools and observatories that suit their analytical needs. The potential and the limitations of this approach are discussed on the basis of a climate change opinion observatory that implements text analysis tools to study opinion dynamics concerning themes such as global warming. Throughout, the article explicitly acknowledges and addresses potential risks of the machine-guided and human-incentivized study of opinion dynamics. Concluding remarks are devoted to a synthesis of the ethical and epistemological implications of the exercise of positioning observatories in contemporary information spaces and to an examination of future pathways for the development of social media observatories.
• dc.description.sponsorship The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 732942.
• dc.format.mimetype application/pdf
• dc.identifier.citation Willaert T, Van Eecke P, Beuls K, Steels L. Building social media observatories for monitoring online opinion dynamics. Social Media and Society. 2020; 6(2):1-12. DOI: 10.1177/2056305119898778
• dc.identifier.doi http://dx.doi.org/10.1177/2056305119898778
• dc.identifier.issn 2056-3051
• dc.identifier.uri http://hdl.handle.net/10230/44917
• dc.language.iso eng
• dc.publisher SAGE Publications
• dc.relation.ispartof Social Media and Society. 2020; 6(2):1-12
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/732942
• dc.rights © The Author(s) 2020. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri https://creativecommons.org/licenses/by-nc/4.0/
• dc.subject.keyword Media
• dc.subject.keyword Data mining
• dc.subject.keyword Opinion dynamics
• dc.subject.keyword Digital methods
• dc.subject.keyword Artificial intelligence
• dc.title Building social media observatories for monitoring online opinion dynamics
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion