Framework for Civic Engagement Analysis Based on Open Social Media Data

Datyev, Igor O.; Fedorov, Andrey M.; Shchur, Andrey L.

doi:10.1007/978-3-030-51971-1_48

Cited by 5 publications

(4 citation statements)

References 26 publications

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“…Civic engagement has been measured as a multi-dimensional construct, consisting of reading, liking, sharing, commenting, and posting civic engagement topics on Facebook. In doing so, we built on the framework developed by [10]. To the best of our knowledge, we are the first ones to have conceptualised civic engagement on social media in such breadth.…”

Section: Discussionmentioning

confidence: 99%

“…Social media offer different interaction functions for contributing to issues of public concern such as sharing information, exchanging views and opinions by liking, sharing, and commenting posts, becoming a fan, joining or following a profile or group, adding hashtags, posting status updates, or adding profile pictures [1]. Datyev et al have developed a conceptual model for analysing civic engagement on social media [10]. They have identified five types of interaction, i.e., views, likes, comments, re-posts, and posts.…”

Section: Civic Engagement On Social Mediamentioning

confidence: 99%

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Understanding Civic Engagement on Social Media Based on Users’ Motivation to Contribute

Hofmann

Pappas

2021

Lecture Notes in Computer Science

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Social media offer various opportunities for civic engagement by, e.g., liking, sharing, or posting relevant content. Users' motivation to contribute to relevant topics is quite divers and can stem from an intrinsic motivation to do good or external incentives such as being recognised and rewarded by other users. In our study, we adopt self-determination theory, which defines motivation as broad continuum ranging from intrinsic motivation to external regulation. We conducted a quantitative survey with 667 Facebook users to identify how the different kinds of motivation impact the users' behaviour in terms of reading, liking, sharing, commenting, and posting topics relevant to civic engagement. Our results suggest that social media users are mainly driven by intrinsic motivation while different forms of extrinsic motivation play a less important role.

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Section: Discussionmentioning

confidence: 99%

Section: Civic Engagement On Social Mediamentioning

confidence: 99%

Understanding Civic Engagement on Social Media Based on Users’ Motivation to Contribute

Hofmann

Pappas

2021

Lecture Notes in Computer Science

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“…In addition, reference is made to European Union policies concerning the principle of explainable AI [50]. In two papers, legal factors are briefly discussed [46,53]. Lastly, a study addressing challenges in the implementation of an eParticipation initiative highlights the ambiguous legal framework, which partially obstructs activity implementation, compounded by official bodies' inability to furnish clear guidance [81].…”

Section: Eparticipation Contextual Factorsmentioning

confidence: 99%

“…Paper ID Deliberative [42,48,55,61,64,65,69,71,79,81,86] Democratic [41,44,50,54,65,81,85] Civic Engagement [41,44,47,[49][50][51][53][54][55]58,60,63,65,66,[68][69][70]74,76,[78][79][80][81][82][83]85,86]…”

Section: Effectsmentioning

confidence: 99%

The Use of Artificial Intelligence in eParticipation: Mapping Current Research

Vasilakopoulos,

Tavantzis,

Promikyridis

et al. 2024

Future Internet

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Electronic Participation (eParticipation) enables citizens to engage in political and decision-making processes using information and communication technologies. As in many other fields, Artificial Intelligence (AI) has recently started to dictate some of the realities of eParticipation. As a result, an increasing number of studies are investigating the use of AI in eParticipation. The aim of this paper is to map current research on the use of AI in eParticipation. Following PRISMA methodology, the authors identified 235 relevant papers in Web of Science and Scopus and selected 46 studies for review. For analysis purposes, an analysis framework was constructed that combined eParticipation elements (namely actors, activities, effects, contextual factors, and evaluation) with AI elements (namely areas, algorithms, and algorithm evaluation). The results suggest that certain eParticipation actors and activities, as well as AI areas and algorithms, have attracted significant attention from researchers. However, many more remain largely unexplored. The findings can be of value to both academics looking for unexplored research fields and practitioners looking for empirical evidence on what works and what does not.

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