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Mapping Cyber-Collective Action among Female Muslim Bloggers for the Women to Drive Movement

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Book cover Social Computing, Behavioral-Cultural Modeling and Prediction (SBP 2013)

Abstract

Social media platforms have been lauded for their democratizing potential. They serve as facilitating platforms for activists seeking to replace or alter authoritarian regimes and to promote freedom and democracy. However, regardless of the prominent role of Twitter, Facebook, and other social media platforms in various recently observed social movements, there is a scarcity of rigorous studies that go beyond mere descriptive tendencies and suggest theoretical underpinnings for the manifestations of cyber-collective actions. In this study, we propose a methodology to gain deeper insights into online collective action by analyzing how decentralized online individual actions transform into cyber-collective actions. The proposed model is experimentally analyzed on the data collected for the Saudi women campaigns on driving prohibition. The data consists of female Muslim bloggers’ postings from 23 different countries during 2007 and 2012, including various events organized through the Internet (primarily via social media), such as the Saudi Arabian Women campaign of September 2007, International Women’s Day of March 2008, and Women to Drive campaign of June 2011. As conceptualized, utilized and illustrated in the study, our novel methodological approach highlights several key contributions to the fundamental research on online collective action as well as computational studies on social media. The tools and methodologies proposed here enable the study of collective actions in broader settings, such as digital/hashtag activism for equitable human rights and citizen engagement for better governance.

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Yuce, S., Agarwal, N., Wigand, R.T. (2013). Mapping Cyber-Collective Action among Female Muslim Bloggers for the Women to Drive Movement. In: Greenberg, A.M., Kennedy, W.G., Bos, N.D. (eds) Social Computing, Behavioral-Cultural Modeling and Prediction. SBP 2013. Lecture Notes in Computer Science, vol 7812. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37210-0_36

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  • DOI: https://doi.org/10.1007/978-3-642-37210-0_36

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37209-4

  • Online ISBN: 978-3-642-37210-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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