Using Google and Twitter to Measure, Validate and Understand Views about Religion across Africa
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Researchers typically use social surveys or censuses to examine attitudes and behaviors across nations. While useful for understanding cross-national differences, they are expensive to collect, include only a limited number of issues and countries, and are not very time sensitive. Many countries across the world now have residents who regularly use Twitter and Google, and these internet platforms are increasingly making data on the country-level number of tweets and google searches available for analysis. While there are a lot of challenges with these data, we examine some of the potential benefits. Specifically, our study assesses the extent to which cross-national social media and survey measures related to religious expression are related. Focusing on Africa, where surveys are particularly difficult to administer, and religious expression, which is quite common across the continent, is high, we find that our religion-related measures derived from google searches correspond particularly well with traditional social science measures. We then look at how all three sets of measures explain terrorism, health-related issues, and the number of Christian and Muslim official holidays within the country. We find that the measures derived from Google almost always perform as well, if not better, than the traditional social science measures. We discuss how internet data may be able to offer reliable and time-sensitive measures for examining differences across nations and for better understanding a range of issues in Africa.
KeywordsReligion Africa Social media Research Cross-national
- Adamczyk, A. 2011. “The indirect result of religious norms and practices: Explaining Islam’s role in limiting the spread of HIV/AIDS.” (15–31) in Religion and Social Problems, edited by T. Hjelm. New York: Routledge.Google Scholar
- Anon. 2018. Digital in 2018: World’s internet users pass the 4 billion mark. We are social UK. Retrieved September 24, 2018 from https://wearesocial.com/uk/blog/2018/01/global-digital-report-2018. Accesed 24 Sept 2018.
- Ariño, A. 2016. The Power of Twitter in Africa. IESE Business School. Retrieved from: https://blog.iese.edu/africa/2016/06/09/the-power-of-Twitter-in-africa/. September October 10th 2018.
- Buntain, C., McGrath, E., Golbeck, J., & LaFree, G. 2016. Comparing social media and traditional surveys around the Boston Marathon bombing. In # microposts (pp. 34–41).Google Scholar
- How Many People Use Facebook, Twitter, and Instagram in South Africa. 2017. BusinessTech. Retrieved from: https://businesstech.co.za/news/internet/199318/how-many-people-use-facebook-Twitter-and-instagram-in-south-africa/. Accessed 10 Oct 2018.
- Internet Stats in Africa. 2018. Retrieved September 2018 from: http://gs.statcounter.com/social-media-stats/all/africa/#monthly-201201-201809. Accessed 10 Oct 2018.
- LaFree, G., Dugan, L., & Miller, E. 2015. Putting terrorism in context: Lessons from the global terrorism database. Routledge.Google Scholar
- Makin, D. A., & Morczek, A. L. 2015. The dark side of internet searches: A macro level assessment of rape culture. International Journal of Cyber Criminology, 9(1), 1.Google Scholar
- Marshall, M. G. 2018. Major episodes of political violence (MEPV) and conflict regions, 1946–2016. Center for Systemic Peace. Retrieved September 28, 2018 from http://www.systemicpeace.org/inscrdata.html.
- O'Connor, B., Balasubramanyan, R., Routledge, B. R., & Smith, N. A. 2010. From tweets to polls: Linking text sentiment to public opinion time series. Icwsm, 11(122–129), 1–2.Google Scholar
- Pew Research Center. 2012. The global religious landscape. Retrieved from: http://www.pewforum.org/2012/12/18/global-religious-landscape-methodology/. Accessed 10 Oct 2018.
- Rosenthal, E. 2007, July 27. Quiet. Libya has an AIDS problem. The New York Times. Retrieved from: https://www.nytimes.com/2007/07/29/weekinreview/29rosenthal.html. Accessed 12 Sept 2018.
- Salganik, M. J. 2017. Bit by bit: Social research in the digital age. Princeton University PressGoogle Scholar
- Stephens-Davidowitz, S., & Pabon, A. 2017. Everybody lies: Big data, new data, and what the internet can tell us about who we really are. New York:HarperCollins.Google Scholar
- Tumasjan, A., Sprenger, T. O., Sandner, P. G., & Welpe, I. M. 2010. Predicting elections with twitter: What 140 characters reveal about political sentiment. Icwsm, 10(1), 178–185.Google Scholar
- UNAIDS 2007. Male circumcision: Global trends and determinants of prevalence, safety and acceptability. Geneva:UNAIDS.Google Scholar
- UNAIDS. 2017. State of the Aids epidemic report. Retrieved from: http://www.unaids.org/sites/default/files/media_asset/2017_data-book_en.pdf. Accessed 12 Sept 2018.
- World Health Organization Global Health Observatory Data Repository. 2012. Alcohol-Attributable Fractions, All-Cause Deaths (%). Retrieved from: http://apps.who.int/gho/data/view.main.53400. Accessed 12 Sept 2018.
- World Health Organization Global Health Observatory Data Repository. 2018. Number of people (all ages) living with HIV. Estimates per country. Retrieved from: http://apps.who.int/gho/data/view.main.22100?lang=e. Accessed 12 Sept 2018.