Affiliation:
1. Aarhus Institute of Advanced Studies , Aarhus University , Denmark
Abstract
Abstract
This study investigates the Facebook posting behaviour of 922 posting users over a time span of seven years (from 2007 to 2014), using an innovative combination of survey data and private profile feed post counts obtained through the Facebook Application Programming Interface (API) prior to the changes in 2015. A digital inequality lens is applied to study the effect of socio-demographic characteristics as well as time on posting behaviour. The findings indicate differences, for example in terms of gender and age, but some of this inequality is becoming smaller over time. The data set also shows inequality in the poster ratio in different age groups. Across all the demographic groups, the results show an increase in posting frequency in the time period observed, and limited evidence is found that young age groups have posted less on Facebook in more recent years.
Reference39 articles.
1. Baker, R., Blumberg, S. J., Brick, J. M., Couper, M. P., Courtright, M., Dennis, J. M., … Zahs, D. (2010). AAPOR report on online panels. Public Opinion Quarterly, 74(4): 711–781.
2. Baumer, E. P. S., Adams, P., Khovanskaya, V. D., Liao, T. C., Smith, M. E., Schwanda Sosik, V. & Williams, K. (2013). Limiting, leaving, and (re)lapsing: An exploration of Facebook non-use practices and experiences. In Proceedings of the SIGCHI conference on human factors in computing systems (pp. 3257–3266). New York, NY: ACM. https://doi.org/10.1145/2470654.2466446
3. Bechmann, A. (2014). Non-informed consent cultures: Privacy policies and app contracts on Facebook. Journal of Media Business Studies, 11(1): 21–38. https://doi.org/10.1080/16522354.2014.11073574
4. Bechmann, A. (2015). Managing the interoperable self. In The ubiquitous Internet: User and industry perspectives. New York: Routledge. Retrieved from https://www.taylorfrancis.com/books/e/9781317931409/chapters/10.4324%2F9781315856667-10
5. Bechmann, A. (2019). Data as humans: Representation, accountability, and equality in big data and machine learning. In Power and rights in the online domain. Cambridge, MA: MIT Press.
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献