Volume 5, No 4, 2008

Virtual polling data: A social network analysis on a student government election


Shane Tilton

Abstract

This paper will look at the ability of online social networks to predict election outcomes of a connected society, in this case a university. Facebook represents a new phenomenon in networking within a university. These network constructs allow for communication to occur rapidly and can influence the opinion of the student body. It is the conglomeration of previous information and communication technologies (ICTs) wrapped up under a simple graphical user interface (GUI) that allows the student body to communicate quickly and has allowed online social networks to dominate collegiate culture. Collegiate culture exists in a duality of the real world and this new online social network. Student governance is reflected in both of these realms. Student governance is as close to political power as most students get within the confines of the university and just as complex as the network structure present in Facebook. Like Facebook, the students within the collegiate experience must successfully navigate within the internal network to survive and become leaders in the community. With these similarities, the research question that will framed the rest of the paper will be "could Facebook be used to estimate the results of a student election?" The research used a hierarchical linear matrix, which was developed for the work of Raudenbush & Bryk, to develop a model that could answer this question. The final analysis of the matrix showed it was able to predict what place the candidates came in 21 out of 27 times for all of the candidates in a given election. In terms of predicting the candidate's final percentage of votes received (within half the standard deviation of the Estimated Polling Percentage, which was .072722) during the election 12 out of 27 times for all of the candidates in a given election.


Pages: 1-8

Keywords: Facebook; Elections; Political; Virtual engagement; Hierarchical linear model

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