Do Social Networks Contribute to Political Polarization?
With the rise of social media over the past decade, access to a variety of political opinions has increased exponentially. But have people actually utilized these social networks to broaden their news feed, or have they used the customizability of these platforms to construct political echo chambers? According to a 2014 study from researchers at the University of Milan there is evidence that the latter case is more accurate. The researchers utilized machine learning clustering algorithms and social network analysis to classify Twitter users as liberal or conservative based on the content of their tweets, who they follow, and their likes/retweets. Through analysis, the study found that liberal and conservative users tended to self-segregate themselves into two main enclaves on the social media platform. This means that liberal users saw and interacted with mostly with other liberal content, and vice versa for conservative users. The graphs constructed in this study connect to our study of graph theory, and how clusters can arise within networks.
There is evidence from psychology and sociology that exposure to biased information feeds can push people further right or left in their political opinions over time. If this phenomenon holds, then Twitter may gradually push its users further into their respective political leanings, and increase polarization between liberals and conservatives over time. To combat this, I propose that Twitter could analyze people’s profiles and suggest them users slightly opposite of them politically to help balance their news feeds, and reduce the likelihood of polarization among Twitter users.
Source: http://perpustakaan.unitomo.ac.id/repository/Echo%20chamber%20or%20public%20spare%20predicting%20political%20orientation.pdf