With the US election being the main news story for the past few months, I thought it would be a good time to see how network analysis could apply to the US presidential elections. Obviously there are many different ways network analysis can be applied to elections but I wanted to focus on how network of attitudes can affect voting outcomes. This was particularly more interesting to me because after seeing the results of the election, it is certain that the American people have very polarizing views on politics and it would be interesting to see how much that is influenced by networks of people, specifically how network of people’s attitudes towards the presidential candidates affect voting.
It has been known that attitudes have a big impact on a person’s personality and their social behaviours so it would be interesting to see how network of attitude attributes can have a strong impact on the decision of which presidential candidate to vote for. That is precisely what this research team tried to do as they used data from previous US presidential elections to confirm their hypotheses of how attitude networks can predict the elections and how it entirely depends on level of connectivity and how the central element of attitudes has the strongest impact which directly relates to material learnt in CSCC46 so far.
This research team was able to see how highly connected attitude networks have a much stronger impact on voting decisions and this is shown in the image above. You start to see a relation between connectivity and impact on voting and how the nodes in the two network graphs represent different attitudes and the edges are the correlations between the two attitudes with thicker edges representing higher correlations. The nodes that are closely put together also represent highly connected attitude networks. With this data, the research team was also able to take it further and see which attribute node is central thus having the biggest impact on voting behaviours. This would immensely help presidential candidates see what they have to showcase the most because the majority of people are looking for just that.
With all that said, it would be interesting to see what attitude types affected the 2020 election the most and apply the same network analysis above on the voters of today. I also hope to see more social aspects to this where you can start to see how your friends affect your own political ideologies and how that can subsequently affect voting and your choice of presidential candidate. I hope more research into elections continues as it is always interesting to see analytics in various aspects of socially relevant behaviours.