Can Voter Participation Be Described By Network Effects?
American democracy is often lauded for its citizenship and accessibility. The government is by the people, for the people. Yet, it is abundantly clear that the people do not fulfill their role to the greatest extent. At least, not in terms of voting. Approximately 67% of voting-age Americans participated in the 2020 president election—the most salient. This was also a record high rate, up 5% from 2016 (census.gov). This certainly raises the question: if the entire model of American government is dependent on citizens voting, then why doesn’t everyone do it?
This very question is a common one, one which many social scientists have pondered over. Author Meredith Rolfe proposes her social theory of political participation in her book Voter Turnout: A Social Theory of Political Participation. Rolfe’s theory provides an explanation of empirical variation in voter turnout and correlates it to the variation in voters’ social network structures (Rolfe 3). To be specific, Rolfe claims that average network size can be used as a proxy for differences in political participations between elections and finds that “small changes in the average degree of voter social networks relate to substantial changes in simulated turnout” (Rolfe 110).
Additionally, Cesi Cruz, Horacio Larreguy, and John Marshall support the idea that voter turnout in democratic governments can be explained through voter networks in their article “Social Network Effects in Developing Countries.” Voter networks are social networks comprised of voters in elections. They explain that the simple structures of voter networks help diffuse politically relevant information and encourage voter behavior between individuals (Cruz et al. 9). Overall, there is an abundance of empirical and observational evidence which suggest that networks can, at least, explain voter behavior and perhaps predict voter turnout.
I suggest that perhaps the voter networks and voter behaviors can be described by the network effects market. Americans are compelled to vote if 1) their vote will be heard and 2) the votes of others will be heard. In other words, the value of voting is dependent on the voting behavior of others; the fraction of the population that votes is the fraction that the voters predict. I will vote if this number of my friends also vote.
One major factor that defers Americans from voting is the belief that a vote will not matter when millions of people are also voting. If everyone else is already voting, why should I? It won’t sway the election! This sentiment can be quantified in the network effect theory. All voters believe that a given fraction will vote, so that fraction will actually vote. Perhaps the greater market equilibrium for voting in federal elections is roughly 60% since it is consistently around that fraction. This could explain why it is difficult to increase the rate of voter participation because it will continuously converge to the equilibrium.
The concepts related to networks is a good explanation for the variance in voter turnout across American elections and it offers a solid framework for explaining individual and community behavior in relation to voting. Thus, it is only natural to apply the idea of network effects to the concept as well. Perhaps this idea is part of a larger analysis of voting and networks, but it is certainly worth considering.
Works Cited
Bureau, U.S. Census. “Despite Pandemic Challenges, 2020 Election Had Largest Increase in Voting between Presidential Elections on Record.” Census.gov, 8 Oct. 2021, https://www.census.gov/library/stories/2021/04/record-high-turnout-in-2020-general-election.html.
Cruz, Cesi, et al. “Social Network Effects in Developing Countries.” The Oxford Handbook of Electoral Persuasion, 2019, pp. 644–667., https://doi.org/10.1093/oxfordhb/9780190860806.013.20.
Rolfe, Meredith. Voter Turnout: A Social Theory of Political Participation. Cambridge University Press, 2014.