Politics Gets Personal: Effects of Political Partisanship and Advertising on Family Ties

14 11 2017

Thanksgiving Dinner. Image from Wikimedia Commons. Falmouth, Maine, USA 2008


An academic friend sent me the abstract to a new paper that uses an innovative methodology to test the claims that political polarization in the US is eroding social capital. Some people have argued that polarization is making it harder for people to stand being around their relatives and neighbours, leading to more “bowling alone” and less face time with people with whom we disagree politically. Two data-savvy social scientists, M. Keith Chen and Ryne Rohla, tried to test this using smartphones. Thanks to what one likes on social media, one can get a good sense of a person’s political leanings. If they like Fox News and retweet Trump, they are probably a strong Republican. If they still have the Hillary Clinton 2016 app on their phone, they probably aren’t.

Smartphones are also GPS-enabled, which helps to pinpoint their locations. Since they tend to stay in the pocket of the owner, which allows to measure how long right-wing and left-wing Americans spend in each other’s presence. Data from the Thanksgiving following the 2016 presidential election suggests that Americans were curtailing the time they spent with ideological opposites, either by cancelling your attendance at Thanksgiving or makign the visit really short. You have your right-wing parents, so you abbreviate your visit to their house on Thanksgiving: turkey, quick dessert, then hit the road before a political argument about who is a traitor starts.

Politics Gets Personal: Effects of Political Partisanship and Advertising on Family Ties


Using smartphone-tracking data and precinct-level voting, we show that politically divided families shortened Thanksgiving dinners by 20-30 minutes following the divisive 2016 election. This decline survives comparisons with 2015 and extensive demographic and spatial controls, and more than doubles in media markets with heavy political advertising. These effects appear asymmetric: while Democratic voters traveled less in 2016, political differences shortened Thanksgiving dinners more among Republican voters, especially where political advertising was heaviest. Partisan polarization may degrade close family ties with large aggregate implications; we estimate 27 million person-hours of cross-partisan Thanksgiving discourse were lost in 2016 to ad-fueled partisan effects.


The big-data techniques that went into this paper were really impressive– note how there were trillions (with a T!) data points supporting this paper.


Location tracking data comes from Safegraph, a company that aggregates location information from numerous smartphone apps. The data consist of “pings”, each of which identify the location (latitude and longitude) of a particular smartphone at a moment in time. Safegraph tracks the location of more than 10 million Americans’ smartphones, and our core analysis focusses on the more than 17 trillion pings Safegraph collected in the continental United States in November of 2016.

I had two initial reactions to this paper.

First, I felt sad when I saw evidence that social capital is being eroded in a country that I like. I’m not an American. I am relieved that political polarization is less of an issue in the two countries in which I have nationality: these two countries, the UK and Canada, have complex multi-party systems, which helps to preclude the severe partisan polarization one sees in the two-party US system. However, while I’m not an American and thus don’t have skin in this particular game, I do recognize that the US is important to my life and well-being and thus I want the US to function well. Eroding social capital undermines the ability of the US to function.

Second, reading the abstract and observing the attention this paper has generated for the authors made me more conscious of the challenges that we qualitative social scientists face trying to carve out impactful careers in a society that, largely legitimately, accords a great deal of respect to quantitative research using big-data methods. I’m not saying that we need to emulate these methods, merely that I and other qual social scientists need to up our games in the choice and design of research topics and then in the dissemination of our research findings to the wider society.



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