Research on the influence of social networks on political behavior has led to findings showing an apparent trade-off between positive attitudes toward the outparty and political engagement. The prevalent sentiments have been that partisan bonding or ties with fellow partisans hurts evaluations of the outparty but helps political engagement. Partisan bridging or ties with opposite partisans, on the other hand, improves evaluations of the outparty but hurts engagement. I argue that this trade-off is essentially an illusion driven by a mistaken assumption that bonding and bridging are two opposite ends of the same continuum. Analyzing two original national surveys of the American public, I show that bonding and bridging are independent constructs with different consequences. Consistent with previous studies, I find that bonding hurts and bridging helps outparty attitudes. Both bonding and bridging, however, are positively related to political engagement. I also show that network disagreement partially mediates the effects of partisan bonding, but not the effects of partisan bridging. This suggests that the efforts to encourage voters to build relationships with politically different others can be done without having to worry that they will lead to decreased engagement.
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Other names for partisan bonding and bridging would be intraparty and interparty ties, respectively. I prefer to use the term bonding and bridging to better situate and relate the present study to the study of social networks and their influence on political behavior.
One might think that the assumption that bonding and bridging are inversely correlated is at least justifiable by intuition. Let us consider a global estimate scenario where a respondent is asked about how many of her friends share her partisanship with answers ranging from one (none) to four (a lot). The intuitive argument would have gained traction had the respondent answered the question by first reconstructing her whole network, counting her bonding friends, and then choosing one answer that best reflects that count. While few people might do that, our respondent is more likely to engage in a bottom-up approach by implicitly enumerating friends who share her partisanship or simply relying on impression. This opens up the possibility of forgetting (Bell et al. 2007) and heuristic reasoning (Tversky and Kahneman 1973). Since the whole network itself is never fully constructed, its size cannot be treated as finite and it would be improper to calculate the number of bridging friends as the reverse of the number of bonding friends (five minus the chosen answer). Similarly, the finite set argument also may not work well with a name generator approach for various reasons, such as selective naming of discussants (Bell et al. 2007; Marsden 2003; Shea et al. 2015) and measurement errors caused by artificially constraining the size of respondents’ networks (Marin 2004, p. 289).
Data and code can be accessed at Dataverse: https://doi.org/10.7910/DVN/GZRCCJ.
Measuring bonding and bridging using a global estimate approach, in turn, means that I cannot asses the effects of dyadic interactions and have to focus on the effects of the whole network. This constraint should not undermine the conclusions of the present study. This is because focusing on dyads or on an artificially constrained network might underestimate the effects of social relationships on political behavior (Eveland et al. 2013). Furthermore, dyadic interactions also have to be understood in the context of overall interactions within the network. As Huckfeldt et al. (2004a, b, p. 54) note, “The consequences of dyadic information flows are conditioned on the remainder of the individual’s network.” This is, of course, not to say that the effects of dyadic interactions can or should be reducible to the effects of the whole network. Future study will benefit from exploring the effects of bonding or bridging from a dyadic perspective, for example by interviewing both the respondent and the discussant (e.g., Huckfeldt et al. 2004a, b).
A notable difference is that PID strength is now positively related to the measure of outparty attitudes. This is likely because the measure taps into a behavioral intention (willingness to interact with opposite partisans). As studies on attitude-behavior connection show, actual behavior or behavioral intention is often more onerous than merely holding attitudes as it requires a higher degree of motivation (Ajzen and Fishbein 1977). As such, the measure may differentiate strong and weak partisans better than measures of attitudes used in the American Dream study.
Another, equally important question would be to examine how partisan bonding or bridging interacts with network disagreement. I present this analysis as Table A7 and Figure A1 in the Online Appendix. I find that the effects of disagreement are significant only among individuals with low partisan bridging or bonding. The effects of disagreement are either weaker or not statistically significant among individuals high in bridging or bonding.
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The American Dream study was made possible through grants from the Institute for Scholarship in the Liberal Arts at the University of Notre Dame and the Institute for Humane Studies at George Mason University. The Democratic Virtues study was funded by the Faculty Research Support Program of the University of Notre Dame and generously shared with me by Dave Campbell. I thank Dave Campbell, Geoffrey Layman, and the anonymous reviewers for their helpful feedback.
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Sumaktoyo, N.G. Friends from Across the Aisle: The Effects of Partisan Bonding, Partisan Bridging, and Network Disagreement on Outparty Attitudes and Political Engagement. Polit Behav (2019). https://doi.org/10.1007/s11109-019-09552-x
- Social network
- Partisan bonding
- Partisan bridging
- Inparty ties
- Outparty ties
- Political engagement
- Outparty attitudes