Friends from Across the Aisle: The Effects of Partisan Bonding, Partisan Bridging, and Network Disagreement on Outparty Attitudes and Political Engagement

Abstract

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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Notes

  1. 1.

    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.

  2. 2.

    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).

  3. 3.

    Data and code can be accessed at Dataverse: https://doi.org/10.7910/DVN/GZRCCJ.

  4. 4.

    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).

  5. 5.

    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.

  6. 6.

    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.

References

  1. Abramowitz, A. I., & Saunders, K. L. (2008). Is polarization a myth? The Journal of Politics, 70(02), 542–555. https://doi.org/10.1017/S0022381608080493.

    Article  Google Scholar 

  2. Agnitsch, K., Flora, J., & Ryan, V. (2006). Bonding and bridging social capital: The interactive effects on community action. Community Development, 37(1), 36–51.

    Article  Google Scholar 

  3. Ajzen, I., & Fishbein, M. (1977). Attitude-behavior relations: A theoretical analysis and review of empirical research. Psychological Bulletin, 84(5), 888–918.

    Article  Google Scholar 

  4. Allport, G. W. (1954). The nature of prejudice. Boston, MA: Addison-Wesley Publishing Company.

    Google Scholar 

  5. Bell, D. C., Belli-McQueen, B., & Haider, A. (2007). Partner naming and forgetting: Recall of network members. Social networks, 29(2), 279–299.

    Article  Google Scholar 

  6. Ben-Nun Bloom, P., & Bagno-Moldavsky, O. (2015). The Conditional effect of network diversity and values on tolerance. Political Behavior, 37(3), 623–651.

    Article  Google Scholar 

  7. Berelson, B. R., Lazarsfeld, P. F., & McPhee, W. N. (1954). Voting: A study of opinion formation in a presidential campaign. Chicago, IL: University of Chicago Press.

    Google Scholar 

  8. Byrne, D. (1962). Response to attitude similarity-dissimilarity as a function of affiliation need. Journal of Personality, 30(2), 164–177.

    Article  Google Scholar 

  9. Campbell, D. E. (2006). Religious “threat” in contemporary presidential elections. The Journal of Politics, 68(1), 104–115.

    Article  Google Scholar 

  10. Campbell, D. E. (2008). Why we vote: How schools and communities shape our civic life. Princeton, NJ: Princeton University Press.

    Google Scholar 

  11. Campbell, D. E. (2013). Social networks and political participation. Annual Review of Political Science, 16(1), 33–48.

    Article  Google Scholar 

  12. Cigler, A., & Joslyn, M. R. (2002). The extensiveness of group membership and social capital: The impact on political tolerance attitudes. Political Research Quarterly, 55(1), 7.

    Article  Google Scholar 

  13. Conover, M. D., Gonçalves, B., Flammini, A., & Menczer, F. (2012). Partisan asymmetries in online political activity. EPJ Data Science, 1(1), 6.

    Article  Google Scholar 

  14. Erisen, E., & Erisen, C. (2012). The effect of social networks on the quality of political thinking: Networks and political thinking. Political Psychology, 33(6), 839–865.

    Article  Google Scholar 

  15. Eveland, W. P., & Hively, M. H. (2009). Political discussion frequency, network size, and “heterogeneity” of discussion as predictors of political knowledge and participation. Journal of Communication, 59(2), 205–224.

    Article  Google Scholar 

  16. Eveland, W. P., Hutchens, M. J., & Morey, A. C. (2013). Political network size and its antecedents and consequences. Political Communication, 30(3), 371–394.

    Article  Google Scholar 

  17. Festinger, L. (1957). A theory of cognitive dissonance. Stanford, CA: Stanford University Press.

    Google Scholar 

  18. Galston, W. A. (2001). Political knowledge, political engagement, and civic education. Annual Review of Political Science, 4(1), 217–234.

    Article  Google Scholar 

  19. Geys, B., & Murdoch, Z. (2010). Measuring the ‘bridging’ versus ‘bonding’ nature of social networks: A proposal for integrating existing measures. Sociology, 44(3), 523–540.

    Article  Google Scholar 

  20. Gomez, B. T., Hansford, T. G., & Krause, G. A. (2007). The republicans should pray for rain: Weather, turnout, and voting in U.S. presidential elections. The Journal of Politics, 69(3), 649–663.

    Article  Google Scholar 

  21. Green, D. P., & Wong, J. S. (2008). Tolerance and the contact hypothesis: A field experiment. In E. Borgida, C. M. Federico, & J. L. Sullivan (Eds.), The political psychology of democratic citizenship (pp. 228–246). New York: Oxford University Press.

    Google Scholar 

  22. Heider, F. (1958). The psychology of interpersonal relations (1st ed.). Hokoben: Wiley.

    Google Scholar 

  23. Huckfeldt, R., Johnson, P. E., & Sprague, J. (2004a). Political disagreement: The survival of diverse opinions within communication networks. Cambridge: Cambridge University Press.

    Google Scholar 

  24. Huckfeldt, R., Mendez, J. M., & Osborn, T. (2004b). Disagreement, ambivalence, and engagement: The political consequences of heterogeneous networks. Political Psychology, 25(1), 65–95.

    Article  Google Scholar 

  25. Huckfeldt, R., & Sprague, J. (1987). Networks in context: The social flow of political information. The American Political Science Review, 81(4), 1197.

    Article  Google Scholar 

  26. Ikeda, K., & Richey, S. (2009). The impact of diversity in informal social networks on tolerance in Japan. British Journal of Political Science, 39(03), 655.

    Article  Google Scholar 

  27. Keith, B. E., Magleby, D. B., Nelson, C. J., Orr, E., Westlye, M. C., & Wolfinger, R. E. (1992). The myth of the independent voter. Berkeley, CA: University of California Press.

    Google Scholar 

  28. Kim, D., Subramanian, S. V., & Kawachi, I. (2006). Bonding versus bridging social capital and their associations with self rated health: A multilevel analysis of 40 US communities. Journal of Epidemiology and Community Health, 60(2), 116–122.

    Article  Google Scholar 

  29. Klar, S. (2014). Partisanship in a social setting. American Journal of Political Science, 58(3), 687–704. https://doi.org/10.1111/ajps.12087.

    Article  Google Scholar 

  30. Klofstad, C. A., McClurg, S. D., & Rolfe, M. (2009). Measurement of political discussion networks: A comparison of two “name generator” procedures. Public Opinion Quarterly, 73(3), 462–483.

    Article  Google Scholar 

  31. Klofstad, C. A., Sokhey, A. E., & McClurg, S. D. (2013). Disagreeing about disagreement: How conflict in social networks affects political behavior. American Journal of Political Science, 57(1), 120–134.

    Article  Google Scholar 

  32. Layman, G. (2001). The great divide: Religious and cultural conflict in American party politics. New York: Columbia University Press.

    Google Scholar 

  33. Lazer, D., Rubineau, B., Chetkovich, C., Katz, N., & Neblo, M. (2010). The coevolution of networks and political attitudes. Political Communication, 27(3), 248–274.

    Article  Google Scholar 

  34. Levendusky, M. S., Druckman, J. N., & McLain, A. (2016). How group discussions create strong attitudes and strong partisans. Research & Politics. https://doi.org/10.1177/2053168016645137.

    Google Scholar 

  35. Lupton, R. N., Singh, S. P., & Thornton, J. R. (2015). The moderating impact of social networks on the relationships among core values, partisanship, and candidate evaluations: The moderating impact of social networks. Political Psychology, 36(4), 399–414.

    Article  Google Scholar 

  36. Lupton, R., & Thornton, J. (2017). Disagreement, diversity, and participation: Examining the properties of several measures of political discussion network characteristics. Political Behavior, 39(3), 585–608.

    Article  Google Scholar 

  37. Marin, A. (2004). Are respondents more likely to list alters with certain characteristics? Social Networks, 26(4), 289–307.

    Article  Google Scholar 

  38. Marsden, P. V. (2003). Interviewer effects in measuring network size using a single name generator. Social Networks, 25(1), 1–16.

    Article  Google Scholar 

  39. Mcclurg, S. D. (2003). Social networks and political participation: The role of social interaction in explaining political participation. Political Research Quarterly, 56(4), 449–464.

    Article  Google Scholar 

  40. McPherson, M., Smith-Lovin, L., & Cook, J. M. (2001). Birds of a feather: Homophily in social networks. Annual Review of Sociology, 27, 415–444.

    Article  Google Scholar 

  41. Mutz, D. C. (2002a). The consequences of cross-cutting networks for political participation. American Journal of Political Science, 46(4), 838.

    Article  Google Scholar 

  42. Mutz, D. C. (2002b). Cross-cutting social networks: Testing democratic theory in practice. American Political Science Review, 96(01), 111–126.

    Article  Google Scholar 

  43. Mutz, D. C. (2006). Hearing the other side: Deliberative versus participatory democracy (1st ed.). Cambridge: Cambridge University Press.

    Google Scholar 

  44. Nir, L. (2005). Ambivalent social networks and their consequences for participation. International Journal of Public Opinion Research, 17(4), 422–442.

    Article  Google Scholar 

  45. Pattie, C. J., & Johnston, R. J. (2008). It’s good to talk: Talk, disagreement and tolerance. British Journal of Political Science, 38(4), 677–698.

    Article  Google Scholar 

  46. Pattie, C. J., & Johnston, R. J. (2009). Conversation, disagreement and political participation. Political Behavior, 31(2), 261–285.

    Article  Google Scholar 

  47. Petrocik, J. R. (2009). Measuring party support: Leaners are not independents. Electoral Studies, 28(4), 562–572.

    Article  Google Scholar 

  48. Pettigrew, T. F., & Tropp, L. R. (2006). A meta-analytic test of intergroup contact theory. Journal of Personality and Social Psychology, 90(5), 751–783.

    Article  Google Scholar 

  49. Pettigrew, T. F., & Tropp, L. R. (2008). How does intergroup contact reduce prejudice? Meta-analytic tests of three mediators. European Journal of Social Psychology, 38(6), 922–934.

    Article  Google Scholar 

  50. Prior, M. (2010). You’ve either got it or you don’t? The stability of political interest over the life cycle. The Journal of Politics, 72(3), 747–766.

    Article  Google Scholar 

  51. Putnam, R. D. (2007). E pluribus unum: Diversity and community in the twenty-first century the 2006 Johan Skytte Prize Lecture. Scandinavian Political Studies, 30(2), 137–174.

    Article  Google Scholar 

  52. Putnam, R. D., & Campbell, D. E. (2010). American grace: How religion divides and unites us. New York: Simon & Schuster.

    Google Scholar 

  53. Scheufele, D. A., Nisbet, M. C., Brossard, D., & Nisbet, E. C. (2004). Social structure and citizenship: examining the impacts of social setting, network heterogeneity, and informational variables on political participation. Political Communication, 21(3), 315–338.

    Article  Google Scholar 

  54. Shea, C. T., Menon, T., Smith, E. B., & Emich, K. (2015). The affective antecedents of cognitive social network activation. Social Networks, 43, 91–99.

    Google Scholar 

  55. Tversky, A., & Kahneman, D. (1973). Availability: A heuristic for judging frequency and probability. Cognitive psychology, 5(2), 207–232.

    Article  Google Scholar 

  56. Ulbig, S. G., & Funk, C. L. (1999). Conflict avoidance and political participation. Political Behavior, 21(3), 265–282.

    Article  Google Scholar 

  57. Ura, J. D., & Ellis, C. R. (2012). Partisan moods: Polarization and the dynamics of mass party preferences. The Journal of Politics, 74(1), 277–291.

    Article  Google Scholar 

  58. Valenzuela, S., Kim, Y., & Gil de Zuniga, H. (2012). Social networks that matter: Exploring the role of political discussion for online political participation. International Journal of Public Opinion Research, 24(2), 163–184.

    Article  Google Scholar 

  59. Van Laar, C., Levin, S., Sinclair, S., & Sidanius, J. (2005). The effect of university roommate contact on ethnic attitudes and behavior. Journal of Experimental Social Psychology, 41(4), 329–345.

    Article  Google Scholar 

  60. Verba, S., Schlozman, K. L., & Brady, H. (1995). Voice and equality: Civic voluntarism in American politics (Abridged ed.). Cambridge: Harvard University Press.

    Google Scholar 

  61. Zhong, C.-B., Phillips, K. W., Leonardelli, G. J., & Galinsky, A. D. (2008). Negational categorization and intergroup behavior. Personality and Social Psychology Bulletin, 34(6), 793–806.

    Article  Google Scholar 

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Acknowledgement

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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Correspondence to Nathanael Gratias Sumaktoyo.

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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

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Keywords

  • Social network
  • Partisan bonding
  • Partisan bridging
  • Inparty ties
  • Outparty ties
  • Political engagement
  • Outparty attitudes