As our political and media systems rapidly evolve, social scientists are revisiting and updating existing models, theories, and methods for investigating the effects of the media on political attitudes and behavior. Among topics, understanding the relationship between media and political polarization remains perhaps the most complex and challenging. For the forthcoming 2012 edition of Communication Yearbook, an annual that features state-of-the-field reviews and synthesis of research, my colleague Dietram Scheufele and I were asked to contribute a brief chapter addressing questions related to media and polarization. I have posted a draft version of that contribution below. See also Dietram's discussion at his blog.
In our contribution, we reflect on several of the themes raised by a much longer and more comprehensive review contributed by German researchers Wolfgang Donsbach and Cornelia Mothes. I will write more about that chapter -- and its many useful insights and conclusions -- when it appears in print later this year.
Scheufele, D.A & Nisbet, M.C. (in press). Online News and the Demise of Political Disagreement. Communication Yearbook.
Information processing is rarely free of partisan biases. We know from decades of research in social psychology, political science, sociology and communication that our values and ideological predispositions influence how much bias we see in media reports (Vallone, Ross, & Lepper, 1985), how willing or likely we are to attend to particular stories (Donsbach, 1991), and – maybe most importantly – how we interpret seemingly objective pieces of information differentially, depending on our personal value systems (Brossard, Scheufele, Kim, & Lewenstein, 2009; Ho, Brossard, & Scheufele, 2008; Kunda, 1990; Nisbet, 2005).
But why are we concerned about selectivity? In many ways, selectively attending to some messages over others, based on perceptions of source credibility, ideological congruence or issue-specific interest, is what enables us to efficiently sift through large amounts of information. But as Donsbach and Mothes outline in their chapter, the notion of selectively attending to or discounting information, based on ideological or value-based predispositions, is also directly at odds with normative views of democratic citizenship.
Discourse and its Effects on Political Citizenship
The notion of a truly deliberative (or civil) society is based on a few key premises (Scheufele, 2011). Among them are two that are particularly relevant for thinking operationally about the issue of selectivity: (1) All possible views and supporting arguments are expressed; and (2) participants are willing to listen to and engage with arguments that are different from their own. As a result, truly civil deliberations among citizens can be defined as the rational exchange of non-likeminded views (or disagreement).
As is so often the case, however, empirical realities are at odds with these normative ideals. Many of us are simply not used to being confronted on a regular basis with others who hold views that are strongly opposed to our own. Our social networks, i.e., the people we are surrounded by in most of our daily activities, tend to be extremely like-minded and homogenous in their demographic and ideological makeup. In the U.S., we have always tended to buy houses, socialize, play sports, and discuss politics mostly with people who think and look like us (McPherson, Smith-Lovin, & Cook, 2001) and in recent decades, the political similarity of our social, political, and geographic enclaves has increased appreciably (Bishop, 2008; Abramowitz, 2010). As a result, we are less and less likely to talk to people who hold different views from our own (Mutz, 2002b).
Yet avoiding disagreement may not necessarily a bad thing. In fact, some researchers have suggested that when we do encounter heterogeneity or disagreement in our social networks, it can have detrimental effects on our willingness to participate in the political process. Mutz (2002a), for example, argues that being exposed to non-likeminded partisan information in one’s social network can create feelings of ambivalence among voters and consequently promote apathy rather than engagement with the political process.
But exposure to non-likeminded information can also have significant positive effects on democratic citizenship, especially if we conceptualize disagreement in ways that that go beyond discussing politics across political party lines or left-right ideology. In a series of studies, for instance, we compared citizens whose discussion networks exposed them to varying levels of disagreement not just by political lines but also by gender, racial, and religious differences (Kim, Scheufele, & Han, 2011; Scheufele, Hardy, Brossard, Waismel-Manor, & Nisbet, 2006; Scheufele, Nisbet, Brossard, & Nisbet, 2004; Scheufele, Nisbet, & Brossard 2003).
We were particularly interested in finding out why disagreement matters, and what the effects of people’s everyday interactions across social settings such as church, work, and volunteer groups were on their willingness to participate in the political process. The take away conclusion is consistent across studies: Encountering disagreement in one's social network is a good thing. In many cases, it promotes participation and a number of civically-relevant outcomes (McLeod, Scheufele, & Moy, 1999; Scheufele et al., 2006; Scheufele et al., 2004).
Demise of Political Disagreement?
When the internet first began to provide broad access to virtually infinite amounts of information to citizens, commentators heralded online information environments as new commonwealths of information. Many of these commentators expressed the hope that online communication could close informational divides and enable a truly deliberative discourse across all cross-sections of society (for an overview, see Nisbet & Scheufele, 2004; Scheufele & Nisbet, 2002)
Recent reviews have been distinctly more pessimistic, and have suggested that we may in fact be returning to a fractionalized, partisan news environment that will reinforce citizens’ existing views through higher levels of selectivity, and ultimately narrow public discourse along partisan lines of disagreement (Bennett & Iyengar, 2008). Donsbach and Mothes’ overview in this volume offers a more in-depth look at this idea and explores a set of complementary explanatory models for how these selectivity-based processes may play from an audience perspective.
But given the dynamic nature of online news environments, it may be useful to think about the particular mechanisms or filters that are unique to online information environments and will continue to change the landscape of how we selectively attend to information around us. At the most abstract level, we can distinguish two sets of mechanisms or filters: media-centric ones and audience-centric ones.
Applying as a filter their professional judgment and expertise, journalists have historically guided audiences towards the issues they deem the most newsworthy and important (White, 1950). Not only would some issues make it into the day’s news while others would not, but audiences could rely on experienced professionals organizing these stories by a hierarchy of importance via lead stories and front-page headlines. As Downie and Schudson (2009) note, “reporting the news means telling citizens what they would not otherwise know.” Empirically, of course, researchers have shown a number of potential distortions in how news items get selected or presented, based on characteristics of the story (Galtung & Ruge, 1965), professional norms and ideologies (Tuchman, 1978), and various external pressures (Gans, 1979). Overall, however, by applying the filter of their professional judgment and expertise, journalists have fulfilled an essential surveillance and agenda-setting function in society.
Yet today with more Americans saying that they get their news on a daily basis from online sources than from local newspapers (Purcell, Rainie, Mitchell, Rosenstiel, & Olmstead, 2010), the presentation, selection, and availability of news is no longer chiefly controlled by journalists. Nor is the primary goal to attract diverse audiences to a hierarchically organized portfolio of coverage defined by an entire broadcast or newspaper edition. Instead, the objective is to lure a combination of habitual and incidental news consumers to specific online stories by way of search engines, aggregators, and social networks. This strategy allows news organizations to maximize page views while also tracking and selling personal information about consumers via third party partners such as Facebook. At least three related trends enable this goal.
Opinionated news and niche audiences: The proliferation of niche cable channels such as MSNBC and Fox News and highly specialized online information environments such as Huffington Post or The Daily Caller have led to an increasing fractionalization of news choices and audiences. Driven by commercial concerns, much of this fractionalization has occurred along partisan fault lines. Or as Rachel Maddow put it: “Opinion-driven media makes the money that politically neutral media loses.” (Maddow, 2010, p. 22). And as more recent research shows, these fragmented news environments have the potential to produce more apathy among some segments of the electorate and more partisan polarization across the population overall (Prior, 2007).
Algorithms as editors: The increasing shift toward online presentation of news, even among traditional news outlets, has also provided media organizations with new real-time metrics of audience preference and the ability to make decisions about news selection and placement based on these metrics. This use of “algorithms as editors” (Peters, 2010) is not without pitfalls. Increasing the influence that reader preferences have on story selection and placement also increases the likelihood of a spiral of mutual reinforcement. In other words, stories that readers selectively attend to will be placed more prominently on news(paper) web sites, which – in turn – increases the odds of readers finding them in the first place. This makes it easy for readers to select content based on popularity, interest, or political identity; opting out of the professional hierarchy of front page headlines and lead stories that might appear in a printed newspaper or broadcast.
Self-reinforcing search and tagging spirals: This notion of reinforcing spirals is exacerbated in online search environments where search engine rankings and search suggestions can heavily influence the overall information infrastructure. The process depends not only on the algorithms used by search engines but also on the tagging and optimization strategies pursued by news content providers, aggregators, bloggers, and interest groups (Hindman, 2009). Examining the presentation of scientific information online, Ladwig and colleagues (Ladwig, Anderson, Brossard, Scheufele, & Shaw, 2010), for example, found that the “suggest” function in Google’s search results often did not correspond to the online information environment that was available to audiences (based on systematic analyses of the complete population of web sites and blogs). As a result, the guidance provided by Google search suggestions is likely to disproportionally drive traffic, regardless of the content available, and create a self-reinforcing spiral that reduces the complexity and diversity of the information that citizens encounter online (Ladwig, Anderson, Brossard, Scheufele, & Shaw, 2010).
Many of these more media-centric filters work in tandem with individual-level behaviors and choices. Prior’s (2007) hypotheses about the polarizing effects of increasing channel diversity, for instance, are based heavily on the assumption that individuals actively make choices about the content (news vs. entertainment) that they attend to. But the social texture that is developing in web 2.0 information environments produces a communication landscape in which at least two new modes of audience-centric selectivity that are likely to influence news choices.
Automated selectivity: In online environments, news portals and aggregator sites allow for highly effective individual pre-selection of the information that reaches us. iGoogle, myYahoo and other news aggregators allow audiences to selectively receive and attend to news items, based on a set of fine-grained filters that can include medium, outlet, content, author and a host of other pre-defined criteria. In contrast, visitors to the landing page for online newspapers may be able to skim or skip stories that they disagree with or find boring, but they will have a hard time making a selective choice without at least briefly glancing at the lead or headline. Portals and other news aggregators – in contrast – will make sure that some stories never even reach our computer screen. Smart phones, tablets and other portable devices make it easier to skim and select when consuming news, creating further incentives for news organizations to cater to this selectivity in their design of mobile applications.
Networks as filters: This individual-level set of filters, however, is being complemented by maybe even more effective social filters. Based on a series of experiments about online information use patterns in various social settings, Messing and colleagues (2011), for example, predict that “social information, and especially personal recommendations, will emerge as the most important explanatory factor shaping both the media environment to which an individual is exposed, and the content that the individual chooses to view” (p. 29).
And the notion of networks as selective filters may be more prevalent than we think. Seventy-five percent of online news consumers now say they get news forwarded through email or posts on social networking sites (Purcell et al., 2010), i.e., information that is passed along and preselected by people who are strongly likely to share their worldviews and preferences. And much of this information is not presented in an isolated news environment, similar to traditional newspapers or television broadcasts, but instead is socially contextualized almost immediately by a host of reader comments, Facebook “like” buttons, and indicators of how often a story has been re-tweeted.
The potential effects of such social-level contextualization on individual news selection are less clear, and two competing hypotheses can be put forth. They map nicely onto the two self-reinforcing spirals that Donsbach and Mothes outline in their essay in this volume.
The first hypothesis suggests that we may be moving toward a society where we are less and less exposed to (and less and less used to) disagreement and viewpoints that are different from our own. Highly like-minded and homophilic networks, in other words, may exacerbate the effects of individual-level selectivity and produce an even more fine-grained filter for incoming information. The result would be a very pronounced spiral of self-reinforcing attitude polarization to use Donsbach and Mothes’ term. Journalists and other professional groups such as scientists are likely to be part of this attitude polarization; since these groups tend to be disproportionately like-minded in their political outlook, are heavier users of online news sources and social media; and face greater demands on their time in managing and using information (Besley & Nisbet, forthcoming; Donsbach, 2004).
A number of recent studies, however, provide some preliminary evidence for a more optimistic hypothesis. It is based on the assumption that friendship networks may often be more politically diverse than the individuals in these networks perceive them to be. In other words, “friends disagree more than they think they do” (Goel, Mason, & Watts, 2010, p. 611). This also means that socially homophilic networks may be characterized by more political diversity than we often assume. Messing et al (2011), in fact, infer that socially-networked information environments can “create at least marginally more cross-cutting exposure to political information” (p. 30) than situations where individuals select news items without additional social cues.
It remains to be seen if these findings are replicated in future work and socially-networked information environments can in fact increase exposure to non-likeminded views. If they do, they could produce some of the same beneficial outcomes that we outlined in our work on heterogeneous face-to-face networks (Scheufele et al., 2006; Scheufele et al., 2004), or at least reinforce the spirals of depolarization that Donsbach and Mothes outline in their models.
It is clear that communication researchers have only begun to fill in parts of a large grid of research questions which will have to be answered in the near future. Hopefully, the overview provided here and in Donsbach and Mothes’ essay will systematize these efforts. Whatever the answers may be that we as a discipline provide, they will have important implications for how we conceptualize and measure communication effects, effectively design online media, educate professionals and the public, and regulate media content and platforms. But more importantly, they will raise normative questions about the future of a media system that – driven by media-centric or audience-centric shifts – no longer provides a commonly shared and professionally defined hierarchy of stories and ideas.
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