A Network Model of Negative Campaigning: The Structure and Determinants of Negative Campaigning in Multiparty Systems

Abstract

Scholarly attention to the nature and extent of negative campaigning in nonmajoritarian multiparty systems is steadily growing. While prior studies have made commendable progress in outlining the conditions and consequences of negative campaigning, they have typically disregarded the complex interdependencies of multiactor communication environments. The present study focuses on network-structural determinants of negative campaigning. It does so by relying on unique data from the 2013 Austrian federal election and using exponential random graph models to investigate patterns of mediated negative campaigning. We find that—above and beyond common determinants of negative campaigning—indicators of network structure are important predictors of campaign communication. This suggests that network models are crucial for accurately representing campaign communication patterns in multiparty systems.

Going Negative, Worldwide: Towards a General Understanding of Determinants and Targets of Negative Campaigning

“…PR), but this does not seem to be the case and the effect exists across all electoral systems and number of competing candidates (Table 4). We also find strong confirmation that a 'logic of retaliation' (Dolezal et al 2016;Song et al 2017) is generally at play, because within dyads attacks are significantly more likely when the sponsor is also strongly attacked by the target. Due to the nature of the data, we cannot break down this effect further and assess the dynamics of who attacks first and who reacts; what appears from our results, though, is that, ceteris paribus, pairs of candidates are more likely to attack each other than attack a third candidate, which responds to the logic of targeted retaliation described in the literature.…”

“…In lay terms, this simply equals expecting that candidates are more likely to attack each other than attack other candidates in the race. The rationale for such expectation draws from the literature showing a 'logic of retaliation' in negative campaigning (Damore 2002;Dolezal et al 2016;Druckman et al 2010;Song et al 2017), according to which negativity can be induced by attacks from opponents. The reasons supporting this trend remain under-theorized, but seem relatively intuitive nonetheless (Dolezal et al 2016): candidates have a strategic incentive to respond to negativity with another attack, because failing to do so might create in the eyes of the voter the image that candidates are ineffective or uncommitted to the issues at stake.…”

“…Furthermore, some evidence exists that backlash effects are less severe for counterattacks, which tips the balance towards going negative (Krupnikov and Bauer 2014); when voters witness an attack against an actor they almost naturally expect a counterattack, the absence of which might be perceived as cognitively dissonant (De Nooy and Kleinnijenhuis 2015). All in all, retaliation 'enables those being attacked to offset the relative losses by damaging the competitors' standing' (Song et al 2017), which means that candidates are often 'better served by counterattacking' (Damore 2002: 673). In our case, because we are unable to test for the dynamic of attacks (we do not know who attacked first and when), we simply assume that when both candidates in a dyad attack each other a great deal, this reflects an overall and repeated logic of retaliation or 'tit-for-tat', regardless of the sequence of attacks.…”

News repertoires and information behavior in Austria—What is the role of social inequality?

“…While the late 20th century media environments included broadcasting, newspapers and media organizations' websites, the early 21st century has been defined by the rise of social media (Fletcher and Nielsen 2017). The process of how news can be accessed has changed profoundly as communication technology matured (Levy and Newman 2014; Livingstone 2013; Song et al 2019). Thus, platforms, such as Facebook or Instagram, and messaging applications, such as WhatsApp or Signal, attract a lot of attention regarding information behavior and media consumption.…”

“…Thus, platforms, such as Facebook or Instagram, and messaging applications, such as WhatsApp or Signal, attract a lot of attention regarding information behavior and media consumption. Social media are currently an integral part of the so-called 'high choice media environments' that force consumers to divide their limited amount of time between a manifold of news offerings (Eisenegger 2019;Gil de Zúñiga et al 2017;Lindell and Hovden 2018;Nielsen and Ganter 2018;Song et al 2019).…”