Movement versus Party: The Electoral Effects of Anti-Far Right Protests in Greece

Abstract

The way social protest affects electoral outcomes remains a lacuna. This article helps fill this gap by examining how social protest against far right actors affects their electoral standing. The article utilizes a unique dataset of 4,745 local protest events to investigate how mobilization against the far right in Greece affected its electoral performance. The article finds that protest activity depressed the electoral results of the far right Golden Dawn by as much as 16%, after controlling for a number of important variables. The article identifies and specifies the patterns through which protests against the far right affect its electoral standing. Protests are effective when following the “tango” pattern—when there is close interaction of far right and anti-far right events. The timing of protest is also important and the article shows how the synchronization of protest and electoral cycles affects electoral outcomes. The article uses the findings to discuss the varying impact of protest across electoral cycles.

INTRODUCTION

The way social movements and political parties interact has long been a lacuna, generated by disciplinary barriers that have kept sociologists and political scientists apart (Hutter 2014a; McAdam and Tarrow 2010; Tarrow 2021). Although recent scholarship has helped narrow this gap, it has not adequately specified how movement and party interaction affects electoral outcomes. Protests organized by social movements are perceived as “the canaries in the coalmines that warn of future political and electoral change” (Gillion 2020, 7). But this change is mostly observed indirectly, at the party-systemic level. For example, it has been shown that by “anchoring” into parties, movements push parties away from the median voter (Schlozman 2015), exacerbating the polarization of American party politics (McAdam and Kloos 2014; McAdam and Tarrow 2013). In multi-party systems, protest cycles transform or destabilize the party-political landscape by electorally punishing mainstream parties (Bremer, Hutter, and Kriesi 2020) or rewarding existing and new party contestants connected with social movements (Della Porta et al. 2017). More direct empirical links between protests and elections are quite rare and primarily based on American data from earlier periods (Gillion and Soule 2018; Wasow 2020).

The article takes empirical cues from protests organized against far right actors to identify and specify a new model for understanding how the interaction of movements and parties affects electoral outcomes. Across different democratic settings, from Saarbrücken and Chemnitz in Germany; to Rome, Bologna, and Genoa in Italy; to Charlottesville in the United States, societal groups mobilize to confront perceived threats posed by the ascendance of far right groups. The model incorporates two distinct protest dynamics to analyze the electoral effects of this mobilization. The tango pattern examines the interaction between the protesters and their opponents and shows how the temporal and spatial co-occurrence of mobilization and counter-mobilization affects electoral outcomes. This pattern captures the tactical choice of anti-far right protesters to organize a direct response to far right events, by counter-organizing a protest at around the same time and place. The timing of political protest is more straightforward: it investigates how the temporal proximity of protest events to elections affects electoral outcomes. Both protest dynamics are shown to have a substantial effect on electoral outcomes.

The article applies the model by leveraging evidence from social protests against “the most extreme-right party in Europe” (Dinas et al. 2019, 244), the Greek Golden Dawn (GD). Using a unique dataset of thousands of protest events organized by hundreds of organizations, groups, and networks across a period of 13 years, we investigate how grassroots mobilization against the far right affected its results in national parliamentary elections. After controlling for important variables like population size, immigration level, unemployment, and average age, and using university student population as an instrument, we show that anti-far right mobilization depresses voter support for the targeted party. We then investigate how specific protest dynamics affect electoral outcomes, looking in turn how the tango pattern and the timing of protest affect electoral support for the far right. We show that tango and timing dampen support for GD. We then discuss the varying impact of protest across electoral cycles and explore future research venues on the micro-mechanisms linking local protest to individual-level voting behavior.

SOCIAL MOVEMENTS AND ELECTORAL POLITICS

The way social movements affect their political environments has received considerable scholarly attention (e.g., Amenta and Caren 2004; Bosi, Giugni, and Uba 2016; Gamson 1975; Kitschelt 1986; Kriesi et al. 1992) but rarely through the examination of electoral outcomes. Movements have been known to affect polities (Goldstone 2003; Yashar 1998), policies (Andrews 2004; Fording 1997; Weldon 2011), and people (Blee 2016; Giugni and Grasso 2016), “yet there is little research on movement influence over elections and the political influence gained through such electoral support” (Amenta et al. 2010, 297). This is partly because social movements are known to affect outcomes through other institutional channels that are only indirectly related to the electoral arena. This is especially so in the early stages of the policy process (Baumgartner and Mahoney 2005; Soule and King 2006), when movements help set the agenda to which governments and legislatures respond (Hutter and Vliegenthart 2018; Walgrave and Vliegenthart 2012; Wouters, Sevenans, and Vliegenthart 2021).

The net effect of movements on elections has mostly been studied indirectly, at the party-systemic level, through the analysis of their impact on political parties. In the US, movements have been known to affect electoral outcomes by grounding or pushing political parties to vote-winning or vote-losing programmatic positions (McAdam and Kloos 2014; McAdam and Tarrow 2013; Schlozman 2015). The effect of the antiwar movement on the political revival of the Democratic Party (Heaney and Rojas 2015); the way the Tea Party revitalized Republican conservatism (Williamson, Skocpol, and Coggin 2011); and the impact of the Women’s Marches (Andrews, Caren, and Browne 2018) and Black Lives Matter protests on the anti-Trump opposition (Meyer and Tarrow 2018), have compelled students of American politics to look for systematic patterns of interaction between movements and parties. In different electoral contexts, movements brought about electoral change by transforming themselves to political parties (Kitschelt 1986; Peterson 2016). The economic crisis gave rise to new political contestants (Hutter, Kriesi, and Lorenzini 2018), more willing than their competitors to intermediate interests by resorting to the streets. In some electoral settings, these political contestants became hybrids of movements and parties, squeezing political support for mainstream party competitors. The scholarly interest on “movement parties” (Kitschelt 2006) on the left (Della Porta et al. 2017) and the right (Castelli Gattinara and Pirro 2019) of the political spectrum has helped narrow the gap in the study of how social movements and political parties interact.

The examination of direct links between protests and elections has been less frequent and has mostly dealt with earlier periods in American politics. Focusing primarily on the local level, a number of studies have sought to trace the effects of social protests on electoral outcomes. For example, the civil rights mobilization in the 1960s and 1970s in Mississippi was shown to have changed Black electoral participation and, over time, local office holding (Andrews 1997). In Southern counties, Ku Klux Klan presence and mobilization had an enduring and positive electoral impact on Republican voting (McVeigh, Cunningham, and Farrell 2014). Evidence of even more direct effects of local protests on elections has come from the analysis of how protest events have affected House results: it has been shown that, depending on the issue, a composite index of protest salience can potentially remove as much as 6 percent from a party’s vote share and reward the other party with 2 percent (Gillion and Soule 2018). Black protests between 1960 and 1972 have also been shown to have a direct effect on voter results: when nonviolent, they increased Democratic vote share by 1.6–2.5 percent, and when violent, they shifted voter support toward the Republicans (Wasow 2020). Studies of the electoral effects of more recent protest waves are rarer, but the evidence points to the same direction. For example, the size of Tea Party protests has been linked to an increase in Republican vote share (Madestam et al. 2013).

Beyond the American context, analyses focusing on the direct effects of social protest on electoral outcomes are even less frequent. One exception is a cross-national analysis of protest events in 30 European countries, which shows how protests driven by worsening economic conditions tend to penalize incumbents and mainstream parties, by accentuating economic grievances (Bremer, Hutter, and Kriesi 2020). A common thread in studies of European and American contexts is that, depending on the issue area, social protest tends to dampen or boost electoral support for political parties. Although social movements have mostly been left out of analyses of electoral change, a nascent body of literature shows the growing need to link social protest with electoral outcomes (Barrie 2021).

HOW SOCIAL MOVEMENTS AFFECT ELECTORAL POLITICS

Given the scarcity of evidence on the direct effects of social movements on electoral politics, it is not surprising that the exact dynamics linking social protest to voting outcomes remain largely unexplored. There is a tendency to assume that protests affect voting behavior by sending informational cues to voters, but the informational link between protests and voting is primarily drawn from the various characteristics of social protest. Since “not all protests are created equal” (Wouters 2019, 406), the main idea here is that, by varying the main attributes of protest, one can identify features of protests that have a distinct impact on the informational signals sent to voters and, hence, electoral outcomes. The issues over which social movements mobilize protesters are a key feature of any protest. Protests over “liberal” issues have been shown to have a different effect on Democratic voter share than protests over “conservative” issues. The main assumption behind the distinction between liberal- and conservative-leaning protests is that they resonate with voters in a different way (Gillion and Soule 2018). Other characteristics that can plausibly affect electoral outcomes are numeric strength (Madestam et al. 2013), unison, diversity, worthiness, and commitment of protesters (Tilly 2004). Once manipulated experimentally, these characteristics are shown to affect how politicians (Wouters and Walgrave 2017) and the public (Wouters 2019) view protests.

Protest tactics have gained growing prominence in efforts to link protest with political outcomes. Taking cues from studies of strikes as well as from analyses of urban riots of the 1960s in the US, earlier scholarship probed the effectiveness of disruptive and violent protests (Giugni 1998). The disruptive nature of some protests has been shown to positively affect policy (Fording 1997) and voting (McAdam and Su 2002). For example, the 1992 Los Angeles riots helped shift support in favor of providing public goods to racial minorities. Violent protest increased local support for more spending in public schools, even when controlling for a number of other variables (Enos, Kaufman, and Sands 2019). Not all the evidence regarding the use of violence in protests points to the same direction, though (Huff and Kruszewska 2016). An elaborate study of Black-led protests between 1960 and 1972 shows that violent protests had a negative effect on the Democratic presidential vote. The key mechanism, here, was the way the media got to frame violent and nonviolent protests and, hence, the way public opinion got to perceive them (Wasow 2020). Individual-level data point to the same direction: extreme protest actions tend to reduce emotional connection, social identification, and overall support for a movement (Feinberg, Willer, and Kovacheff 2020). A study of party identification after the Capitol Insurrection yields similar findings (Eady, Hjorth, and Dinesen 2022).

The Tango Pattern

The growing scholarly focus on protest tactics provides an opportunity to examine other tactical elements of protest beyond violence. Violent disruption is often endogenous to the tactical choice of social movements to directly counter the mobilization of their political opponents. Mobilization and counter-mobilization are known to take place over abortion, gay rights, gun control, or environmental policy in the US; or between nationalist movements and anti-racist groups in Europe (Meyer and Staggenborg 1996, 1630). But this dynamic and dyadic nature of protest is not adequately taken into account in analyses of protest outcomes.

The tango pattern introduced here takes place when movements decide to mobilize against the street presence of their political opponents. It is obviously an uneasy tango: counter-movements tactically choose to protest against their opponents at around the same time and, more importantly, at the same place or in close proximity to the street-level mobilization of political opponents. In this sense, the temporal dimension of the tango pattern—the synchronous move of protesters and counter-protesters—is intimately linked with the spatial dimension. The tango metaphor signifies the nature of the interaction between the opposing actors: the opponents are tightly, rather than loosely, “coupled” (Meyer and Staggenborg 1996; Zald and McCarthy 1987). More importantly, the tango pattern helps draw attention to the temporal and spatial dimensions of counter-protests, which are mostly implied rather than explicated and analyzed in recent scholarship on direct counter-mobilization against right-wing opponents (Hager et al. 2022; Reynolds-Stenson and Earl 2018; Vüllers and Hellmeier 2022; Wood 2021).

The spatial dimension of protest merits specific attention here, as it tends to be overlooked in analyses of the tactical choices social movements make and of the consequences they produce. Despite important insights from critical geography on the social production of space (Lefebvre 1991) and its centrality in urban mobilization (e.g., Agnew 1987; Harvey 1989; Lefebvre 1996; Soja 1989), and notwithstanding efforts to incorporate spatial insights into the examination of protest (Andrews and Seguin 2015; Martin and Miller 2003; Routledge 1997; Schwedler 2022; Zhang and Zhao 2019), the analysis of protest outcomes is only gradually coming to terms with the importance of space (Miller 2000; Miller and Nicholls 2016). The tango pattern highlights the significance of spatial contestation by suggesting how “bare space” relates to protest and, more importantly, by permitting the investigation of “how actors underscore contentious claims through collective performances in symbolically charged public spaces” (Tilly 2000, 140). The social and symbolic meaning that competing groups attribute to public spaces—be they public squares (Arthurs 2010), historical monuments (Forest and Johnson 2019), or “points of oppression” (Kelly-Thompson 2020)—constitutes a significant albeit unexamined component of their tactical repertoire.

The tango pattern and its temporal and spatial dimensions help cast new light on the link between protest mobilization and outcomes. Counter-mobilization is not solely electoral but is also spatial: spatial presence signals antithesis with the messages of opponents and seeks to complicate their organizational logistics (Zeller 2022). The spatial contestation sometimes associated with counter-mobilization can also prompt state authorities to act against political opponents, thereby frustrating their organizational efforts and facilitating their demobilization (Zeller 2021). The tactical choice of spatial proximity and temporal immediacy by counter-protesters affects the likelihood of participation (Hager et al. 2022) and the size of the protest (Biggs 2018). The mere tension generated by the spatial and temporal concurrence of protests might help solidify an “us versus them” understanding (Vüllers and Hellmeier 2022) and further cement bonds between activists (Klandermans and Mayer 2005).

Despite its potential benefits, the organization of protest as a direct response to the mobilization of political opponents is a double-edged sword for social movements. Counter-mobilization is a riskier form of protest because spatial proximity and temporal concurrence risk direct confrontation between opposing groups and, ultimately, the outbreak of violence. The prospect of violence might dampen the participation of not only opposing but also own groups, thereby limiting the effectiveness of the protest events (Borbáth and Hutter 2021; Vüllers and Hellmeier 2022). More importantly, when counter-mobilization turns violent, it risks alienating potential institutional allies and undermining the legitimacy social movements deem necessary to affect political outcomes (Ellinas 2020).

The Timing of Protest

Another tactical component in analyses of how protests affect electoral outcomes is their timing—the temporal proximity of protests to major elections. Recent efforts to examine temporal aspects of protest (Della Porta 2020) have noted how “institutional schedules” (Gillan and Edwards 2020, 508; Jabola-Carolus et al. 2020) can provide the impetus for political mobilization. Movements seeking to influence electoral outcomes can be expected to closely follow the electoral schedule and to increase their protest activity in periods closer to election day. In electoral autocracies, elections are known to set off cycles of protest and become opportunities for mobilizing government opponents (Trejo 2014; Tertytchnaya 2020). But in democratic settings, not all movements can be expected to be more active during election campaigns: protest might alienate the electoral constituencies of political allies (McAdam and Tarrow 2013, 337) and electoral prospects might undermine the need for protest (Meyer 1993, 42). Both reasons might dampen protest prior to elections.

The synchronization of protest and electoral cycles is more likely when movements see political opportunities for electorally advancing their goals or, alternatively, when they see electoral threats—that is, the electoral advancement of their political opponents (Meyer and Minkoff 2004; Vann Jr 2018). This means that the relevance of protest activity to the analysis of electoral outcomes depends on when it takes place. It can be expected that protest activity that is temporally more proximate to elections is more relevant than protest activity that is temporally more distant (Jung 2010). Analyses of how protests affect voting outcomes implicitly assume this temporal proximity: it varies from just a few days (Enos, Kaufman, and Sands 2019); to an election year (Gillion and Soule 2018; Wasow 2020); to the entire legislative period (Bremer, Hutter, and Kriesi 2020). But the temporal proximity of protests to elections has not yet been explicitly subjected to systematic inquiry.

PROTESTING AGAINST THE FAR RIGHT

Social protest against far right actors provides a new opportunity to examine how the interaction of social movements and political parties affects electoral politics. Across different European settings, there are, by now, many examples of social movements mobilizing against the far right. In recent years, dozens of thousands of Germans have taken to the streets to protest against the electorally ascendant Alternative for Germany, holding “Never again” and “Nazis out” banners. The brief attempt of the governing Christian Democrats to cooperate in one region with the far right party sparked protests in major cities, with protesters chanting antifascist slogans. Historical alarm bells have also gone off in Germany against the street-level mobilization of the electorally insignificant National Democratic Party of Germany. Its events have, at times, pushed to the streets thousands of anti-far right protesters. Even gatherings of a few dozen NPD members have attracted sizable crowds across various German localities. Although Germany is a particularly important case for protests against the far right, such protests constitute a broader contemporary phenomenon. For example, the 2019 Sardines movement that sprung up in Bologna and spread throughout Italy managed to gather large crowds to counter the politics of the Lega Nord. The initial aim of the founders was to gather as many people as possible in major public squares to protest the anti-immigrant appeals of the Lega (Hamdaoui 2022).

The visible societal mobilization against the far right has been largely overlooked in the sizable literature on the electoral ascendance of the far right (e.g., Golder 2016). This literature has treated these organizations solely as parties, downplaying the movement-type elements in their repertoire. Recent scholarly emphasis on “movement parties” (Kitschelt 2006; Della Porta et al. 2017; Pirro and Castelli Gattinara 2018; Borbáth and Hutter 2021; Castelli Gattinara, Froio, and Pirro 2022) has helped draw attention to this movement-type, street-level mobilization of the far right and has generated a need to systematically examine the responses against it. Such responses are not only political and institutional (Art 2007; Capoccia 2013; Müller 2016) but also societal (Müller 2022). Protests against the far right have started gaining scholarly attention (Castelli Gattinara, Froio, and Pirro 2022; Vüllers and Hellmeier 2022; Zeller 2021; 2022), but analyses of how these protests affect electoral outcomes remain rare (Colombo et al. 2021).

PROTEST AGAINST THE FAR RIGHT IN GREECE

To analyze the electoral effects of anti-far right protests, we analyze subnational evidence (Pepinsky 2019), by leveraging original data from Greece. Like most European countries, and even before the onset of the economic crisis of the 2010s, Greece witnessed the electoral surge and parliamentary breakthrough of the far right. But unlike most other countries, the country experienced the ascendance of a clearly antidemocratic variant of the far right (Pappas 2016). Greek protests against the far right primarily targeted the GD. Founded in the early 1980s as a National Socialist magazine, GD became a political party in the 1990s and contested all national elections between 2009 and 2019. Mostly known as a violent neo-Nazi gang, the party gained notoriety in the 1990s and 2000s for its assaults on migrants and leftists. In the 2009 parliamentary election, the party received 0.3%. In the 2010s, its extreme ideas and street-level mobilization in migrant-rich communities started gaining electoral traction, and in the May and June 2012 national parliamentary elections, GD managed to enter the national legislature, winning about 7 percent of the vote. By the January and September 2015 parliamentary elections and amid unprecedented refugee inflows (Dinas et al. 2019), GD became the third biggest political party, sustaining its share of the national vote at around 7%, despite the criminal prosecution of its top leadership. In the 2019 parliamentary election, GD narrowly missed the 3% electoral threshold and failed to win parliamentary representation. In 2020, its leader, former members of parliament, and dozens of cadres were convicted for running or being members of a criminal organization and many have been serving substantial prison sentences.

The electoral traction of the GD in the early 2010s along with its growing street-level presence across dozens of Greek localities set the stage for unprecedented societal mobilization against it. To confront the ideological and spatial threat (Andrews and Seguin 2015) posed by the electoral ascendance of the GD, the self-proclaimed Greek antifascist movement brought together hundreds of organizations, groups, and networks, which ranged from trade unions, human rights organizations, and migrant associations to numerous radical leftist and autonomous groupuscules. A few of these were national organizations, but the vast majority were local groups. Antifascist groups organized thousands of events like protest marches, public speeches, and neighborhood assemblies. Across many Greek municipalities, protesters held banners in the streets, handed out leaflets demanding the imprisonment of “the neo-Nazi gang,” and organized festivals and concerts to galvanize support against the GD. Some events involved thousands, and others, only a handful of protesters. The vast majority of these events—like the anti-racist festivals organized on the International Day for the Elimination of Racial Discrimination every March, or demonstrations held every September to commemorate the 2013 murder of an antifascist musician—contested far right claims without involving direct encounters with the GD.

A significant segment of the antifascist movement tactically chose to directly challenge the organizational expansion of the party in various localities, generating the tango pattern described earlier. At the time when the GD was busy setting up local branches across Greece, organizing food rationing in public squares, and holding military-style marches and torch-bearing gatherings at major monuments, antifascist groups staged hundreds of highly localized counter-protests. Anti-far right protests were particularly prevalent in urban, migrant-rich localities where the GD sought to acquire grassroots presence and challenge the local dominance of leftist groups. The sequence of the tango pattern was that the GD would announce an open event in a particular setting and the antifascists would make a call for a counter-event. For example, every June the GD would hold an annual gathering at the Alexander the Great Statue in Thessaloniki, to celebrate his birthday. Antifascists would typically organize a counter-protest at the same time, in a nearby location.

DATA AND METHODS

To examine the electoral effects of protests against the far right, this study relies on the analysis of protest events (Fisher et al. 2019; Hutter 2014b; Koopmans and Rucht 2002). The analysis here relies on 4,479 protest events organized against the Greek far right between the parliamentary elections held on October 4, 2009, and the parliamentary elections held on July 7, 2019 (Ellinas and Lamprianou 2023). To examine how earlier anti-far right protests might affect electoral outcomes, the dataset also includes 266 protest events against the Greek far right organized between June 2006 and the elections held on October 4, 2009, bringing the total sample size to 4,745 protest events (Figure 1). During the period between October 2009 and July 2019, the GD contested all six national parliamentary elections. The dataset includes all events posted by users on the Athens Indymedia in the category “anti-fascism, anti-racism and anti-nationalism.” Founded in 2001, Athens Indymedia is part of the global Indymedia network, set up after the late 1990s, to provide grassroots coverage of anti-globalization protests (Fenton 2020).

Figure 1. The Distribution of Protest Events per Year

Notes: The first bar aggregates 2006 and 2007 events for purposes of visibility. The 2019 data only represent protest events for half year (up to the elections of July 2019).

As an aggregator of information from multiple sources, Indymedia is a unique data source because it provides a comprehensive record of events organized across Greece, like demonstrations, marches, pickets, canvassing, assemblies, festivals, and concerts. The events were identified, assessed, and added to the dataset after meticulous piloting and coding by two coders that lasted several years (Appendix I in the Supplementary Material). The ideological slant of the medium and its reliance on grassroots rather than professional journalistic coverage of protests imposes a notable limitation on the compilation of anti-far right events. The multiplicity of sources reporting these events limits the availability, veracity, and consistency of measures of protest size, a key component for analyzing protest outcomes (Biggs 2018).

Despite this limitation, this unique data source helps deal with other known biases of event catalogs. Unlike major national newspapers, which are noted to have a selection bias in their coverage of protest events (Earl et al. 2004; Walgrave and Vliegenthart 2012), Indymedia posts offer coverage for a much wider range of events. Moreover, Indymedia provides coverage of micro-events in areas away from central or media locations, thereby limiting some of the methodological biases evident in event catalogs compiled from mainstream newspapers (Fisher et al. 2019). Because of the wide geographical range of its coverage, Indymedia allows the compilation of events held simultaneously in multiple locations, avoiding the propensity to treat multi-sited protests as a single record in event catalogs (Biggs 2018, 366). Furthermore, given the emphasis of this study on how protest affects electoral outcomes, Indymedia helps moderate a plausible endogeneity problem—the drop in national news coverage of protest due to the diversion of attention to the national election and limited availability of “news holes” (Oliver and Maney 2000). Finally, Indymedia provides grassroots coverage of highly localized micro-events that are usually off the radar of major national media. These events are usually posted by various anti-far right collectivities or by individual Indymedia users. The aggregation of these micro-events permits an exploration of electoral outcomes that does not rely on the agenda-setting role of high-profile, media-covered protests (Hutter and Vliegenthart 2018; Walgrave and Vliegenthart 2012).

The six parliamentary elections between October 2009 and July 2019 form five intermediate periods of protest (Figure 2). For the period leading to the elections of 2012, protest activity remained at relatively low levels, but there was a significant increase in the last few months before the elections. After peaking in 2013, anti-far right protests lost some steam in the years leading to the January and September 2015 elections. However, there was a gradual but steady increase in the number of events leading to the 2019 elections. Violence was a rather infrequent phenomenon in anti-far right protest events. Out of 4,745 events, around 6% (N = 285) had some degree of violence from anti-far right organizers or protesters.

Figure 2. The Six Parliamentary Elections Contested by the GD, Define Five Intermediate Periods of Protest

Notes: The solid line graphs between elections illustrate the frequency of protest events per month. The pie chart in the right top inset shows the proportion of municipalities with no protests, moderate protest, and frequent protest events, for the whole period from October 2009 to July 2019.

Time-wise, the length of the in-between election periods is very uneven and ranges from 42 to 1386 days. The shortest period of 42 days corresponds to the repeat election of June 2012, due to the undecisive outcome of the May 2012 election. In 2015 there was a repeat election in September 2015, only eight months after the previous election.

The main independent variable (IV) of the study is the count of protest events per municipality, per period. As the pie chart of the right top inset of Figure 2 shows, almost half of the municipalities had no protest events for the whole period from October 2009 to July 2019. The distribution of counts of events per municipality, per period, is extremely skewed, with an excessive number of zeroes and a number of extreme outliers, so it is not appropriate to use in parametric models such as regressions (Appendix II in the Supplementary Material). For this reason, we recoded the protest events per period as a trichotomous IV where category “No protest events” represents municipalities with no events at all, category “Moderate protest” represents municipalities with at most one event per year, and category “Frequent protest” represents municipalities with more than one event per year (see Appendix III in the Supplementary Material for more details). As the pie charts of Figure 2 show, the majority of municipalities had no protest events in any given period, but the proportion of municipalities with moderate and frequent protest increased significantly for the longer periods. The exact distribution of the trichotomous variable per period is presented in Appendix III, Table A in the Supplementary Material.

The main dependent variable (DV) is the electoral results of GD, measured as the percentage of votes received by the GD per municipality. In total, there are 325 municipalities clustered in 74 regional units (see Appendix IV in the Supplementary Material). The correlations between the electoral results of the GD for adjacent elections range from 0.514 to 0.917 (see Appendix V in the Supplementary Material). As illustrated in Figure 2, the electoral results of October 2009 are used as the baseline measure for the elections of May 2012 (r = 0.514, p < 0.001). The correlation between the electoral results of May and June 2012 is very high (r = 0.917, p < 0.001), and the period between the two elections is extremely short (42 days). We hence use the electoral results of October 2009 as a baseline for the elections of June 2012. Subsequently, all previous electoral results are used as baseline for the next election.

At the first stage of our statistical modeling, linear regression models were used to explain the electoral results of the GD per municipality, for each national election beginning May 2012. The main IV is the trichotomous variable of anti-far right protest described above. For each of the models, 2011 census data are used to control for a number of theoretically significant variables. We used immigration as a percentage of the total population to control for the propensity of GD to perform better in municipalities with higher immigrant concentration (Arzheimer 2009; Hangartner et al. 2019). In accordance with studies measuring the electoral effects of protest events (Enos, Kaufman, and Sands 2019; Gillion and Soule 2018; Wasow 2020), we also controlled for population size. To avoid numerical problems in the estimation of the model, we use the natural logarithm rather than the absolute size of the population of municipalities which ranges from 766 to circa 664,000. We use the average age of the population for each municipality to control for the propensity of far right parties in general (e.g., Stockemer, Lentz, and Mayer 2018) and the GD in particular to perform better among younger voters. We use the proportion of unemployed people per municipality to control for economic grievances (e.g., Arzheimer 2009; Sipma and Lubbers 2020) and a dichotomous variable as an indicator of whether GD has a registered branch in each municipality. To control for the possible spillover effects of geography (Hainmueller and Kern 2008), we model municipalities as nested in regional units using generalized linear mixed-effects models.

For all models, we investigated both the assumptions and the model fit (Gelman and Hill 2006). Finally, we investigated additional alternative models, by replicating our analysis using additional controls and other theoretically interesting variables to confirm the robustness of our findings.

At the second stage of the analysis, we investigated more refined models, to test the key protest dynamics of tango and timing, which we expect drive the electoral results of the GD. To investigate the tango effect, we counted the number of counter-mobilization events organized in each municipality as a response to a GD event during any given period of time in-between elections (see Appendix III, Table B in the Supplementary Material). A tango event is an event organized in the same municipality as a GD-organized event, explicitly as a reaction to that GD-organized event. As mentioned earlier, such events would typically include a counter-protest, -march or -gathering taking place at around the same time and place where the local GD branch would organize an event. The GD event is also recorded in our dataset, when an explicit reference to it is made in the Indymedia post mentioning the anti-far right event. In other words, when the anti-far right event is explicitly organized as a response to the far right event.

There were 59 tango events in 31 municipalities for the period between October 2009 and May 2012. For the period of May 2012 to June 2012, there were only seven tango events, one per municipality, and we hence excluded the June 2012 election from the analysis. There were 178 tango events in 77 municipalities during the period June 2012 to January 2015. For the period of January 2015 to September 2015, there were only 14 tango events in nine municipalities, so we excluded the elections of September 2015 from further statistical analysis. There were 85 tango events in 38 municipalities during the period September 2015 to July 2019. Due to the small number of tango events per municipality per period, we operationalized new dichotomous IV, which had the value of “1” or “0” depending on whether there were tango events organized in a municipality in a given period or not. For each of the three periods remaining in the analysis, the dichotomous IV was used as the main IV in linear regression models.

To investigate the expected effect of timing, we split each period in-between elections in two parts: The six months preceding an election is defined as the “proximate” part of the period, and the rest of the time going backwards to the previous election is the “distant” part. For example, for the elections of May 2012, the period between the previous election of October 4, 2009, to November 6, 2011, is the distant period and the six-month period between November 6, 2011, to the elections of May 6, 2012, is the proximate period. By default, the two shortest in-between election periods are too short for the six-month cutoff between proximate and distant protests and are hence excluded for the timing models, as was the case for the tango models.

For the distant and proximate parts of the three remaining periods, we counted the number of protest events (Appendix III, Table C in the Supplementary Material). For the period October 2009 to May 2012, there were 0.4 events per day for the distant period and 0.9 events per day for the proximate period. For the period June 2012 to January 2015, there were 1.9 events per day for the distant period and 0.7 events per day for the proximate period. For the period of September 2015 to July 2019, there were 1.5 events per day for the distant period and 1.8 events per day for the proximate period.

For each period, we created a new variable where we classified each municipality in one of four categories: (a) had no events in both distant and proximate parts of the period, (b) had at least one event in both proximate and distant parts of the period, (c) had at least one event but only in the distant part of the period, and (d) had at least one event but only in the proximate part of the period. For each of the three periods remaining in the analysis, the categorical IV was used as the main IV in linear regression models.

We considered the possibility that confounding effects might introduce bias in our results. To investigate the possibility of endogeneity between protest events and other theoretically significant explanatory variables, we used a two-stage (instrumental variable) model (Sovey and Green 2011). Our instrumental variable of choice is the number of students studying at various university departments and programs in each municipality. It is a variable that takes into account the historically and empirically grounded expectation that “university campuses are frequently hotbeds for student mobilization” (Zhang and Zhao 2019, 101; see also McAdam 1986; Sewell 2001). A fundamental requirement for such a two-stage model is that the instrumental variable must be independent of the DV. We consider this requirement to be satisfied because student numbers in various municipalities are independent of the electoral results of the GD and, more importantly, because university students usually vote in the municipality of their permanent residence, not that of their university department or program.

RESULTS

A linear mixed-effects model was built for each of the national elections from May 2012 onward (Appendix VI in the Supplementary Material). Model 1 (Table 1) uses the electoral results of the May 2012 elections as a continuous DV, controlling for the electoral results of the baseline elections of October 2009. As expected by the literature, the larger the population, the lower the age of the population, and the higher the concentration of immigrants, the higher the electoral results of the GD. There is a high inter-class correlation (ICC = 0.48) which suggests that municipalities within the same administrative region tend to have similar electoral results for the GD. Municipalities with moderate protest (at most one event per year for the period) yield significantly lower results for the GD (three-quarters of a percentage point) compared to the municipalities with no protest events for the period. Municipalities with more than one event per year for the period yield significantly lower results for the GD (more than a percentage point) compared to the municipalities with no events for the period. These results are not only statistically, but also practically, significant: with a national yield of around 7% in the elections of May 2012, the impact of frequent anti-far right protests corresponds to a reduction of around one-sixth (1.09/6.97 ≈ 16%) of the electoral power of GD. Viewed alongside the effect of other known variables in analyses of far right voting, such as immigration (Arzheimer 2009; Hangartner et al. 2019), the impact of protest on voting is substantial. ¹

Table 1. Basic Linear Models Explaining Electoral Gains of the GD (Regions as Random Effects; DV Is the Electoral Results)

* Note: For Model 2, we used the IV of protest events for the whole period October 2009–June 2012. If we use only the events for the 42 days between May–June 2012 elections, the coefficient for the “at most one event per year” becomes −0.65 (p = 0.055) instead of −0.64 (p = 0.013) and the coefficient of “more than one event per year” becomes −0.86 (p = 0.02) instead of −0.81 (p = 0.007).

Model 2 uses the electoral results of the June 2012 elections as a continuous DV, controlling for the results of the elections of October 2009 (as for the previous model). The larger the population and the lower the age of the population, the higher the electoral results of the GD, but the coefficient of immigration is not statistically significant. There is a very high inter-class correlation (ICC = 0.54), which suggests that municipalities within the same administrative region tend to have similar electoral results for the GD. The effect of anti-far right protest is similar to that of Model 1: municipalities with protest events yield significantly lower results for the GD compared to the municipalities with no events.

Model 3 uses the electoral results of the January 2015 elections as a continuous DV, controlling for the results of the elections of June 2012. The larger the population, the higher the electoral results of the GD, but the coefficients of immigration and the age of the population are not statistically significant. There is a high inter-class correlation (ICC = 0.37), which suggests that municipalities within the same administrative region tend to have similar electoral results for the GD. Municipalities with frequent protest (more than one activity per year for the period) yield significantly lower results for the GD (more than a third of a percentage point) compared to the municipalities with no events for the period. Municipalities with moderate protest do not yield lower results for the GD compared to those with no events. These results are not as impressive as those of Models 1 and 2.

In Models 4 and 5, the coefficients are much smaller and are not statistically significant.

Regarding the parsimony of our models, other variables were also tested but were not found to have significant contribution in the models. For example, the legacy of earlier protest against the far right (protest events before the baseline electoral measure of 2009) did not affect subsequent electoral results of GD per municipality for the May 2012 electoral breakthrough of the GD. Also, the physical presence of a GD branch in a municipality (McVeigh, Cunningham, and Farrell 2014) prior to each election, the proportion of unemployed people per municipality, and abstention rates (Castro and Retamal 2022; Klein Teeselink and Melios 2021) did not affect the electoral results (Appendix VII in the Supplementary Material).

We also investigated whether our findings remain stable after considering the effect of left-wing electoral strongholds in the model. Adding the 2009 electoral results of three left-wing parties, the radical left Syriza, the communist KKE, and the extra-parliamentary Antarsya in the model of May 2012 does not significantly change our findings (with the exception of one of the models, where the Syriza electoral results for the 2009 elections render the coefficient of moderate protest not significant, but not the coefficient of frequent protest; see Appendix VIII in the Supplementary Material).

We also investigated whether violence was a significant predictor of the electoral results of the GD. In the models of Table 1 described above, we added a dichotomous variable indicating whether there was at least one violent protest event per municipality per period. Violence did not have statistically significant results, which suggests that violent events neither benefit nor harm the electoral results of the GD (see Appendix IX in the Supplementary Material).

Finally, the fundamental assumptions of linear regression (e.g., normal distribution of residuals, homoscedasticity, and so forth) were investigated (e.g., histograms, q–q plots), but no substantial violations were found (see Appendix X in the Supplementary Material for some visual aids).

We considered the possibility of confounding effects in the models of Table 1. Our instrumental variable of choice is the number of students studying at various university departments and programs in each municipality. The instrumental variable is a very good predictor of protest events (e.g., the correlation between the count of protest events and the number of students per municipality for the period September 2015–July 2019 is r(323) = 0.66, p < 0.001; see Appendix XI in the Supplementary Material for more information and pertinent tests). The models of Table 1 were replicated using instrumental variable regressions, and some results are presented in Appendix XII in the Supplementary Material. The coefficient of protest activities remains significant for the 2012 models (as was the case for Table 1), confirming our original findings. Once the instrumental variable is included in the model, the coefficient for the model of January 2015 is marginally not statistically significant. ²

TANGO AND TIMING: THE DYNAMICS OF PROTEST AGAINST THE FAR RIGHT

Moving from our basic to more refined models, we first examine whether the electoral outcomes of the GD are affected by a tango pattern, an action–reaction relationship involving events organized by the GD and counter-protests organized in the same municipality in response to these GD events. We used the same mixed-effects models as in Table 1, the only difference being that we replaced the ordinal IV of protest events with the dichotomous version of the tango variable as explained earlier (also see Appendix III, Table B in the Supplementary Material for descriptive statistics). Figure 3 compares the frequency of tango events to the frequency of all protest events per period. It is interesting that the frequency of tango events drops dramatically after 2013, although the frequency of protest events rebounds before the 2019 elections.

Figure 3. The Distribution of Tango Protest Events per Year

Notes: The first bar aggregates 2006 and 2007 events for purposes of visibility. The bars represent anti-far right events and the solid line represents tango events. The 2019 data only represent protest events for half year (up to the election of July 2019).

The results (Table 2) suggest that, for the elections of May 2012, municipalities with at least one tango event had much lower electoral outcomes for the GD compared to municipalities with no tango events. With a national yield of around 7% in the elections of May 2012, the impact of having tango events corresponds to a reduction of around 13% of the electoral power of GD (circa 0.9 percentage point out of 7). The coefficients of tango events were not significant for the January 2015 and July 2019 models, although they had the same sign as that of May 2012.

Table 2. “Tango” Linear Models Explaining Electoral Gains of the GD (Regions as Random Effects; DV Is the Electoral Results; “Tango” Effects as a Dichotomous Variable)

Second, we examined whether the timing of protest events, more specifically, their temporal proximity to the parliamentary election, has an effect on the electoral outcome of the GD. We used the same mixed-effects models as in Table 1, the only difference being that we replaced the ordinal IV of protest events with the categorical variable of distant/proximate events and, as explained before, we dropped two elections with very short in-between periods. Some descriptive statistics are presented in Appendix III, Table C in the Supplementary Material. Figure 4 presents the relative frequency of distant and proximate events. For example, for the period October 2009 to May 2012, there were 0.9 events per day for the last six months before the May elections, but only 0.4 events per day for the previous part of the period. ³

Figure 4. Timing of Protest Events per Period

The results (see Table 3) for May 2012 suggest that organizing at least one proximate protest event against the far right, compared to organizing no events at all, corresponds to a smaller electoral outcome for the GD, similar in magnitude to that identified by previous models which was around one-sixth of the 7% of the national vote. Municipalities with protest events in the distant period only, did not have a smaller electoral outcome compared to those which had no events at all. Municipalities which had both distant and proximate events also yielded significantly lower electoral outcomes for the GD. The results were partly statistically significant for the January 2015 model as the coefficient of having both distant and proximate events was statistically significant.

Table 3. “Timing” Linear Models Explaining Electoral Gains of the GD (Regions as Random Effects; DV Is the Electoral Results; “Timing” Effects as a Categorical Variable with Four Categories)

DISCUSSION

The literature on how social movements and political parties interact rarely examines the direct effects of this interaction on electoral outcomes. This study contributes to this literature by specifying a model that incorporates distinct protest dynamics affecting electoral outcomes. First, our analysis shows a direct relationship between social movement mobilization and electoral outcomes: protests against the far right took a toll on its electoral result. The electoral effect of protest is far from obvious: social mobilization against the far right has, at times, raised questions about its utility (Mayer 1995). Such skepticism about the effectiveness of protests against the far right relates to the association of this type of mobilization with political disruption, which is thought to alienate political and institutional allies (Borbáth and Hutter 2021, 3). In contrast to these expectations, the evidence presented here shows that protest can be an effective means to dampen public support for the far right. The effect of protests was sizable: in those localities where protest events were more frequent, the far right lost as much as 16% of its electoral strength compared to those municipalities without protests. Like other studies measuring the direct effects of protest on electoral results (Colombo et al. 2021; Gillion and Soule 2018; Wasow 2020), we also found a substantial effect.

Second, our study identifies specific protest dynamics that help account for the varying effect of protest on electoral results. We found protests to be quite effective when “in tango” with the targeted political actor—when organized at around the same time and, more importantly, the same place as those of far right actors. By examining the tango pattern within particular space, our article incorporates dynamics of protest that help redress the limitations of aspatial analyses of political contention (Miller 2000; Miller and Nicholls 2016; Sewell 2001; Tilly 2000). More importantly, the analysis of the tango pattern casts new light on questions regarding the effectiveness of counter-mobilization. Earlier evidence suggested that counter-mobilization might be ineffective. For example, in Germany, counter-mobilization against the far right Pegida reduced the likelihood that its supporters will stop protesting (Vüllers and Hellmeier 2022). Evidence from interviews with far right activists suggests that social pressure might help cement bonds between them (Klandermans and Mayer 2005), thereby solidifying group commitment and their appetite for mobilization. Our evidence shows that counter-mobilization can have a strong effect on electoral outcomes: where they occurred, dyads of action from and in reaction to the far right depressed voter support for the GD by as much as 13%.

The second protest dynamic shown to be electorally relevant is the timing of protests. The evidence presented shows that the synchronization of protest and electoral cycles makes protest more effective: protests against the far right taking place right before the next election are much more effective than those temporally more distant. The importance of temporal proximity to elections has already been identified, but the link between contentious and electoral cycles has mostly been indirect (Tilly 1997). For example, the 2012–2013 protests in Argentina against the Kirchner government facilitated coalition-making by the opposition in the upcoming congressional election (Gold and Peña 2019). And the Black Lives Matter protests facilitated interracial alliances that helped generate the Blue Wave in the 2018 midterm elections (Schram and Fording 2021). This study offers one of the few analyses of the direct effects of the overlap of protest and election cycles.

Although this study has managed to show a direct association between protests and elections, it has also reinforced earlier findings, “that protest has great limits as a movement strategy” (Amenta et al. 2010, 297). The analysis here shows that anti-far right protests have a strong effect in some but not all elections. This might be because, just like protests, not all elections are equal. Some elections can be considered “exceptional” (Blee and Currier 2006, 263) or “critical” (Key 1955) in that they present a more favorable opportunity structure (Kitschelt 1986; Kriesi et al. 1992) for protest actors to influence outcomes due to the increased fluidity of electoral alignments. While the findings of this article help account for subnational variation, it is important to note that anti-far right protests were most effective when national electoral realignments—including the electoral breakthrough of the far right—were at their peak (Dinas and Rori 2013).

The findings of our study help go beyond these national structural facilitators of movement outcomes by specifying how tactical characteristics of protests depressed voter support for the far right at the subnational level in some but not all elections. First, although protest levels remained high throughout this period, the tango pattern was most visible in the 2012 elections, when protest was most electorally effective. The decoupling of far right and anti-far right mobilization in the subsequent years can go some way to explain why the electoral effect of protests seems to wither away after some time. Second, protests became less effective in subsequent elections because the protest cycles were no longer synchronized with electoral cycles. One of the reasons that made the 2012 Greek elections exceptional or critical was, in fact, the temporal proximity of protest and election cycles.

The reasons why these protest tactics have a different impact on electoral outcomes over the period under study merits more attention. Borrowing from the emphasis of scholarly works on how movements are most influential in earlier stages of political processes (Soule and King 2006; Johnson 2008), it is plausible that the varying electoral impact of anti-far right protests in subsequent electoral periods relates to the success of the movement in transferring its plight to the institutional arena of politics. Political mediation of anti-far right protests by like-minded political and institutional actors (Amenta et al. 2010, 298) led to restrictive measures against the far right party, facilitating its subsequent withdrawal from street-level mobilization (Ellinas 2020). This withdrawal limited the spatial threat the GD posed to its opponents and reduced the tactical necessity for spatial contestation. The spatial withdrawal of the target actor can largely explain the decoupling of far right and anti-far right protests shown in Figure 3. The varying impact of anti-far right protests, then, seems to be largely associated with the alteration of the protest patterns specified in this model.

Similar protest dynamics against the far right are gaining growing scholarly visibility (Colombo et al. 2021; Hager et al. 2022; Vüllers and Hellmeier 2022; Zeller 2021; 2022), but are not always as pronounced as in the single context of this study. Our findings are plausibly generalizable to settings where “far-right protest mobilisation, and counter-mobilisation in reaction to them, tend to feed each other” (Castelli Gattinara, Froio, and Pirro 2022, 1033), but less so in environments where far right actors do not rely as much on street-level activism to make electoral inroads. In this sense, counter-protests are probably more effective against far right movement parties (Pirro and Castelli Gattinara 2018; Borbáth and Hutter 2021), which rely on street presence and make spatial claims to reach their electorates. An analysis of street-level activism of the GD shows that it added as much as 22% to its electorate (Ellinas and Lamprianou 2019; see also Dinas et al. 2016). It is hence plausible that the effectiveness of counter-protests feeds on the electoral efficacy of far right protests. It is also plausible that the effectiveness of anti-far right protests relies, at least in part, on the capacity of mobilizers to attract sizable crowds to their events—a parameter that is known to be important (Biggs 2018) but missing from this analysis.

By showing how counter-protests can be electorally effective, the evidence presented here raises questions about the micro-mechanisms linking such protests with voting. The data used here cannot help discover the exact links between small-scale protest events and individual-level voter behavior—links that are hard to draw without survey, experimental, interview, or ethnographic data. Given the limitations imposed by the absence of such data, the evidence leveraged here can only be suggestive of the specific mechanisms linking highly localized protests (that are usually off the radar of national media) with electoral outcomes. The nature of the data utilized in this article makes it plausible that local protests reach voters without necessarily relying on the attention-generating and agenda-setting function of national media (Baumgartner and Mahoney 2005; Hutter and Vliegenthart 2018; Walgrave and Vliegenthart 2012). Lacking national media coverage, small local protests might have an electoral effect through direct informational cues sent to the locality. Rather than relying on the publicity generated “outside the immediate arena in which protest takes place” (Lipsky 1968, 1151), demonstrations can affect the localities in which they are organized without diffusing nationwide (Ayoub, Page, and Whitt 2021). Instead of triggering a bystander backlash (Selvanathan and Lickel 2019), local protests might generate bystander sympathy or support (Wouters 2019).

CONCLUSION

More than a decade after the observed bifurcation of scholarship on social movements and electoral politics (McAdam and Tarrow 2010), there is still a scarcity of research directly linking protests with electoral outcomes. This study helps fill this gap by showing how counter-mobilization affects the electoral fortunes of the targeted actor. More importantly, it shows how distinct dynamics of protest help account for electoral outcomes.

The empirical focus of the study—protests against the far right—is timely. From Athens to Hamburg and from Seattle to Rome, local protests against the far right are gaining increasing visibility, raising questions about the proper role of social actors in institutional and political efforts to marginalize extremism (Müller 2022). This study offers significant evidence about the effectiveness of such protests: protests against the far right depress voter support. Drawing on an original dataset of protest events for a period over a decade, this article shows that protests against the far right can have a direct negative effect on its electoral performance. Based on the findings presented here, counter-movements against the far right are likely to be most effective when they follow the tango pattern, organizing their protests to counter those of the far right. They are also more likely to affect elections when they synchronize their protest activity with electoral campaigns.