Online and offline political participation in the 2014 presidential elections in Salvador¹

Abstract

This study investigates the influence of sociodemographic variables (gender, age and schooling), family income, political attitudes (civic engagement and party preference) and the use of digital social media platforms on the online and offline political participation of voters of Salvador (in the state of Bahia, Brazil) during the 2014 presidential elections. The results of multinomial statistical analysis proved that social media engagement was determinant for online and offline political participation. On the other hand, a higher education was decisive for web participation. Multivariate analyses also confirmed the Reinforcement Hypothesis (DI GENNARO; DUTTON, 2006; NORRIS, 2001), evidencing that the most engaged voters in conventional participation used digital technologies to reinforce their participatory activity. The data of this study was obtained through household survey conducted in January 2015 in Salvador to investigate the use of Information and Communication Technologies (ICTs) in the electoral decision-making process.

Keywords
Digital democracy; Internet; Political behavior; Political participation; Presidential elections

Resumo

Este estudo investiga a influência das variáveis sociodemográficas (sexo, idade e escolaridade), renda familiar, atitudes políticas (engajamento cívico e preferência partidária) e o uso de plataformas digitais de mídias sociais na participação política online e offline dos eleitores de Salvador durante as eleições presidenciais de 2014. Os resultados da análise estatística multinomial comprovaram que o engajamento através de mídias sociais foi determinante para a participação política online e offline. Por outro lado, o nível de escolaridade superior foi decisivo para a web-participação. As análises multivariadas também confirmaram a Hipótese de Reforço (DI GENNARO; DUTTON, 2006; NORRIS, 2001), demonstrando que os eleitores mais engajados na participação convencional usaram as tecnologias digitais para reforçar sua atividade participativa. Os dados usados neste estudo foram obtidos através de uma pesquisa domiciliar realizada em janeiro de 2015, em Salvador, para investigar o uso das Tecnologias da Informação e da Comunicação (TICs) no processo decisório eleitoral.

Palavras-chave
Democracia digital; Internet; Comportamento político; Participação política; Eleições presidenciais

Resumen

Este estudio investiga la influencia de las variables sociodemográficas (sexo, edad y escolaridad), renta familiar, actitudes políticas (compromiso cívico y preferencia partidaria) y uso de medios sociales digitales en la vida política online y offline de los electores de Salvador, en el estado de Bahia – Brasil, durante las elecciones presidenciales de 2014. Los resultados del análisis estadístico multinomial comprobaron que el compromiso a través de medios sociales fue determinante para la participación política online y offline. Por otro lado, el nivel de escolaridad superior fue decisivo para la web-participación. Los análisis multivariados también comprobaran la Hipótesis de Refuerzo (DI GENNARO; DUTTON, 2006, NORRIS, 2001), demostrando que los electores más comprometidos en la participación convencional usaron las tecnologías digitales para reforzar su actividad participativa. Los datos del estudio fueron obtenidos a través de una encuesta domiciliar en enero de 2015, en Salvador, para investigar el uso de las Tecnologías de Información y Comunicación (TICs) en el proceso decisorio electoral.

Palabras clave
Democracia digital; Internet; Comportamiento político; Participación política; Elecciones presidenciales

Introduction

This study is an addition to the Brazilian literature on the impact of digital technologies on the political sphere in recent years. Its central objective is to investigate the influence of sociodemographic variables, family income, political attitudes (civic participation and party preference) and the use of digital social media platforms (Facebook, Twitter, Instagram etc.) and video-sharing (YouTube) on the political participation of voters of Salvador during the 2014 presidential campaign. For the first time in Brazil, we present a methodological differential: a simultaneous investigation of offline and online political behavior of the fourth largest electorate in Brazil by conducting a household survey².

Based on this methodological approach, this study raises the following questions: What is the impact of the use of digital technologies, especially social media platforms, by Salvador’s voters on the electoral decision-making process? What are the most important individual, social and material determinants of this process? Did digital technologies attract new participants or reinforce the participation of those already active offline? Why does this matter?

The decline of traditional political participation in liberal democracies is a phenomenon of which there is strong empirical evidence, such as the high levels of abstention from polls and the lack of engagement in the work of electoral committees and party assemblies (NORRIS, 2002; 2007; 2011; PUTNAM, 2015). Changes in traditional communication systems, with the emergence of the internet, are seen as capable of promoting new forms of mobilization and civic engagement (NORRIS, 2001; BUCY; GREGSON, 2001) and of attracting new participants to the political sphere with a potential to reduce traditional participation inequalities due to socioeconomic cleavages (KRUEGER, 2002).

From this perspective, in the last two decades, a growing literature has addressed the use of Information and Communication Technologies (ICTs) in the process of civic engagement and political participation as a way to reduce the participation deficit of representative democracies (NORRIS, 2001; 2002; BIMBER, DAvIS, 2003; BEST, KRUEGER, 2002). A large volume of empirical research is devoted to the study of impacts of the internet on electoral campaigns (TOWNER; DÚlIO, 2013; 201 vITAK et al, 2011; SCHlOZMAN et al, 2010).

In Brazil, several researchers have addressed the phenomenon. Theoretical and methodological aspects are thus discussed (GOMES et al, 2011); experiences, issues and challenges in the use of digital technologies in electoral campaigns (MARQUES et al, 2013) and the potential of interactive tools, especially a political use of digital social media platforms (CERVI et al, 2016, ALDÉ; MARQUES, 2015) and constraints of political activism online (RIBEIRO et al, 2016, SANTANA, 2015), within a set of studies that also include a participatory bias.

Thus, this study shares the perspective that, in the current Brazilian scenario³, internet tools contribute to reinforce the participation of people who are traditionally engaged and people with higher levels of income and education (SCHlOZMAN et al, 2010; 2012; NORRIS, 2001; DI GENNARO; DUTTON, 2006). It also confirms the results of previous studies (TOWNER, 2013: VITAK, 2011), demonstrating that interactions promoted in digital social media platforms influenced political-electoral participation of electors offline and online.

To facilitate the understanding of the issues and analyses proposed, this study was developed in five sections, including this introduction. The second section addresses the concept of political participation and the crisis of representative democracy, as well as the unfolding of this phenomenon with the arrival of the internet, especially digital social media platforms. The third section presents the method and the results of an opinion poll conducted in Salvador, capital of the state Bahia (Brazil), in January 2015, which comprises the basis for this article. The poll comprises the variables used to investigate the determinants of online/offline participation, statistical analyses and results. In the fourth section, the discussions are presented and, in the fifth section, the conclusions are expounded.

Concept of participation

Political participation is defined as the attempt to influence some political outcome or to exercise control over decision-makers at a governmental or non-governmental level (NORRIS, 2007; BRADY, 1999; VERBA; NIE, 1972). This study focuses on only one of the dimensions of participation (BRADY, 1999). It addresses the cluster “Campaign work”, with modalities of participation used during election periods for the choice of governors (donation of funds, commitment in committees, etc.). Such process legitimizes contemporary democracy (PATEMAN, 1992), but records a steep decline in some countries (NORRIS, 2007).

This is because, in the last three decades in most Western democracies, citizens dissatisfied with the performance of governments and disbelieving in the institutions of representative regimes have moved away from conventional participation channels (voting, parties, involvement in committees, etc.) (NORRIS, 2011; DALTON, 2004; INGLEHART, 1977; PUTNAM, 2002). At the same time, they engaged in alternative repertoires (boycotts, protests, petitions, etc.) (NORRIS, 2011; DAlTON, 2004; INGlEHART, 1977). Norris (2011) attributed the phenomenon to the emergence of a critical citizenship characterized by a growing skepticism regarding the directions of liberal democracy.

At the origin of this dissatisfaction, there is a “democratic deficit”, as Norris (2011) states and defines as the difference between the expectations of citizens and the performance of governments. Along the same lines, Dalton (2004) identified an imbalance between the state’s supply capacity and new environmental, social, ethnic-racial as well as other demands by social organizations. Putnam (2002; 2015) concluded that the decline of community life was responsible for a massive civic disengagement in the United States and in consolidated democracies in Europe, leading to a decline in conventional political participation (PUTNAM, 2002; 2015). Inglehart (1977; 2009) emphasized a cultural shift towards values of self-expression (INGlEHART; WElZEl, 2009; INGlEHART, 1977).

In this conjuncture, the use of digital technologies as an instrument to reinvigorate social capital and to strengthen democratic participation divides opinions. The central question is: does participation mediated by internet tools allow citizens to exert influence over decision-makers? In other words: is it a participation in the classical sense? This is what we will discuss next.

Internet, social media and political participation

Morozov (2009) called the practice of slackativism, a criticism especially addressed to Facebook users, arguing that such habits induce individuals to the idea that they contribute to changes in the world with the click of a mouse, when in fact this does not occur. Such a view is refuted by Margetts and her peers (2015), for whom there is a culture shared by the political mainstream according to which “the political contribution must involve hard work and some types of rites of passage” (MARGETTS et al, 2015, p.18). In this context, online participation is still regarded “as inferior to offline participation” (MARGETTS et al, 2015, p.18), despite the impacts of internet tools on the political sphere around the world.

The participation mediated by digital social media platforms, known as social networks⁴ in Brazil, is the most significant example of the potential of internet today in promoting civic engagement and mobilization (CASTEllS, 2012). So far, there seems to be a consensus that such websites promote individual empowerment (MARGETTS et al, 2015) and strengthen citizens’ autonomy of action vis-à-vis civil society institutions and organizations (governments, parties, parliaments and others) (MARGETTS, 2015; GOMES, 2011). Independent from such traditional mediation structures, individuals articulate through social media websites around common interests and promote actions on a small and large scale, including beyond their territorial boundaries (MARGETTS, 2015; CASTEllS, 2012).

Some scholars argue that the use of such platforms promotes increased political offline participation (BODY, 2008; TOWNER, 2013; TOWNER; DUlIO, 2011; VITAK et al, 2011). Others advocate no links to it (BAUMGARTNER; MORRIS, 2010; ZHANG et al, 2010). A third line of studies states that such websites influence political participation both online and offline (TOWNER, 2013; ZÚÑIGA, 2014; vITAK et al, 2011). There are also those who associate the use of such websites with civic participation, but not with political participation, on the grounds that they target relationships with friends and may stimulate community involvement (ZHANG et al, 2010).

One of the reasons for mobilization, engagement and participation of individuals through internet may also be that such activities do not demand civic competences and require much less time than the traditional political participation, as the researchers Best and Krueger (2005) pointed out. Both authors pointed to web navigation skills and political interest as the most important resource for online activism. However, they emphasized that the potential of digital tools to attract new participants may only be realized in a context of universal access to the internet. Outside of this scenario, according to Best and Krueger (2005), the internet contributes to reinforcing the status quo of traditional activists, with higher levels of education and income, with the exception of young people, generally more skilled at browsing online, as the researchers claimed.

Thus, internet access and participation online, so far, have reproduced traditional inequalities of participation, with an improvement in the underrepresentation of young people and women in the participatory process mediated by the web (LOADER et al, 2014; SCHlOZMAN et al, 2010; 2012; STOllE; HOOGHE, 2004). They are attracted to non-hierarchical or less formal forms of participation offered by tools such as digital social media platforms (SCHlOZMAN et al, 2010; 2012).

As can be seen, there is no consensus so far on the impacts of internet tools on political participation online and offline. Thus, this study seeks to make this contribution in order to clarify the discussion on issues raised by the theoretical and empirical literature on the subject. To do so, we present below three work hypotheses:

• H1: The participation mediated by digital technologies reproduces the inequalities of traditional participation, favoring groups already politically engaged with higher levels of income and education (SCHlOZMAN et al, 2010; DI GENNARO; DUTTON, 2006; BEST; KRUEGER, 2005). It can be stated, therefore, that the online political participation in the 2014 presidential elections in Salvador confirmed the Reinforcement Hypothesis (DI GENNARO; DUTTON, 2006);

• H2: Young people are present in greater numbers in the virtual universe (SCHlOZMAN et al, 2010) and have a greater ability to navigate through the internet, the main predictor of web participation, according to Best and Krueger (2005). Thus, it is possible to state that being between 18-29 years old was determinant for online participation;

• H3: Digital social media platforms influence online and offline participation (TOWNER, 2013; TOWNER; DUlIO, 2011). It can be stated, therefore, that the use of such websites was determinant for the digital and conventional participation of voters of Salvador.

Research and method

In order to verify the hypotheses, we analyzed the results of a household survey conducted in the city of Salvador in January 2015 which encompass several variables related to the use of digital technologies in the electoral decision-making process. The sample size was set at 280 interviews, with a margin of error of six points above and below and a confidence interval of 95.5%. This means that if the sample was repeated a hundred times, the same results would be obtained in 95.5% of the cases. The sample design was based on data from “Electoral Statistics 2014” of the Superior Electoral Court (Tribunal Superior Eleitoral – TSE) and on the projection of the population of Salvador for the year 2015 (2,926,442 inhabitants), according to the last Urban Development Master Plan (Municipal law no. 7,400/2008).

Respondents were selected by use of proportional quotas according to the variables gender, age and education level, the same criteria used by the “Statistics of the 2014 Electorate” of the Superior Electoral Court. The interviews were distributed in domiciles of the 17 administrative regions of Salvador⁵, obeying the territorial division provided by the Development Master Plan and the population size of each area. The voters of the 18^th administrative region, representing the islands of Maré, Madre de Deus and Frades, were included in the Suburb Railroad sample⁶.

Of the total number of interviewees in the sample (n = 280), 45.7% were male and 54.3% were female. As for age, 13.2% ranged between 18-24 years old, 25.4% between 25-34 years old, 21.8% between 35-44 years old, 24.3% between 45-59 years old, and 15.4% were 60 years old or older. Education level was distributed as follows: up to complete primary school (43.9%), high school (46.1%), and higher education (10.0%). Regarding the distribution of family income, 23.6% earned up to a minimum wage, 30.0% earned more than one up to two minimum wages, 24.6% earned more than two to three minimum wages, 11.4% earned more than three to five minimum wages, 5.4% earned more than five to ten minimum wages, 1.8% earned more than ten to twenty minimum wages, 0.7% earned more than 20 minimum wages, 0.7% did not know how to answer, and 1.8% refused to answer.

Among the 280 voters in the sample, 183 had access to the internet and 97 had no connection to the internet. Among those who were connected to the internet, 22 were not social media users and 161 voters used more than one platform: 147 Facebook users, 136 WhatsApp users, 46 Instagram users, 36 YouTube users, 19 Twitter users, 1 MySpace user and 1 Google+ user. Among the voters in our sample who said they had a preferred party (37.5%), 76 (27.1%) indicated PT, 19 (6.8%) indicated DEM, 4 (1.4%) indicated PMDB, 2 (0.7%) indicated PSB and 2 (0.7%) indicated other small parties, such as PDT/PSD. Regarding civic participation, 232 voters answered that they were not engaged in any institution, organization, association or movement, 26 of them reported participating in religious groups linked to churches, eight participated in neighborhood or professional associations, four were in trade unions, three were in NGOs, and four in other associations.

Sociodemographic variables (gender, age and schooling), family income, political attitudes (civic engagement and party preference) and use of social media (Facebook, WhatsApp, Instagram, Twitter) and video-sharing (YouTube) were used as independent variables⁷. Previous studies (ZÚÑIGA, 2014; TOWNER,2013; TOWNER; DUlIO, 2011; vITAK 2011; SCHlOZMAN et al, 2010; 2012; VERBA et al, 1995; ROSENSTONE; HANSEN, 1993; MIlBRATH and GOEl, 1977) evidenced that these variables are important predictors of political participation.

As dependent variables, we used the online and offline participation modalities, adapted from the Youth & Participatory Politics Survey Project (COHEN et al, 2012) and the American National Elections Studies (ANES), following a procedure adopted by Towner (2013). Offline participation was investigated based on the following questions: 1) Did you personally talk to someone and try to show this person why he/she should vote for or against one of the parties or candidates? 2) Did you attend any political rally, dinner or event in support of a particular candidate? 3) Have you used a campaign bottom, put a sticker on the car, a sign on your window, wall or in front of your house? 4) Did you ever campaign for any party or candidate? 5) Did you personally donate money to any party or candidate?

Online political participation was investigated using the following questions: 1) Did you send an e-mail with a political content to another person? 2) Have you ever chatted online with someone and tried to show him/her why it should vote for or against any party or candidate? 3) Have you followed or become a fan of any political candidate on social media platforms? 4) Have you posted a comment or weblink on a blog, social media or website to express political opinions? 5) Did you take part in a discussion online or participated of a chat group on politics? 6) Did you donate money online to a candidate or political party?

Since these participation modalities originated in North American studies, it was necessary to test the reliability of its use in the Brazilian context by conducting factorial analyses in each of the two dimensions, online and offline⁸. It is a set of statistical techniques that allows measuring the consistency of a group of variables, investigating the interrelation between each (HAIR et al, 1993). It should be noted that nine among the 11 participation modalities (online/offline)⁹, which are transformed into participation measures empirically tested in this study, present a dichotomous variation (yes/no) depending on the respondents’ answer. Thus, the factors were extracted from a matrix of tetrachoric correlation, a method indicated for such cases (DIGBY, 1983).

In the two models (online/offline) (Table 1), the factorial load of the variables was adequate and above the critical limit (0.5) established by the literature (HAIR et al, 1993). This means that it is correct to group them together into one measure. It also indicates that electors who opted for one of the modalities in each of the models (online and offline) are inclined to practice the others modalities (RIBEIRO; BORBA, 2015; BRADY, 1999; VERBA; NIE, 1972). Thus, because the factorial analysis justified a reduction of the variables to indicators, two distinct indexes of offline and online participation were established, the first one (offline participation) having four dichotomous variables and ranging from 0 to 4; the second one (online participation) comprehending five variables that range from 0 to 5. With this, it is also possible to investigate the influence of one type of participation over the other to answer one of the hypotheses of this study.

Table 1

Offline Participation
	Factor	Singularity	KMO	Cronbach α
Try to influence the vote of someone else	0.72	0.48	0.71	0.51
Participate in political meetings	0.64	0.59
Use a candidate’s bottom, etc.	0.57	0.68
Campaing	0.96	0.08
Online Participation
Send e-mails with a political content	0.89	0.2	0.83	0.81
Try to influence someone else’s vote online	0.82	0.31
Follow/like a Fanpage of a politician	0.9	0.18
Post political comments, etc.	0.65	0.09
Participate in online chats on politics	0.93	0.12

• Source: Research elaboration.

Thus, the online and offline participation modalities, transformed into empirical measures of participation, were used to construct a scale from zero to three (0-3), representing, at each step of the scale, the sum of repertoires for each voter: 1) “no participation”, when the value was equal to zero (inactive voters); 2) “low participation”, when the voter was involved in only one participatory activity; and 3) “moderate/high participation”, when voters used two or more repertories. Thus, the voters of the sample were classified as follows: 1) Did not participate in any offline action (n = 185); 2) Participated in at least one offline action (n = 65); and 3) Participated in two or more offline actions (n = 30). 4) Did not participate in any online action (n = 237); 2) Participated in at least one online action (n = 17); 3) Participated in two or more online actions (n = 26) (Graphs 1 and 2).

Graph 1
Offline participation

Graph 2
Online participation

The adjustment of the Kaiser-Meyer-Olkin test (KMO) confirmed the suitability of the model to answer the hypotheses of this research, since it presented a value higher than 0.6 (HAIR et al, 1993). Additionally, the reliability of the nine variables used in the composition of the online/offline participation indexes, described in previous paragraphs (Cronbach’s Alpha), was tested. The online participation index (0.81) (Table 1) presented a value within the limits established by most studies (between 0.7 and 0.9) (STREINER, 2003).

In turn, the reliability of the offline participation index (0.51) was below the ideal value considered as minimum (0.7) by some authors (STREINER, 2003), while for others it has a moderate level (lANDIS; KOCH, 1977) or an acceptable minimum value (GlIEM; GlIEM, 2003). In this regard, it is worth reiterating that the cluster “Campaign Work”, which groups a repertoire of five electoral participation modalities, has been used in electoral studies by ANES since 1948 in the United States. Since then, it has served as a reference in the application of opinion polls on political behavior in several Western countries (BRADY, 1999).

The variability in participation rate indexes, in both the online and offline models, and the reduced size of the scale to identify the determinants of electoral participation led to the use of the multinomial model, as recommended by Ribeiro et al (2016). Because they are the majority, inactive voters will be considered a reference category to analyze the impacts of independent variables on participation, that is, the determinants that make the individual leave a situation of inactivity to use one or more repertoires of political action.

The model that analyzes online participation also included voters who did not have internet access (n = 97). The sampling was designed to represent the electorate of the city of Salvador in 2014, not allowing the constitution of a sub-sample that considered only the voters who access the internet. The solution used was to group voters who did not have access to digital technologies (n = 97) together with those who did not use any participation repertoire online (n = 237) in the 2014 elections. Although not the most plausible solution, this methodological option made it possible to maintain the representativeness of the sample for the entire electorate of the capital of Bahia. It should be noted, therefore, that among the 84.6% of voters who did not participate online, 34.6% did not participate, a priori, because they did not have access to the internet.

Results and discussion

The model presented in Table 2 shows the constraints of low and moderate/high online and offline participation, taking as reference the category of inactive people.

Table 2
Online and Offline Participation Coefficients

	Offline Participation		Online Participation
	Low	Moderate	Low	Moderate
Online/Offline Participation Index	1.885	7.81**	5.89**	6.54**
Education level	.970	.753	1.439	3.00*
Age	1.38*	1.263	.733	1.068
Income	.841	1.011	1.144	1.184
Gender	1.386	.734	.570	1.617
Using Twitter	7.06*	.992	.497	.230
Using WhatsApp	3.07*	6.73*	.533	1.264
Using Youtube	.849	.478	.397	2.661
Using Facebook	.683	0.09*	36.58**	22.41*
Using Instagram	.387	1.671	1.881	4.32*
Party Identification	1.813	10.97**	1.239	2.262
Civic Engagement	1.893	2.745	.924	2.681
Pseudo R2	0.36		0.53

• Notes:
• ^*
  p<0.05,
• ^**
  p<0.01
• Source: Research elaboration.

Online political participation did not influence the low offline participation, but had a positive effect on moderate participation. Each increase in the online participation scale increased by 7.8 times the chances of a voter emerging from inactivity to a moderate political participation outside the internet. Taking into account that most respondents were more active offline, this result allows stating that most mobilized voters outside the digital platforms were precisely those who used them to express themselves politically (STOllE; vISSERS, 2013). Thus, the Reinforcement Hypothesis observed in previous studies (DI GENNARO; DUTTON, 2006; NORRIS, 2001), and also raised in this study (H1), is confirmed.

This statement is endorsed when online participation coefficients are observed. The offline participation index had a positive effect on both low digital and moderate participation. Each increase in the scale of conventional participation increased the odds of a voter having a low participation online by 5.8 times and having a moderate participation by 6.5 times when compared to inactive voters. That is, voters who participated in offline campaign actions were more likely to engage in online participation repertoires. However, the online participation had a positive effect only for moderate offline participation, as we stated above.

Contrary to theoretical expectations, education did not affect significantly offline participation. It was expected that voters with higher education would be those who participated the most (VERBA et. al, 1995; ROSENSTONE; HANSEN, 1993). On the other hand, the greater involvement in online activities is strongly favored by higher education levels (SCHlOZMAN et al, 2010; 2012). Each increase in this measure – from primary to high school, and from high school to higher education – increased 3 times the odds of voters in this sample having an online participation from moderate to high. Thus, it can be stated that voters who most used online participation repertoires were those who had a higher education level, confirming, in part, the Hypothesis 1.

On the other hand, we expected that younger voters were more familiar with social networks than older voters (lOADER et al, 2014, BEST; KRUEGER, 2005), which could not be observed in this sample by the model described above. The Hypothesis 2, therefore, was not confirmed. Age influenced only a low participation offline, increasing it by 1.38 times. From a lower age group to a higher age group, the chances of a voter using an offline participation repertoire are greater. This finding confirmed previous studies regarding involvement with conventional campaign activities (VERBA et al, 1995; ROSENSTONE; HANSEN, 1993). The variables gender and income were not influential in this sample, either for participation online or offline.

Regarding the effects of using digital platforms (Hypothesis 3) in offline participation, only YouTube was not significant. Twitter had a positive impact on the low offline participation, increasing 7 times the chances of voters taking part of an action off the internet, which confirms studies on the use of this tool for mobilization in electoral campaigns in Brazil and in other countries (AGGIO, 2016; TOWNER, 2013; MARQUES et al, 2013). In turn, WhatsApp increased by three times the odds of a voter having low offline participation and by 6.7 the likelihood of having a moderate participation. It should be noted that WhatsApp has also been widely used in electoral campaigns to mobilize the staff of candidates and voters (GUTIERREZ-RUBI, 2015).

Facebook, in turn, had a negative effect on the offline participation of respondents of this sample, reducing by almost 2 times the chances of a moderate voter participation offline, which is contrary to previous studies (TOWNER, 2013; VITAK et al, 2011). In contrast, this social network is the main channel of online participation, increasing the low and moderate web participation of the voters of this sample by 36 times and 22 times, respectively. This impact may be explained by three reasons: 1) the technology available on Facebook, which enables grouping simultaneously all actors of an electoral campaign, i.e., politicians, voters and the media (WESTTlING, 2007); 2) basic platform functions in online campaigns, connecting voters, increasing political engagement and encouraging mobilization (TOWNER, 2013); and 3) Facebook’s functioning as a home base of social media, a phenomenon identified by the Pew Research Center in the US and confirmed by the author’s field research¹⁰. Finally, the use of Instagram, a platform synchronized with Facebook and Messenger, had a positive effect on a moderated participation online, increasing the chances of Salvador’s voters using two or more online repertoires by 4.3 times.

Despite the isolated effects of using Twitter and Instagram, WhatsApp and Facebook have similar effects, albeit of a different nature. WhatsApp favored offline participation, while Facebook influenced online participation. These results indicate that WhatsApp was used as a mobilization tool for campaign actions offline, as the federal deputy Nelson Pelegrino (PT-BA) stated in an interview with the author (08/13/2014), corroborating other studies (GUTIERREZ -RUBI, 2015). Facebook was the main channel of web participation (TOWNER, 2013; WESTlING, 2007). Through this social network, voters used online political action repertoires. The results, therefore, confirm the Hypothesis 3.

In relation to online participation, party identification was not significant among the voters of this sample. Thus, voters who did not show a preference for any political party participated in online repertoires just as those that had a party identification, which confirms recent studies (MARGETTS et al, 2015) on the mobilizing role of digital tools even among those who have no interest in politics.

Party identification has shown a positive effect only for moderate offline participation. The voters of this sample who performed more campaigning activities outside the internet were precisely those who identified themselves with some of the political parties involved in the elections (ZÚÑIGA et al, 2014, MIlBRATRH; GOEl, 1977). Finally, civic engagement was not a significant predictor of online participation, nor offline participation, contrary to the classical literature on conventional participation (PUTNAM, 2015), corroborating empirical research on web participation (BEST; KRUEGER, 2005; BENNETE, 1998).

Conclusions

The results of this study confirmed the exclusionary nature of political participation mediated by digital technologies (BARBER, 2006), confirming the Reinforcement Hypothesis (DI GENNARO; DUTTON, 2006; NORRIS, 2001), that is, the internet attracts the offline politically engaged groups. A high education level was crucial for online participation, while average and lower education level voters would hardly use internet tools to participate in elections, according to the data in this sample.

It also corroborates Barber’s (2006) thesis according to which a digital apartheid will not be solved solely by equalizing access to the internet. Education, according to him (BARBER, 2006), is a barrier that deepens the inequalities of the use of internet, rendering its democratic potential unfeasible. Along the same lines, Di Gennaro and Dutton (2006) believe that the internet will exacerbate participation inequalities, while Eisenberg (2003) concluded that the internet is as exclusionary as print media because it requires high cognitive capacities by users.

Regarding the impact of the use of social media on online and offline political participation, the sample results also confirmed previous studies (TOWNER, 2013, TOWNER; DUlIO, 2011; VITAK et al, 2011). It should be noted that all who participated online (n = 43) did so through such websites. These platforms are changing and expanding the forms of political participation (MARGETTS, 2015; ZÚÑIGA, 2014), although some forms of participation mediated by social media, as presented in this study, such as talking to people and trying to convince them to vote in a party or candidate, only mirror activities developed offline.

The sample size and its homogeneity regarding socio-demographic characteristics and the economic status of Salvador’s electorate (77.9% with an income between 1-3 minimum wages) make it difficult to identify the influence of these variables on online and offline participation policy. Thus, there is a need for further studies using greater samples in order to deepen the study of the impact of digital technologies on the behavior of the voter from Bahia.

• 1
  This study has been carried by the author since 2014 as part of her doctoral research.
• 2
  The research was applied by the institute of public opinion P&A Pesquisa e Análise, with 30 years of experience in public opinion survey, using a questionnaire prepared by the author.
• 3
  Brazil’s 2016 Brazilian Media Survey, conducted by Ibope, found that socioeconomic inequalities impede the access to the Internet for a significant part of the population http://www.secom.gov.br/atuacao/pesquisa/lista-de-pesquisas-quantitativas-e-qualitativas-de-contratos-atuais/pesquisa-brasileira-de-midia-pbm-2015.pdf). This was also observed in our field research, which revealed that voters who do not access the Internet are mostly women over 45 years of age, income of up to three minimum wages and educational level up to secondary school.
• 4
  Boyd and Elisson (2007) defined social network websites as “web-based services that allow users to (1) build public or semi-public profiles within a limited system; (2) articulate a list of other users with whom they share a connection, and observe and cross their connection lists with lists made by others within the system. The nature and nomenclature of such connections may vary from location to location”.
• 5
  According to the latest Urban Development Master Plan (Municipal law no. 7,400/2008), Salvador has 18 Administrative Regions. 17 are located on the mainland and the 18^th is an island encompassing the Islands of Maré, Madre de Deus and Frades within the Baía de Todos os Santos region.
• 7
  “A variable is a general class of objects, events, situations, characteristics and attributes that are of interest to the research […] The independent variable has an impact on the dependent variable. In other words, the values that the dependent variable takes on are influenced by the independent variable.” (BALNAVES; CAPUTI, 2001, p.46).
• 8
  The methodological procedures used in this study to verify the conditions for electoral participation were recommended by Dr. Ednaldo Ribeiro from the Federal University of Paraná (UFPR), who applied them in his article “Online and offline participation in Brazil: relations and constraints” (RIBEIRO et al, 2015). They were here performed by his student, lucas Toshiaki Archangelo Okado.
• 9
  The modality of participation “donation of funds for parties or candidates” was discarded from this study because it recorded only one case in each dimension (on/off), which made multivariate analyses impossible.
• 10
  http://www.pewInternet.org/2015/01/09/social-media-update-2014/.

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Publication Dates

• Publication in this collection
  Sep-Dec 2017

History

• Received
  09 June 2017
• Accepted
  18 Sept 2017