[11 March 2016]

The Effects of the on Online and Offline Political Participation among Citizens in Australia*

Liang Jiang

School of Arts and Social Science

University of Technology Sydney

Sydney, NSW 2007

[email protected]

* Prepared for presentation at the 66th Annual International Conference of British Political Science Association, Brighton, United Kingdom, 21 - 23 March 2016.

Abstract

Many questions about the effects of Internet use on citizens’ political participation have remained unanswered. Particularly little is known about how the Internet affects citizens’ online and offline political participation in Australia. This study expands the knowledge about the relation between internet use and political participation by examining the effect of Internet use on citizens’ online and offline political participation and the moderating roles of psychological resources in the political process. The results obtained from two cross-sectional data from the Australian Election Study reveal a positive relation between the Internet and online and offline political participation. In addition, the moderating roles of psychological resources differ from one resource to another. More importantly, this study finds that the Internet mobilises not only those who are already pre-disposed or interested in politics but also those who are politically inactive to become more politically involved.

Keywords: internet, political participation, political interest, political efficacy.

The Effects of the Internet on Online and Offline Political Participation among Citizens in Australia

Introduction

In the run-up to the 2013 Australia federal election, the media buzz about online mobilization was palpable. Expectations were set high. Following in the footsteps of Howard Dean in the 2004 American presidential election and Barack Obama in the 2008 American presidential election, internet-based techniques are made globally famous for election campaign and they are now being used the world over.

Australia is no exception too. Internet-based fundraising and grassroots organising have been growing in importance in the Australian federal elections. Labor, Liberals and Greens used various online channels to call for and collect small donations from supporters in the 2013 election. The Labor Party raised 20.8 million during the campaign, much of it from small online donations made by individuals (Show

2013).The other parties also received different amount of money in small-unit donations during the 2013 election campaign. Parties and candidates utilised to push into the consciousness of viewers lost to them on TV, printed newspaper and radio (Chen 2014). In addition, social media in the campaign was important. Kevin Rudd and Tony Abbott employed Twitter and in different ways to deliver personal messages and specific campaign information and build good personal images for campaigning strategies (Chen 2014).

Without question, the internet is an integral part of citizens’ lives in Australia. An Australian

Communications and Media Authority (2014) report on the use of digital media by adult Australian released in December 2014 reported that 92 per cent of adult Australians have internet access, with 88 per cent of these Australians having engaged in online communication activities. This also included internet access for election information. During the 2013 federal election, based on the Australian Election Study

(AES), 15 per cent of respondents followed the election through the Internet and 30 per cent had accessed websites of mainstream news media. In addition, 14 per cent had access to federal parliament site and another 12 per cent obtaining election information from party or candidate sites (McAllister and Cameron 2014). The rapid rise of the internet and its widespread use among citizens in Australia may have the potential to affect individual political behaviour as traditional media did.

Although the Internet in Australia has become the focus of growing scholarly literature in recent years, there is surprisingly little systematic research on the role that the internet plays in shaping individual political behaviour. Specifically, while some scholars take into account the role of the Internet in political electioneering (e.g., Chen 2014; Chen and Smith 2010; Gibson and McAllister 2006, 2011, 2015; Gibson et al 2008; Macnamara 2008; Macnmara and Kenning 2011, 2014; Macnamara et al 2012) and the impact of the internet on psychological resources relevant to politics (Gibson and McAllister 2015; McAllister

2015), no studies to our knowledge have analysed how internet access in shapes citizens’ political participation in Australia. As a consequence, we are not certain whether internet use mobilises individuals in Australia for political participation, and how the impacts of internet use differ in online and offline political participation. Does the Internet serve to activate only those who are already predisposed or interested in politics? Or does the Internet also mobilise politically inactive populations in Australia? In addition, this study also explore how psychological resources, such as political interest and political efficacy, play a moderating role between internet use and online and offline political participation.

Below, I address these questions by examining the role of internet in motivating political participation among individuals in Australia. I argue that the Internet has the potential to mobilize citizens politically but the strength of this relationship depends on psychological resources. I tested my arguments using the data from the 2010 and 2013 Australian Election Study. My analyses revealed that internet use leads to several positive impacts on online and offline political participation. The moderating role of political interest is not noticeable but political efficacy and election interest both play a noticeably moderating roles between internet use and political participation. Moreover, I found that in Australia, the internet serves not only as reinforcements for politically active populations but also mobilises politically inactive populations. This present study contributes to scholarly literature in several ways. Firstly, on a theoretical level, I highlight the complex yet important role that the internet plays in shaping citizens’ political participation in Australia. In doing so, I seek to contribute to a relatively slim body of research on how religion matters in citizens’ political engagement in Australia. Secondly, I extend the scholarly focus beyond the moderating role of political interest and by doing so, I also develop a more comprehensive understanding of the moderating roles of other psychological resources. Additionally, this study contributes to other studies on political institution by uncovering the potential effect of compulsory voting on the internet use for political purposes. Finally, the analysis goes beyond existing studies, which tend to argue that the

Internet serves as either reinforcement or mobilisation, and shows that the internet is equipped with those two effects.

The paper proceeds as follows: in the next sections, I will formulate and develop my arguments; I then describe the data and measurements utilized in this paper, followed by presenting analyses and results, and finally concluding by discussing the implications of my findings and offering suggestions for further research.

Internet Use and Political Participation

While it is generally believed in the communication of politics that internet matters in individuals’ political life, the issue of how the Internet affects individuals’ political life remains unsolved. This unsolved circumstance is due to three competing arguments. On the one hand, it is optimistically argued that the Internet has the potential to foster citizens’ involvement in politics and contribute to the quality of democracy (Bimer and Copeland 2011; Boulianne 2009; Kenski and Stround 2006; Wang 2007; Xenos and Moy 2007). The optimists believe that the Internet provides a channel through which political parties and elected representatives inform citizens about their points of view and communicate interactively with voters. It may also offer easy access to citizens for political information so as to increase political interest and participation. Shah et al (2005) found that a variety of sources available online, along with the lower- costs of access to information about politics, facilitate individuals to acquire a knowledge of politics and thus enhance their engagement in politics. On the other hand, skeptics assert that the Internet does not cause individuals to participate in political acts. As the Internet is being used primarily for entertainment and has been thought to be a depoliticising medium which distracts individuals from involvement in politics, the Internet is more of distraction than an impetus to participation (Davis 1999; Putman 2000;

Zhang and Chia 2006). Zhang and Chia (2006) found that frequency of Internet use was not positively related with political and civic participation.

The last set of scholars falls somewhere in between. This group does not espouse such pessimistic claims about the impact of Internet usage as the skeptics d0, arguing that the Internet does have some effect on citizens’ engagement in politics. Scholars of this group also argue that optimists may have overrated the potential of the Internet to affect citizens’ involvement in politics, since they found that the Internet has mixed impact on their involvement in politics. The empirical evidence for such claims indicates that the effects of the Internet are not directed to all citizens but to a specific group of people and specific forms of political participation (Bimber 2003; Dimitrova et al 2011; Oser et al 2013), and that specific forms of

Internet usage differ in their effects on citizens (Kruikemeier et al 2014). Boulianne (2011) found that the

Internet will not encourage citizens who are apathetic about politics to become more politically involved; rather, it only serves to activate citizens who are already interested in politics. Campante et al (2013) investigated the effects of Internet use on differential forms of political engagement. They found that

Internet use may mobilise people for participation in non-electoral activities while it does not have such influence on participation in electoral activities. Kruikemeier et al (2014) distinguished active and passive forms of political Internet use. They found that the use of only a few specific forms of the Internet has a positive effect on political interest and voter turnouts. Overall, the question of how the Internet affects citizens’ political involvement remains unaddressed. The empirical evidence is mixed.

In Australia, studies of internet use mostly centre on elections, and empirical evidence tends to lean towards the optimistic views. The question of how parties take advantage of the internet to obtain votes have received considerable attention (Chen 2014; Chen and Smith 2010; Macnamara and Kenning 2011,

2014). Gibson and McAllister (2006) employed a national data to investigate the factors determining candidates’ use of web campaigning and its effect on vote. They found that candidates who were running web campaigns tended to obtain more support from citizens, particularly support from their party members, and thus running a web campaign is integral to election success. Internet use also may affect voting choices of citizens, since those who utilise the internet were more likely to vote for Labor rather than for the Coalition in the 2004 Australian federal election (Gibson and McAllister 2008). Moreover, as

Australia adopts the system of compulsory voting, any support which candidates gain within the system derives only from conversion of existing voter preferences rather than mobilization of latent preferences

(Gibson and McAllister 2011). Further investigation shows that political systems, parties and their candidates exert influences on distribution, drivers and contents of web campaigning, albeit levels of the influence are differing (Gibson et al 2008).

However, until now very little research has examined the effects of Internet on political participation in

Australia. Collin (2008) employed the data of face-to-face, in-depth interviews to analyse the effects of the Internet on political identities of young people. He found that the Internet is used as a tool by which young people may identify issues, learn more about politics and more easily integrate participation into their everyday lives. Traditional political institutions can also shape their views on political participation through the Internet. He therefore concluded that the Internet contributes to the development of young people’s political identities. McAllister (2015) examined the role of the Internet in shaping political knowledge among young people and in turn the impact of political knowledge on political participation.

His analysis showed that internet use during an election campaign was significantly associated with political knowledge among young people, and that such political knowledge was more likely to increase voting in the 2013 Australian federal election. Although both papers contributed to the existing literature, there are two limitations. Obviously, their analyses did not include online political participation, or e- participation. Some of the new forms of e-participation have no clear parallels in the non-, and thus it is risky to infer the impact on e-participation from the case of offline political participation

(Gibson and Cantijoch 2013, also see: Oser et al 2013). Moreover, Gibson and Cantijoch (2013) argued that the lack of measures of e-participation may lead to the lack of clear and cumulative findings about the political impact of Internet use. In addition, both papers only included young people as their research population. While the proportion of young people who has access to the internet is higher than that of older groups, the results for young people do not represent the case for other groups.

Research on the relationship between internet use and political participation has been grounded in several potential causal mechanisms. One causal mechanism has focused on the relation between the Internet and resources for participation. A determinant of whether or not to participate is the availability of resources to face the costs that participation brings: the less resource, the higher the cost, the less likely citizens will participate (Verba et al 1995). The impact of costs on participation is therefore dependent on the levels of resources available. The existence of the Internet has given rise to resources which traditional media previously did not provide. For example, through Internet, anybody can make contact with other individuals and organizations and launch protest actions online without the physical and temporal limits imposed by the offline world. Carrying out these tasks online may contribute to savings of time.

Meanwhile, through the Internet anyone can access and expand on the available information about topics of specific interest. It not only allows individuals to obtain various resources in the form of political information, but also reduces the cost of acquiring political information given that online information access is unlimited, fast and cheap. The low cost of acquiring political information online may encourage individuals to access more information via the Internet, which in turn stimulates a great interest in politics and thus favours participation (Lupia and Philpot 2005; McDonald 2008). This uncovers the second causal mechanism: depending on how easily access to political information is, internet use leads to an increase in the level of political participation.1

1 Scholars also cast doubt on this causal mechanism and argued that even though the information is available, it requires the of users to access and the capacity of users to process and interpret (Bimber 2003; Polat The next causal mechanism is that internet use has the potential to shape attitudes which have an impact on political participation. The Internet provides an interactive and anonymous forum by which users can express and exchange opinions freely. With more frequent access to the Internet, the more likely attitudinal changes occur. Scholars argued that attitudinal change is akin to reinforcement, since the internet will not encourage citizens who are less politically interested to become more politically involved; rather it encourages citizens who are already interested to participate more actively in politics (Boulianne

2009, 2011; Hirzalla et al 2010). A different idea shows that attitudinal change is driven from mobilization through the Internet. Wong (2006) found that political use of the Internet boosts political interest and feelings of trust and efficacy, and in turn enhances the likelihood of citizens’ participation in politics.

Although scholars have found the potential causal mechanisms for the impact of Internet use on political participation, studies on how the Internet affects political participation have produced mixed and less conclusive findings, potentially due to variability in relationships over time. It is argued that the links between Internet use and political participation that are found in one election season is not necessarily repeated in others (Boulianne 2009; Mossberger et al 2008; Bimber et al 2015). Thus, any findings in relation to the Internet and political participation, which were concluded with the analysis of single cross- section, may be questionable (Bimber and Copeland 2013). At the same time, the mixed empirical evidence is also potentially due to the scarce systematic evidence about offline and online political participation. In this paper I will examine variations in the impact of internet on political participation across times and forms based on the AES for the 2010 and 2013 elections, given that the 2013 survey replicates questions as to internet and online activities from the 2010 survey and it provides direct comparison on the same questions. Specifically, to what extent is the relationship between internet use and political participation consistent over time? And whether do psychological resources play the

2005; Prior 2005). Therefore the availability of information does not necessarily lead to an increase in the levels of political participation. moderating role in the relationship? Empirical evidence shows that the impact of the internet on political participation is conditioned by psychological resources (Xenos and Moy 2007; Bimber et al 2015).

Data and Method

To examine these expectations, I analysed cross-sectional survey data from the 2010 and 2013 AES, which were three nationally representative mail-out, mail-back surveys of persons registered to vote in the

2010 and 2013 elections. The surveys were weighted to reflect the characteristics of the national electorate. These data contain consistent measures of Internet use for political information and measures of political participation for the two elections.

Dependent variables

Two sets of dependents variables were used, online and offline political participation. Online political participation was measured by four political actions. The four political actions were: 1) discussion with others online, 2) signed up to receive information from a party or candidate and/or registered as their follower/friend/supporter on Twitter or Facebook (labelled as “receive online information”), 3) used online tools to promote parties and candidates (labelled as “promote parties online”), 4) shared, posted, or reposted any non-official content on a , Twitter feed or profile (labelled as “post non- official content”), and offline political participation was measured by five political actions. The five political actions were: discussed politics with others, talk to people about voting, work for party or candidate, go to meetings or rallies, and contribute money. Descriptive statistics for these variables for each year are displayed in the Appendix Table.

Independent and Control Variables

The primary independent variables are Internet use, psychological resource, and the interaction between these two variables. Two variables are used to measure internet use. The first variable is frequency of general internet use, which is measured by responses to the question: ‘In general, how often do you use the internet?’ and is coded from 1 (never uses the internet) to 7 (uses the internet several times per day).

Respondents indicated their frequency of election internet use as the second variable: ‘Did you make use of the internet at all to get news or information about the 2013 federal election?’ and the frequency is coded from 1 (never used) to 5 (used many times).

Three variables are used to measure psychological resources: political interest, political efficacy and election interest. Political interest is based on the question: ‘Generally speaking, how much interest do you usually have in what’s going on in politics?’ and is coded from 1 (none) to 4 (a good deal). Political efficacy is based on the question: ‘some people say that no matter who people vote for, it won’t make any difference to what happens. Others say that who people vote for can make a big difference to what happens. Where would you place yourself?’ and is coded from 1 (won’t make any difference) to 5 (make a big difference). Election interest is based on the question: ‘how much interest would you say you took in the election campaign overall?’ and is also coded from 1 (none at all) to 4 (a good deal). Six variables are used as control variables. They are gender, tertiary education, Australian born, age, household income and urban residence. Among them, gender, tertiary education, and Australian born were dummy variables.

Age is measured in years and household income is measures in quintiles. Urban residence is five point scale coded from 1 (lives in a rural area or village) to 5 (lives in a major city over 100,000 people).

Descriptive statistics for these variables for each year are displayed in the Appendix Table.

Analysis

To estimate the size and effect of the relationship between Internet use and online and offline political participation between 2010 and 2013, two regression models were estimated for each act and for each year. In the first model, main effects were presented by including all independent variables except for three sets of interaction including political interest and internet use for election news, political efficacy and internet use of election news, and election interest and internet use for election news. The second set of models includes the three interactions, which demonstrate any moderation effect. By including models for each year rather than merging two years into a single data set, how interactions vary across acts and years are able to be shown and interpreted. Moreover, how the three sets of interactions differ in the relationship between internet use and online and offline political participation can too be elucidated. This procedure resulted in a total of 36 regression models.

For the online political participation models, the analysis is a bit more complicated becasue two different types of variables exist. As a results, I used ordinary least squares (OLS) regression for discussion online.

The rationale is that the dependent variable are quasi-continuous and results produced by OLS regression in empirical studies of interest and political participation have proved to be robust (McAllister 2015;

Bimber et al 2015). For the other online political participation models, logistic regression was used because the dependent variables are dichotomous (Long & Freese 2006). For offline political participation models, I simply used OLS regression because all of the dependent variables are quasi-continuous.

[Tables 1 and 2 near here]

Results

Online political participation

I will begin with discussion online, where I find a main effect for election internet use in 2010 and 2013 in the OLS regression, as shown in Table 1. For the variables of psychological resources including political interest, political efficacy and election interest, political interest has a positive effect while political efficacy has a negative effect on discussion online. However, such positive effect of political interest on discussion online was only found in the 2010 model, whereas the positive impact of election interest appears only in the 2013 model. This result raises a question, that is, whether and how psychological resources affect the relationship between internet use and discussion online. To answer this question, I now turn to Table 2 and look at the interaction effects. In the interaction model for 2010, the interaction term of political interest is significant and negative while the election internet use term is significant and positive. This means that internet use for election news was positively associated with discussion online when general political interest is low, and this relationship diminished as general political interest increased. For 2013, there was no interaction. The interaction term of political efficacy had no effect in 2010 but had a positive effect in 2013. As the interaction term of political efficacy and the election internet use were significant and positive, it means that internet use for election news was positively associated with discussion online when interest was high, and this relationship increased as efficacy increased. While the interpretation of OLS results suggests that in 2010 internet use had a stimulating effect on discussion online for those low in general political interest and no relationship in

2013, the interpretation also suggests that political efficacy has a stimulating effect on internet use and discussion online in 2013. The stronger the political efficacy individuals have, the more likely they would use internet for election news, and in turn they will be more likely to discuss it with others online. Such a relationship does not appear in 2010. Meanwhile, these results indicate variability over time in the role of general political interest and political efficacy. The interaction term of election interest and the election internet use is significant and positive in 2010 and 2013, which means that internet use for election news are positively related to discussion online when election interest is high, and the relationships also increased as election interest increased. The interpretation of the OLS results suggests that election interest matters in discussion online across the elections.

For the control variables, age was negatively associated with discussion online in the 2010 and 2013 models, indicating that young people are more likely to discuss with others online than more elderly citizens. This is in line with previous findings from studies on internet and political participation

(McAllister 2015). Household income was negatively associated with discussion online in both years’ models. Individuals who have lower income were more likely to discuss with others online than those individuals with higher income. The effect of location of residence appears only in the 2010 model. In

2010, citizens who lived in rural residence were more likely to discuss with others online.

The results for the other online acts are similar to those of discussion online. The logistic regression models, which are shown in Table 1, show that the internet use for election news significantly exert main effects on signing up to receive information, using online tool to promote parties, and shared or posted non-official content for parties and candidates. However, the results of interaction for the other online acts indicate a different picture. The logistic regression models, which are shown in Table 2, show that the interactions between general political interest and internet use for election news and between political efficacy and internet use for election news are not significant, meaning that general political interest and political efficacy are not relevant to the relationship between internet use for election news and the other online acts. It is a little surprising that while the interaction of election interest is not significant for signing up to receive information and using online to promote parties in 2010 and 2013, this interaction is significant and negative for shared or posted non-official content for parties in 2013. It means that internet use for election news was positively associated with shared or posted non-official content for parties when election interest was low, and this relationship diminished as election interest increased. This finding also indicates variability over time in the role of election interest, since there is no interaction effect in 2010. In addition, the interpretation of the logistic regression results suggests that in 2013 internet use had a stimulating effect on shared or posted non-official content for parties for those low in election interest and no relationship in the other year.

For other variables which are shown in Tables 1 and 2, young people were more likely to participate in online political acts than elder people, but this relationship appears only in 2013. Household income had a negative effect on signing up to receive information in 2010. It also has a negative effect on using online tool to promote parties and shared or posted non-official content for parties in 2013. People who have low income were more likely to participate in online political activities than those in the high income group.

Likewise, Australian born people were more likely to sign up to receive information than overseas-born citizens, but only in 2010. In addition, the effect of following election in newspapers is significant and negative in 2013. Those people who were less active in following election in newspapers were more likely to use online tool to promote parties and to share or post non-official content for parties. The effect of following election on TV was like those of following election in newspaper, but unlike following election on elections, it only appeared in 2013.

[Tables 3 and 4 near here]

Offline political participation

I ran OLS models for 5 offline political acts, and as presented in Table 3, the results indicate that main effects exist for the use of the internet for election news in the two elections, with substantive importance declining from 2010 to 2013 for discussion with others and talking to people about vote. The importance of going to meetings or rallies and contributing money also rose from 2010 to 2013. As for the interaction terms in the models in Table 4, a small improvement in fit is seen. In both years, the interaction between political interest and internet use for election news is not significant in almost all of the models, indicating that there was no relationship between internet use and offline political participation, regardless of whether citizens are interested in politics or not. However, the only exception occurs in going to meetings or rallies in the 2010 election. The result of the OLS model indicates that in 2010, general political interest was significant and negative while the election internet use term was significant and positive. This means that election internet use was positively associated with going to meetings or rallies when general political interest was low, and this relationship diminished as general political interest increased. For 2013, there was no interaction. The interpretation of the OLS results suggests that internet use for election news had a stimulating effect on going to meeting or rallies for those low in general political interest, but this only applies to the 2010 election.

With regards to the interaction term for political efficacy in Table 4, the interaction term in discussion with others and talking to people about vote is significant and positive and the election internet use term was also significant and positive in 2010 and 2013, which means that internet use for election news was positively associated with discussion with others and talking to people about vote when political efficacy was high across elections. The relationship of political efficacy to discussion with others and talking to people about vote increases with internet use. It is also the case for working for party or candidates, going to meetings or rallies and contributing money only in 2013. As for 2010, the interaction between political efficacy and election internet use is not significant in the models of those three offline activities. This indicates that whether individuals have low or high political efficacy, there was no relationship between internet use for election information and working for party or candidates, going to meetings or rallies as well as contributing money. As such, this suggests that there is variability over time in the role of political efficacy.

The results for the interaction term for election interest however show a more complex picture, as seen in

Table 4. In 2010, the interaction was significant and negative, indicating that election internet use was more strongly associated with discussing politics for those who were less interested in election. By contrast, there was no relationship at all between election interest and discussion with others in 2013. The interaction appeared in other offline acts. In 2013, the interaction was significant and positive for talking to people about vote and going to meetings or rallies, suggesting that election internet use was more strongly associated with talking to people about vote and going to meetings or rallies as election interest increases. However, there was no interaction in 2010. The results of the OLS models also showed that no interaction was found on working for parties or candidates and contributing money across elections.

Hence variability over time in the role of political efficacy is visible too.

The results of the OLS models in Table 4 show that the impacts of media sources differ in offline political acts and change over time. People who follow election in newspaper in 2013 were more likely to work for party or candidates, go to meeting or rallies and contribute money than those who did not. Followers of election on TV were more likely to discuss politics with others than citizens who did not follow election on TV in both elections. Likewise, following election on radio seems to be influential in facilitating discussion with others and working for party or candidate across elections. Looking at the two years separately, it is revealed that following election on radio had a positive effect on talking to people about vote in 2010 while in 2013, the positive effect was on going to meetings or rallies. In addition, the impact of political mobilisation is noticeable in that party contact is positively associated with discussion with others in 2013.

For the control variables, the results of the OLS models in Table 4 show that age, gender, household income, being Australian born and urban residence were also important factors, although the importance varies from year to year and from act to act. Age was significant and negative, demonstrating that young people were more likely than elder people to talk to people about vote across elections, discuss politics with others only in 2013, work for party or candidate and go to meeting or rallies only in 2010, whereas elder people are more likely to contribute money than the young in 2013. Those people who have low income were more likely to talk to people about vote in 2013, contribute money in 2010, and work for party or candidate and go to meetings or rallies in both elections. The importance of gender was reflected by the finding that women were more likely to discuss politics with others in both elections, whereas men were more likely to work for party or candidates and contribute in 2010. However, the impacts of place of birth and location of residence were quite limited, although both controls still matter. The results in Table

4 indicate that overseas-born citizens were more likely to talk to people about vote during the 2013 election, and in the 2010 election, citizens who live in rural areas were more like to work for party or candidate, go to meeting or rallies and contribute money.

Discussion

This present study shows consistent effects of internet use on online and offline political participation.

That is, internet access for election news did have positive effects on online and offline political participation across 2010 and 2013 Australian federal elections. However, the moderating roles of psychological resources differ in political acts and elections. For online political participation, after controlling for social-demographical factors, party mobilization, media source and psychological resources, internet use is positively associated with online political acts, whether the relationship is moderated by interaction terms. But this does not mean that psychological resources do not exert any effects in the relationship between internet use and online political participation. In fact, psychological resources play different moderating roles in the relationship, depending on what online political acts citizens take part in. The moderating roles of psychological resources appeared in discussion online, although there were no moderating effects for the other online political acts. For offline political participation, internet access for election news was also strongly associated with offline political participation, after controlling for social-demographics, party mobilization, media source and psychological resources.

An interesting finding is the moderating roles of psychological resources between internet use and political participation. The results showed that political interest did not play a decisive role in the political process and the role of political interest in moderating the political process is modest. Across online and offline political participation, the moderating role of political interest appeared only in discussion online and going to meeting or rallies. However, political efficacy and election interest had stronger influences between internet use and political participation. Political efficacy plays moderating roles between internet use and discussion online and between internet use and all of the offline political acts. Election interest is related to the relationships between internet use and discussion online, internet use and discussion with other offline, internet use and talking to people about vote, as well as interent use and going to meetings or rallies. Prior studies mostly focused on the aspect of political efficacy as a mediator that connects internet use and political participation (Jung et al 2011; Tian 2011) but few studies have examined the possibility that political efficacy can moderate the impact of internet use on political participation.

Existing literature shows that political efficacy did not influence the relationship between internet use and political participation (Park 2015). However, the results for political efficacy in the present study are not in line with the previous findings, and the evidence strongly suggests that the moderating role of political efficacy exists.

Political efficacy has been seen as a feeling that an individual can influence the political process, and those who feel political efficacious are more likely to vote and participate in other political activities. Unlike voluntary-voting countries in which political efficacy may mobilise individuals to turn out, citizens in Australia are forced to go to ballots due to the system of compulsory voting. Therefore, political efficacy is not likely to mobilise citizens to turn out but is likely to mobilise citizens to decide which party citizens vote. The results in present study showed that citizens who use internet for election news were more likely to participate in offline political activities, and the relationship increased as political efficacy increased. In the context of the present study, offline political activities refer to campaign activities. Active participation in campaign activities that a party or candidate hosted to some extent means that participants are inclined to vote for the party or candidate. Furthermore, the moderating role of political efficacy is salient when the victory of election for a party or candidate is at stake. Pre- election polls showed that Kevin Rudd and Tony Abbott were not able to secure the popularity vote of the public and had to take turns to lead during the 2013 election campaign, whereas Gillard had a commanding lead on Tony Abbott in the 2010 polls.2 The fierce competition in the 2013 election may more effectively activate citizens’ political efficacy. Political efficacy therefore had stronger moderating influence between internet and online and offline political participation in the 2013 election, compared with the 2010 election. This was an unexpected finding.

Meanwhile, the results showed that election interest played several different moderating roles between internet use and online and offline political participation. Political interest can generally be thought of as the extent to which politics evokes a citizen’s curiosity to politics (Deth 2000), or as the motivation to engage in politics (Shani 2007). According to those definitions of political interest, election interest can be thought of as a motivation, which is aroused by elections, to engage in election activities. In short, political interest can be defined as a citizen’s curiosity to politics which is evoked by elections. In

Australia citizens have election interests potentially due to the system of compulsory voting. Citizens are forced to vote a party and thus citizens have to pay attention to election campaigns and consider voting choices through searching information relevant to elections. The evidence in this present study shows that

2 Data source: http://www.theaustralian.com.au/national-affairs/newspoll election interest influences internet use and political participation. The influence of election interest on internet use and discussion online, internet use and talking to people about vote and the relationship between internet use and going to meetings or rallies is in particular noticeable.

More importantly, the analysis of this paper is likely to ease the issue of whether the Internet could only mobilise those citizens who are already predisposed or interested in politics (Boulianne 2009; Hirzalla et al 2011; Gustafsson 2012) or if the Internet will also encourage politically inactive citizens to become more political involved (Krueger 2002; Ward et al 2003). The evidence to support the two arguments is found in this paper. On the one hand, according to the analysis of this paper, internet use mobilses citizens who are uninterested in general politics or elections to be involved in discussion online, share or post non- official content for party online, discuss politics with others offline, and go to meetings or rallies. On the other hand, the Internet also serves to activate those citizens who are already interested in election or politically efficacious to engage in discussion online, take to people about vote, work for party or candidate and contribute money. Therefore, this study is the initiative to demonstrate that internet not only mobilises those who are already interested in politics but can also mobilise those who are politically inactive to be active participants of politics.

Regarding the results of this paper, it should be noted that the variable of political efficacy used here is internal political efficacy instead of external political efficacy. This is because internal political efficacy, which is the feeling of who people vote for can make a big difference to which candidates get elected.

Therefore, I assert that it is more relevant to studying the relationship between internet use for election news and election compared to external political efficacy. The question of whether external political efficacy has the same effect as internal political efficacy does requires further examination. In addition, this paper employed data from the 2010 and 2013 Australian Election Study for the sake of comparability.

Both datasets included duplicate items as to internet use and offline and online political participation, which helps in comparison between the two election years. However, relationships that appear only in just two elections might not generalizable to other years. It is important to keep in mind that the technology itself is changing rapidly and that the development of new tools and applications may produce different kinds of communication and information exchange. The limitation of generalisability is also attributed to the different strategies of political elites in different elections. More comparable datasets employed might provide more generalised findings.

These limitations notwithstanding, this study has provided new input into the studies on the impact of internet use in the broader debate regarding the effects of internet use. I found not only that internet use is positively associated with online and offline political participation, but also showed that internet use has two functions, which is mobilisation and reinforcement. In addition, this study shows the potential effects of compulsory voting on internet use for election information.

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Pseudo R2 .287 .286 .273 .303 .311 .312 Adjusted R2 .210 .218 (N) 2214 3955 2214 3955 2214 3955 2214 3955 Note. OLS=Ordinary least squares. Cell entries are coefficients with standard errors in parentheses. Source: Australian Election Study, 2010 and 2013 *p≤.05; **p≤.01; ***p≤.001

Table 2. Mixed Regression Models Predicting Online Political Participation (Interaction Effects) OLS regression Logistic regression Sign up to receive Use online tool to Shared/posted non- Discussion online information promote parties official content 2010 2013 2010 2013 2010 2013 2010 2013 Internet use

Frequency of general -.007 .006 -.271 .317 -.167 .300 .150 .450** internet use (.007) (.008) (.164) (.193) (.212) (.240) (.181) (.154) Frequency of election .176*** .188*** 1.387*** 1.019*** 1.293*** 1.073*** 1.096*** 1.104*** internet use (.016) (.013) (.286) (.141) (.313) (.150) (.194) (.086) Media sources

Frequency of following election in .012 -.016 .129 -.024 .082 -.276* .082 -.300*** newspapers (.018) (.015) (.250) (.103) (.292) (.117) (.190) (.080) Frequency of following election on -.001 .001 .194 .017 .104 -.109 -.112 -.232** TV (.019) (.017) (.283) (.117) (.330) (.129) (.195) (.088) Frequency of following election on .009 .015 -.374 .026 -.227 .091 -.026 -.012 radio (.014) (.013) (.204) (.094) (.227) (.109) (.149) (.072) Party mobilisation .021 .018 .476 .167 - .532 .262 .198 .270 Party contact (.026) (.025) (.415) (.215) (.452) (.251) (.291) (.162) Psychological resources - .036 .056* 2.177 .092 1.622 .267 - .341 .097 Political interest (.054) (.023) (1.473) (.390) (1.765) (.440) (1.142) (.241) -.010 .026* .138 .240 .033 .109 .201 .034 Political efficacy (.012) (.011) (.353) (.223) (.452) (.250) (.318) (.127) .043 .093*** -.664 .841* 1.060 .756 .837 1.024*** Election interest (.025) (.023) (.501) (.402) (.583) (.444) (.618) (.246) Controls - -.005*** .006*** -.018 -.020** -.018 -.044*** -.006 -.027*** Age (.001) (.001) (.166) (.006) (.014) (.007) (.009) (.005) .023 .033 .508 .318 .393 .573* .419 .458** Gender (.026) (.024) (.425) (.193) (.475) (.226) (.301) (.148) -.024 .024 .001 .235 .092 -.581* .571 -.273 Tertiary education (.030) (.029) (.426) (.218) (.480) (.292) (.308) (.177) - -.008* .009*** -.080* -.019 -.016 -.035* -.010 -.032** Household income (.002) (.002) (.034) (.015) (.037) (.016) (.023) (.011) -.037 -.013 1.344* .466 .353 .139 .181 -.009 Australian born (.030) (.027) (.655) (.241) (.592) (.269) (.354) (.168) -.014 -.003 -.018 -.129 .230 -.090 .145 -.021 Urban resident (.009) (.008) (.166) (.068) (.235) (.081) (.138) (.055) Interaction

Election internet use* -.046* .029 .215 -.147 .636 -.102 -.047 -.034 political interest (.021) (.018) (.368) (.198) (.442) (.220) (.270 (.130)

Election internet use* -.008 .033*** -.037 .066 .040 .083 -.020 .064 political efficacy (.011) (.009) (.171) (.113) (.211) (.126) (.152) (.069)

Election internet use* .056** .057*** -.099 -.007 .332 -.109 -.084 -.303* election interest (.020) (.017) (.238) (.210) (.418) (.227) (.291) (.131) - - - 1.238*** .633*** -12.62* 12.06*** -17.28** 10.07*** 11.18*** -9.98*** Constant (.179) (.088) (5.046) (1.962) (6.332) (2.201) (3.355) (1.326) Pseudo R2 .290 .288 .281 .304 .311 .317

Adjusted R2 .222 .233 (N) 2214 3955 2214 3955 2214 3955 2214 3955 Note. OLS=Ordinary least squares. Cell entries are coefficients with standard errors in parentheses. Source: Australian Election Study, 2010 and 2013 *p≤.05; **p≤.01; ***p≤.001

Table 3. OLS Regression Models Predicting Offline Political Participation in 2010 and 2013 (Main Effects) Discussion with Talk to people Work for party or Go to meetings or Contribute money others about vote candidate rallies 2010 2013 2010 2013 2010 2013 2010 2013 2010 2013 Internet use Frequency of .017 .019* - .010 - .022** .005 - .004 .007 - .005 - .003 - .001 general internet use (.009) (.008) (.010) (.008) (.532) (.008) (.005) (.005) (.005) (.005)

Frequency of .078*** .065*** .105*** .064*** .076*** .075*** .034** .046*** .023** .038*** election internet use (.018) (.013) (.020) (.014) (.017) (.013) (.012) (.008) (.009) (.008) Media sources

Frequency of following election .025 .024 .003 .024 .008 .039** .021 .025* .011 .033*** in newspapers (.022) (.015) (.024) (.017) (.021) (.015) (.013) (.010) (.011) (.009) Frequency of following election .077*** .072*** .011 -.022 .029 -.004 .011 -.009** .001 -.003 on TV (.024) (.017) (.026) (.019) (.023) (.017) (.014) (.011) (.012) (.011) Frequency of following election .048** .061*** .063*** .025 .062*** .044*** .018 .033*** .003 .015 on radio (.018) (.013) (.019) (.015) (.017) (.013) (.010) (.008) (.008) (.008)

Party mobilisation .061 .149*** - .009 .006 .035 - .020 .032 .003 - .003 .001 Party contact (.032) (.025) (.034) (.028) (.030) (.025) (.019) (.016) (.016) (.015) Psychological resources .218*** .230*** .088 .116*** .014 .066** .010 .041** .019 .032* Political interest (.031) (.023) (.072) (.026) (.063) (.024) (.039) (.015) (.016) (.014) .033* .056*** .060*** .066*** .037** .044*** .001 .018* -.001 .016* Political efficacy (.015) (.011) (.016) (.012) (.014) (.011) (.009) (.007) (.007) (.007) .298*** .278*** .101*** .148*** .028 .041 .003 .009 .007 -.007 Election interest (.031) (.024) (.034) (.026) (.029) (.023) (.018) (.015) (.016) (.014) Controls

-.002 -.006** -.009*** -.008** -.003** .001 -.002*** .002 -.001 .002*** Age (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.001) .149*** .089*** -.067 -.036 -.060* .001 -.025 .020 -.033* -.004 Gender (.032) (.024) (.035) (.027) (.031) (.024) (.019) (.016) (.016) (.015) .054 .030 -.078 -.036 -.015 .015 .013 -.006 .006 .004 Tertiary education (.037) (.029) (.041) (.027) (.035) (.030) (.022) (.019) (.019) (.018) .005 .001 -.004 -.006** -.016** -.007** -.010*** -.003* -.004** .001 Household income (.003) (.002) (.003) (.002) (.003) (.002) (.002) (.001) (.001) (.001) .051 .015 -.074 -.082** -.009 -.004 -.003 -.020 -.004 .015 Australian born (.037) (.028) (.041) (.031) (.036) (.028) (.022) (.018) (.019) (.017) -.004 -.012 -.013 .008 -.028* -.007 -.019** -.003 -.019** -.002 Urban resident (.012) (.008) (.013) (.009) (.011) (.008) (.007) (.005) (.006) (.005) .457*** .796*** 1.068*** .843*** .926*** .540*** 1.051*** .713*** 1.096*** .632*** Constant (.116) (.089) (.127) (.098) (.110) (.089) (.068) (.058) (.058) (.055) Adjusted R2 .401 .386 .124 .134 .083 .077 .056 .056 .018 .046 (N) 2214 3955 2214 3955 2214 3955 2214 3955 2214 3955 Note. OLS=Ordinary least squares. Cell entries are coefficients with standard errors in parentheses. Source: Australian Election Study, 2010 and 2013 *p≤.05; **p≤.01; ***p≤.001

Table 4. OLS Regression Models Predicting Offline Political Participation in 2010 and 2013 (Interaction Effects) Discussion with Talk to people Work for party or Go to meetings or Contribute money others about vote candidate rallies 2010 2013 2010 2013 2010 2013 2010 2013 2010 2013 Internet use Frequency of general .014 .019* - .010 - .016 .005 .001 .007 - .001 - .004 .002 internet use (.009) (.008) (.010) (.009) (.009) (.008) (.005) (.005) (.005) (.005)

Frequency of election .098*** .069*** .090*** .034* .070*** .048*** .034** .022* .028** .019* internet use (.020) (.014) (.022) (.015) (.019) (.014) (.012) (.009) (.010) (.008) Media sources

Frequency of following .023 .024 -.000 .023 .009 .040** .021 .025* .012 .033*** election in newspapers (.022) (.015) (.024) (.017) (.021) (.015) (.013) (.010) (.011) (.009)

Frequency of following .075** .069*** .011 -.018 .029 -.002 .011 -.006 -.001 -.000 election on TV (.024) (.017) (.026) (.019) (.023) (.017) (.014) (.011) (.012) (.010)

Frequency of following .047** .058*** .063*** .025 .062*** .041** .018 .032*** .003 .015 election on radio (.018) (.013) (.019) (.015) (.017) (.013) (.010) (.008) (.009) (.008) Party mobilisation . 059 .151*** - .008 .013 .035 - .011 .032 .009 - .003 .005 Party contact (.032) (.025) (.035) (.028) (.030) (.025) (.019) (.016) (.016) (.015) Psychological resources .265*** .229*** .088 .128*** .014 .076*** .010 .049*** .024 .037** Political interest (.065) (.024) (.072) (.026) (.063) (.023) (.039) (.015) (.033) (.014) .034* .057*** .065*** .071*** .039** .049*** .001 .022** -.001 .019** Political efficacy (.015) (.011) (.016) (.012) (.014) (.011) (.009) (.007) (.007) (.007) .296*** .251*** .108*** .151*** .028 .047* .003 .013 .005 -.004 Election interest (.031) (.024) (.034) (.026) (.029) (.023) (.018) (.015) (.016) (.014) Controls - .002 - .006** - .009** - .008** - .003** - .000 - .002*** .001 - .001 .002*** Age (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.001) (.001) .147*** .090*** -.067 -.032 -.060* .006 -.025 .024 -.033* -.001 Gender (.032) (.024) (.035) (.027) (.031) (.024) (.019) (.016) (.016) (.015) .051 .029 -.078 -.026 -.015 .023 .013 -.000 .006 .009 Tertiary education (.037) (.030) (.041) (.033) (.035) (.029) (.022) (.019) (.019) (.018) .005 .000 -.004 -.006** -.016** -.006** -.010*** -.003* -.004** .001 Household income (.003) (.002) (.003) (.002) (.003) (.002) (.002) (.001) (.001) (.001) .052 .016 -.074 -.088** -.009 -.009 -.003 -.025 -.004 .011 Australian born (.037) (.028) (.041) (.031) (.036) (.028) (.022) (.018) (.019) (.017) -.004 -.014 -.013 .009 -.027* -.008 -.019** -.003 -.019** -.003 Urban resident (.012) (.008) (.013) (.009) (.011) (.008) (.007) (.005) (.006) (.005) Interaction Election internet use* .022 - .011 .014 - .003 - .011 .003 - .008* .022 .003 .022 political interest (.026) (.019) (.028) (.020) (.025) (.018) (.015) (.012) (.013) (.011) Election internet use* .031* .035*** .042** .026** .023 .054*** .003 .023*** -.008 .016** political efficacy (.013) (.009) (.015) (.010) (.013) (.009) (.008) (.006) (.007) (.006) Election internet use* -.050* -.027 .016 .063*** -.015 .026 -.014 .024* -.003 .015 election interest (.024) (.017) (.026) (.019) (.023) (.017) (.014) (.011) (.012) (.011) .299*** .801*** .938*** .781*** .992*** .488*** 1.108*** .671*** 1.084*** .600*** Constant (.219) (.090) (.241) (.099) (.210) (.089) (.130) (.058) (.111) (.055) Adjusted R2 .404 .389 .127 .141 .083 .091 .055 .069 .018 .055 (N) 2214 3955 2214 3955 2214 3955 2214 3955 2214 3955 Note. OLS=Ordinary least squares. Cell entries are coefficients with standard errors in parentheses. Source: Australian Election Study, 2010 and 2013 *p≤.05; **p≤.01; ***p≤.001

Appendix Table: Variables, Coding and Scoring 2010 2013 Std. Std. Varible Coding Means Dev. Means Dev. 1= not at all, 2=rarely,3=occasionally, Discussion online 4=frequently 1.21 .58 1.34 .72

Sign up to receive information 1=yes, 0= no .02 .13 .04 .20 Use online tool to promote parties 1=yes, 0= no .01 .12 .03 .17 Shared/posted non-official content 1=yes, 0= no .03 .17 .08 .27 1= not at all, 2=rarely,3=occasionally, Discussion with others 4=frequently 2.93 .88 2.95 .88 1= not at all, 2=rarely,3=occasionally, Talk to people about vote 4=frequently 1.44 .77 1.48 .80 1= not at all, 2=rarely,3=occasionally, Work for party or candidate 4=frequently 1.26 .68 1.31 .72 1= not at all, 2=rarely,3=occasionally, Go to meetings or rallies 4=frequently 1.09 .34 1.12 .45 1= not at all, 2=rarely,3=occasionally, Contribute money 4=frequently 1.06 .34 1.10 .44 Internet use 1= never uses to 7= several Frequency of general internet use times per day 4.69 2.50 5.51 2.22 Frequency of election internet 1=never used to 5 used many use times 2.26 1.16 2.58 1.24 Media source

Frequency of following election 1=none at all, 2= not much, in newspapers 3=some, 4=a good deal 2.74 .91 2.56 .97 Frequency of following election 1=none at all, 2= not much, on TV 3=some, 4=a good deal 3.09 .87 2.99 .92 Frequency of following election 1=none at all, 2= not much, on radio 3=some, 4=a good deal 2.49 1.04 2.40 1.05 Party mobilisation Party contact 1=yes, 0= no .47 .50 .61 .49 Psychological resources 1=none, 2= not much, Political interest 3=some, 4=a good deal 3.18 .79 3.13 .81 1= who people vote for cannot make a difference to 5=who people vote for can make a big Political efficacy difference 3.74 1.18 3.78 1.17 1=none at all, 2= not much, Election interest 3=some, 4=a good deal 3.13 .83 3.08 .85 Controls Age Years 56.55 16.49 54.11 16.97 Gender 1=female, 0=male .53 .50 .52 .50 Tertiary education 1=yes, 0= no .27 .44 .19 .39 Household income Quintiles 10.34 5.93 11.52 6.25 Australian born 1=yes, 0= no .72 .45 .71 .45 1=rural area or village to 5=a major city over 100,000 Urban resident people 4.07 1.32 3.91 1.42 Interaction (N) 2214 3955 Source: Australian Election Study, 2010 and 2013