First Monday

Digital skills and political participation in northeast Anatolia, Turkey by Duygu Ozsoy, Eyyup Akbulut, Sait Sinan Atlgan, and Glenn W. Muschert



Abstract
The study examines the relationship between digital skills and political participation, while controlling for political capital and exposure to political information via social media. Digital skills are conceptualized in four sub-types (operational, formal, informational, and strategic) and political participation in three sub-types (online, off-line, and civic participation). The study examines a non-Western sample drawn from the northeastern region of Turkey (n = 400), and data were collected through performance tests developed by van Deursen and van Dijk (2011), and respondents were surveyed regarding their political participation, demographic characteristics, political capital, and exposure to information about politics. Analysis involved exploratory factor analysis for data reduction and OLS regression. Findings indicate that digital skills of each type positively influence political participation and, similarly, exposure to political content through social media and political capital have positive effects on political participation. Digital skills most strongly predict civic and online political participation types, but are empirically unrelated to off-line political participation activities. The study examines a previously unstudied population in the non-Western context of northeast Anatolia, which is a novel empirical test considering nearly all previous studies have examined Western populations. While the overall effect that digital skills positively associate with political participation is generally confirmed, this study reports a nuance that may be culturally specific. In previous studies, digital skill has most strongly influenced online participation forms, while in the Turkish context civic participation is more strongly associated with digital skills.

Contents

Introduction
Literature
Method
Findings
Conclusion
Limitations

 


 

Introduction

For over two decades, scholars have investigated the effect of Internet use on political participation, and there is a wide, rapidly expanding literature on the topic. In the Web 2.0 era, research has focused more specifically on the use of social networking sites [SNS] rather than general Internet use. The Internet offers new possibilities for online participation, reduces the cost of accessing information (Anduiza, et al., 2009), and the migration of social relations into SNS platforms changes traditional time and space limitations. These changes allow for broader engagement combined with reduced costs of connectivity (Gil de Zúñiga and Valenzuela, 2011), gives consumers easy access to content, lowers the bar for information posting/sharing of user-created content. Combined, these new technical, communicative, and social developments contribute a new dimension of political participation (Gil de Zúñiga, et al., 2014).

Use of SNS platforms allows traditional political participation to be extended into complementary online dimensions, while also potentially offering opportunities for participation in new forms of activities online (Vissers and Stolle, 2014). Studies have indicated that the types of Internet activities undertaken are more important than the amount of time engaged in online political participation (Bode, 2012; Quintelier and Vissers, 2008). In other words, effective use of the Internet is more important for political participation, and while digital skills determine efficacious Internet use, possession of strong digital skills would make political participation by skilled Internet users more impactful (Hargittai, 2002; van Dijk, 2002). Thus, there is a noteworthy relationship between digital skills, often via SNS use, and effective online political engagement (Anduiza, et al., 2009; Hargittai and Shaw, 2013).

This article examines the relationship between digital skills (including the sub-types defined operational, formal, informational, and strategic skills) and political participation (including the sub-types of online participation, off-line participation, and civic participation) while controlling for political capital levels and exposure to political information via social media. The main contribution is thus the comprehensive definition and measurement of digital skills types and political participation types, which allows the empirical test of the effects of digital skills on participation. In specific, digital skills are measured using performance tests, known as the most valid method of assessing skills (van Deursen and van Dijk, 2011), in which Internet users are given a PC and a set of tasks to complete. Their use of the PC is then tracked, allowing an external assessment of their digital skills, as reflected in their ability and speed in completing the requested tasks. The skills tests allowed the documentation of participants’ overall digital skills, and their level of specific digital skill within noted sub-types, including technical abilities to utilize ICTs and abilities to utilize information effectively (van Deursen and van Dijk, 2011).

Similarly, this analysis examined multiple dimensions of political participation, including off-line political participation, online political participation, and civic participation types (Chae, et al., 2019). While some studies have measure different types of engagement using overlapping indices, this potentially conflates the different types of engagement (see Boulianne, 2009). Thus, this study uses both an aggregate measure of political participation and distinctly separate measures for sub-types of political participation, as recommended by Vissers and Stolle (2014).

 

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Literature

Research examining the relationship between the use of social networking sites and political participation reveal conflicting results. Some studies suggest that the relationship is positive, while others assert that the relationship is weak and inconsiderable (Baumgartner and Morris, 2010; Dimitrova and Bystrom, 2013). Some important reasons for the contradiction of the findings could be related to differences in methodological aspects of studies (e.g., sample types, sample size, variations among variables examined, and the presence or absence of mediator variables) or idiosyncrasies associated with the research setting (e.g., whether the research was conducted during an election period or some other, broader political context) (Boulianne, 2009; Boulianne, 2015; Chae, et al., 2019; Tang and Lee, 2013; Xenos, et al., 2014).

However, meta-analyses of such relevant studies (see Boulianne, 2018, 2015, 2009) show there is a positive relationship between both Internet and SNS use and participation, but that this effect has increased unevenly over time, as data collected since 2000 show a larger effect sizes. While early studies reveal that Internet use has a small, but positive effect on political participation, newer studies reveal substantially stronger and positive effects (Boulianne, 2018). Another meta-analysis (Skoric, et al., 2016) also finds a positive relationship between SNS use and social capital, civic engagement, and political participation. Although the relationship is positive, the extent to which the association reflects a causal relationship remains debated (Boulianne, 2015; Theocharis and Quintelier, 2016). Informational use of SNS for political reasons and news has a positive relationship with both online and off-line political participation and civic engagement (Cho, et al., 2009; Gil de Zúñiga, et al., 2012; Gil de Zúñiga, et al., 2013; Gil de Zúñiga, et al., 2014; Holt, et al., 2013; Valenzuela, et al., 2009), and while these associations may be positive, a meta-analysis (Chae, et al., 2019) shows that Internet use is most strongly related to online participation, then to civic engagement, and finally to off-line participation.

Although some studies find a weak relationship between online and off-line participation (Emmer, et al., 2012), the definition of online political activity is important. For example; Conroy and colleagues [1] found that participation in online political groups is strongly correlated with off-line political participation. One study conducted during an election period finds that involvement in online political activities before an election directly associates with off-line participation after the elections (Lin, 2016). There is also a positive relationship between Internet activity and off-line civic participation (Purdy, 2017). Another important factor in the relationship between online and off-line participation is age, as online participation leads off-line, especially among late adolescents (Kim, et al., 2017). The impact of online participation on off-line engagement, especially for very young people, suggests a change of political participation compared to the traditional definition.

Even though information-seeking and active use of SNS is more strongly associated with increased levels of participation, compared with leisure and passive Internet use (Hoffmann, et al., 2017), relational SNS use is also important for political engagement, an indirect effect via allowing citizens political expression (Gil de Zúñiga, et al., 2014). Exposure to political content on social media positively and significantly predicts both off-line and online participation (Tang and Lee, 2013; Valeriani and Vaccari, 2016), although people have stronger ties with those who share similar interests and attitudes via SNS, they nonetheless interact with those who hold different perspectives. Such engagement with others holding divergent opinions provides access to information and resources available beyond one’s inner circle (Gil de Zúñiga and Valenzuela, 2011; Scheepers, et al., 2014). Thus, as the use of social media increases, the heterogeneity of opinions expressed increases, which also seems to drive further engagement (Gil de Zúñiga and Valenzuela, 2011; Kim, et al., 2013). Therefore, the use of social media changes news consumption and political discourse, leading to greater heterogeneity (Messing and Westwood, 2014).

Moreover, since introverts tend to use more social media, they tend to connect with more a comparatively heterogeneous network, which supports participation by increasing social interaction and information access capabilities (Gil de Zúñiga and Valenzuela, 2011). SNS use also increases political knowledge more for the less affluent persons, because higher socio-demographic people have the opportunity to access information even when they do not have Internet access (Morris and Morris, 2013). Thanks to both exposure and network heterogeneity, increased SNS use increases the level of participation of previously passive or less active participants, which narrows the participation gap (Chan and Guo, 2013; Gibson, et al., 2005; Vissers and Stolle, 2014).

Different form of online media such as news sites, political party Web sites, and SNS affect participation in different ways (Dimitrova, et al., 2014). Indeed, it is not so much the amount of time spent in online activities that influences political participation, but rather the effect is more strongly noted among some forms of online activities than for others. In other words, different uses of the Internet affect participation at different levels and in different ways. Internet use demands new skills in addition to traditional skills, these are called digital skills (Bonfadelli, 2002; Steyaert, 2002, 2000), which are prerequisites for Internet use. Thus, as online skill levels increase, effective use of the Internet also increases, and users are able to derive greater benefits (Hargittai, 2002; van Dijk, 2002; Zillien and Marr, 2013).

Therefore, in this study, we investigate the relationship between digital skill levels and political participation, specifically employing the digital skill types and definitions posited by van Deursen and van Dijk (2011), including medium-related and content-related skill types.

Medium-related Internet skills consist of operational skills, which include a basic command of an Internet browser, and formal skills, which include the ability to navigate and orient oneself within the Internet’s hypermedia structure. The first type of content-related Internet skills consists of information skills, which include the ability to find, select, and evaluate sources of information on the Internet. Secondly, strategic skills refer to one’s capacity to use the Internet as a means to reach particular personal and professional goals. [2]

This study tests a number of associations between Internet skills (including van Deursen and van Dijk’s four types) and political participation (including online participation, off-line participation, and civic participation).The following hypotheses are derived from the supporting literature, and are the analytical focus for this article:

 

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Method

Data were gathered through direct observation of performance of digital skills tests and via administration of a face-to-face questionnaire to record demographic characteristics, political capital, exposure to political content, and political participation. Subjects’ digital skills were assessed via performance tests developed by van Deursen and van Dijk (2011) though adapted to Turkey. Such tests measured participants’ digital skills in four sub-categories (operational, formal, informational, strategic skills). The sample (n=400) was recruited from the target population of Internet users in three provinces northeast Anatolia, Turkey: Bayburt, Erzincan, and Erzurum, as defined by the Classification of Territorial Units of the Turkish Statistical Institute (TurkStat). Participation was limited to those who were active Internet users, and who participated in at least one social networking site. The latter criterion was employed, as studies indicate that most online political participation takes place on social media (Tang and Lee, 2013; Valeriani and Vaccari, 2016). Participants were provided with computers to access the Internet, and then provided a series of online tasks to complete. Their performance of these tasks was tracked (specifically whether they were able to complete the tasks, and if so how much time was required for each task), in order to give a direct observation used to measure digital skill levels.

Respondents also completed a questionnaire to measure demographics, Internet habits, political capital, exposure to political information, and political participation. The questionnaire was administered in-person at the time of the skills test. The demographic information recorded gender, age, and education level, monthly household income. Internet use was also recorded, including how long participants have been using the Internet (month), hours they used per week, and how freely respondents had access to the Internet in terms of time(s), device(s) and place(s) of access.

Questions were also included regarding respondents’ political capital and exposure to political media. Political capital was measured using the scale developed by Hargittai and Shaw (2013), consisting of three sub-dimensions. First, respondents were asked about their level of interest in politics; second, respondents were asked to identify specific facts about Turkish politics, in order to measure their level of political knowledge; and, third, respondents indicated their level of support for political parties. Similarly, respondents also answered four questions related to their exposure to political content via social media.

The measure of participants’ political participation used the political participation scales developed by Wolfsfeld and colleagues (2016), Hargittai and Shaw (2013), and Çuhadar (2006). In all, three aspects of political participation were measured: online political participation, off-line political participation, and civic participation. Online political participation was measured via 13 questions related to politics online, such as Internet searching, posting online opinions, participating in online discussions, writing online comments, and contacting politicians online. Off-line political participation was measured via 18 questions assessing voting behaviors, advocating for candidates, supporting work of political parties, fundraising, making financial contributions to campaigns, and writing to or otherwise communicating with politicians. Civic participation was measured via seven questions indicating signing petitions, participating in marches, working for NGOs, attending public forums, or participating in unions. All measures of political participation used a five-point Likert-type scale.

Exploratory factor analysis was conducted to reduce data for the political measures, producing scales consistent with the measures applied in the original studies from which the scales were derived (see Çuhadar, 2006; Hargittai and Shaw, 2013; Wolfsfeld, et al., 2016). In all, these factor analyses resulted in five scales used in the analysis: political capital, exposure to political content via social media, online political participation, off-line political participation, and civic participation [3].

 

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Findings

Descriptive statistics. The sample (n=400) consisted of 204 women and 196 men of varying ages, levels of education, and income levels, approximately representative of the study population drawn from the Bayburt (n=44, or 11.0 percent), Erzincan (n=96, or 24.0 percent), and Erzurum (n=260, or 65.0 percent) provinces in northeast Anatolia.

The descriptive statistics for the five political variable are shown in Table 1, including political capital (political knowledge and political interest), exposure to political content through social media, online political participation (political expression via the Internet and online activities), off-line political participation (offline activities and political persuasion), and civic participation. Finally, all measures are combined into a scale measuring total political participation of the respondents. Finally, the survey measured participants’ party membership (80.5 percent were not members), membership in NGOs (84.8 percent not were members), and membership in any union (85.3 percent were not members).

 

Table 1: Variables measuring political dimensions
 Political capital measuresExposure to online political contentOnline participation measuresOff-line participation measuresCivic participation
Political knowledgePolitical interestExpressionActivismActivismPersuasion
n399400400400400400400400
mean0.493.202.941.611.381.502.631.19
sd0.2601.1531.0240.9900.6720.7281.0790.554

 

Inferential statistics. OLS regression analyses tested the relationship between digital skills and political participation types. According to the analyses, digital skills are highly significant predictors (p < 0.001) of all types of political participation and overall level of political participation, except for off-line political participation, as demonstrated in Table 2.

 

Table 2: OLS regression of digital skill levels on political participation types
Note: n=400; *p<0.05; **p<0.01; ***p<0.001
 Online political participationOff-line political participationCivic participationGeneral political participation
BSE BβBSE BβBSE BβBSE Bβ
Digital skills in general.113.031.178***.010.032.015.228.030.359***.154.032.242***
R2.032.000.129.059
F12.971***.09258.985***24.782***

 

The impact of digital skill explains roughly six percent of the variability in overall political participation (R2 = .059; F = 24.782; p < 0.001). Digital skills level explained 13 percent of the variability in civic participation (R2 = .129; F = 58.985; p < 0.001). Finally, digital skill levels predicted three percent of the variability in online political participation (R2 = .032; F = 12.971; p < 0.001). However, digital skills did not significantly explain offline political participation. The findings indicate nonetheless that digital skill level positively affects both overall political participation level and political participation type, such that, as digital skills level increases, the rate of political participation also increases. These analyses offer general support for Hypothesis 1 as online political participation, civic participation, and political participation in general all directly related to digital skills, while off-line political participation is not influenced by digital skill levels.

Regression analyses were further employed to test the associations between the four sub-categories of digital skills and political participation variables. Analysis indicated that operational-type skills were a significant predictor of all political participation types, except for off-line political participation and overall political participation level, as demonstrated in Table 3.

 

Table 3: OLS regression of operational digital skill levels on political participation types
Note: n=400; *p<0.05; **p<0.01; ***p<0.001
 Online political participationOff-line political participationCivic participationGeneral political participation
BSE BβBSE BβBSE BβBSE Bβ
Operational digital skills.352.108.161**-.018.110-.008.690.104.316***.452.107.207***
R2.026.000.100.043
F10.579**.02744.055***17.762***

 

Operational skills explained four percent of overall political participation (R2 = .043; F = 17.762; p < 0.001); three percent of online political participation (R2 = .026; F = 10.579; p < 0.01), 10 percent of civic participation (R2 = .100; F = 44.055; p < 0.001). Analysis indicates that operational skills positively affects both overall political participation level and political participation types, while off-line participation is not associated with operational skills. According to this analysis, Hypothesis 2 is generally supported, as online political participation, civic participation, and political participation in general all directly related to operational skills, while off-line political participation is not influenced by operational skills.

Formal-type digital skills were tested for their ability to predict the political participation types and the overall political participation level. Formal skills significantly predict overall political participation level, online political participation, and civic participation, however, this set of skills did not significantly explain off-line political participation, as reported in Table 4.

 

Table 4: OLS regression of formal digital skill levels on political participation types
Note: n=400; *p<0.05; **p<0.01; ***p<0.001
 Online political participationOff-line political participationCivic participationGeneral political participation
BSE BβBSE BβBSE BβBSE Bβ
Formal digital skills.384.120.159**-.025.121-.010.657.117.272***.446.119.184***
R2.025.000.074.034
F10.292**.04231.675***13.981***

 

Formal skills explained three percent of overall political participation (R2 = .034; F = 13.981; p < 0.001); 7.4 percent of civic participation (R2 = .074; F = 31.675; p < 0.001); three percent of online political participation (R2 = .025; F = 10.292; p < 0.01). Formal skills did not have a significant ability to predict off-line political participation. Thus, formal skills have a significant positive effect on general political participation and two sub-categories. Thus, Hypothesis 3 is generally confirmed by this analysis, as online political participation, civic participation, and political participation in general are directly related to formal-type digital skills, while off-line political participation is not influenced by formal skills.

Informational-type skills were tested for their ability to predict political participation in general and among its sub-types. Analysis indicated that informational skills significantly predict overall political participation level and all sub-types of political participation, except off-line participation, as described in Table 5.

 

Table 5: OLS regression of informational digital skill levels on political participation types
Note: n=400; *p<0.05; **p<0.01; ***p<0.001
 Online political participationOff-line political participationCivic participationGeneral political participation
BSE BβBSE BβBSE BβBSE Bβ
Informational digital skills.341.100.168**.092.102.045.684.096.336***.485.099.238***
R2.028.002.113.057
F11.515**.81450.758***23.989***

 

Informational skills explained six percent of overall political participation (R2 = .057; F = 23.989; p < 0.001); three percent of online participation (R2 = .028; F = 11.515; p < 0.01), and 11 percent of civic participation (R2 = .113; F = 50.758; p < 0.001). Informational skills positively predicted overall political participation, online political participation, and civic participation, but were empirically unrelated to off-line participation. As a result of this analysis, Hypothesis 4 is generally confirmed, as online political participation, civic participation, and political participation in general all directly related to informational-type digital skills, while off-line political participation is not influenced by informational Internet skills.

Like other digital skills types, strategic skills significantly predict overall political participation level and political participation types, with the exception of off-line participation, as described in Table 6.

 

Table 6: OLS regression of strategic digital skill levels on political participation types
Note: n=400; *p<0.05; **p<0.01; ***p<0.001
 Online political participationOff-line political participationCivic participationGeneral political participation
BSE BβBSE BβBSE BβBSE Bβ
Strategic digital skills.233.099.117*.039.100.019.576.096.288***.374.098.187***
R2.014.000.083.035
F5.492*.14936.117***14.467***

 

Strategic skills explained four percent of overall political participation (R2 = .035; F = 14.467; p < 0.001); a modest one percent of online participation (R2 = .014; F = 5.492; p < 0.001); and, eight percent of civic participation (R2 = .083; F = 36.117; p < 0.001). Strategic skills positively predicted both overall political participation, civic participation, and online political participation, but was not associated with off-line participation. Thus, Hypothesis 5 is generally confirmed, as online political participation, civic participation, and political participation in general all directly related to strategic-type digital skills, while off-line political participation is not influenced by strategic skills.

Regression analysis further tested the extent to which the exposure to political content through social media predicts political participation types. The exposure to political content through social media is a significant predictor of the overall political participation level and all sub-types of political participation. as demonstrated in Table 7.

 

Table 7: OLS regression of exposure to online political content on political participation types
Note: n=400; *p<0.05; **p<0.01; ***p<0.001
 Online political participationOff-line political participationCivic participationGeneral political participation
BSE BβBSE BβBSE BβBSE Bβ
Exposure to online political content.420.045.420***.455.045.455***.297.048.297***.164.044.464***
R2.177.207.088.215
F85.412***104.055***38.566***108.946***

 

The exposure to political content through social media explained 22 percent of overall political participation (R2 = .215; F = 108.946; p < 0.001); 18 percent of online political participation (R2 = .177; F = 85.412; p < 0.001), 21 percent of off-line political participation (R2 = .207; F = 104.055; p < 0.001); and, nine percent of civic participation (R2 = .088; F = 38.566; p < 0.001). Thus, exposure to political content through social media affects all forms of political participation tested, and as a result, Hypothesis 6 is supported in each of the analyses.

A final regression analysis tested the ability of digital skill level in general to predict political participation types, while controlling for levels of political capital and exposure to political content via social media. Results indicated that these control variables increase the overall explanatory power of the models, and that their addition does not diminish the explanatory power of the digital skill variables, as described in Table 8.

 

Table 8: OLS regression of digital skill level on political participation types, controlling for political capital and exposure to online political content
Note: n=400; *p<0.05; **p<0.01; ***p<0.001
 Online political participationOff-line political participationCivic participationGeneral political participation
VariableBSE BβBSE BβBSE BβBSE Bβ
Digital skill.104.028.164***.005.026.008.225.028.354***.147.026.232***
Political capital.290.058.232***.518.054.413***.171.059.136**.378.055.301***
Exposure to online politics.331.046.332***.312.043.313***.237.047.237***.350.043.350***
R2.247.357.228.343
F43.181***73.002***38.833***68.594***

 

The variables of digital skills level, political capital and exposure to political content through social media together explain 34 percent the of overall political participation level (R2 = .343; F = 68. 594; p < 0.001). The standardized β coefficients indicate that the exposure to political content through social media is the strongest predictor of the overall political participation level, followed by political capital and digital skills, respectively. Similarly, the combined model predicted 36 percent of variability in off-line political participation (R2 = .357; F = 73.002; p < 0.001); 25 percent of online political participation (R2 = .247; F = 43.181; p < 0.001); and, 23 percent of civic participation (R2 = .228; F = 38.833; p < 0.001). Finally, each of these variables positively affect general political participation and all sub-types of political participation. These findings indicate that any increase in digital skills, political capital, and exposure to online political content leads to an increase in the level of general political participation, including all sub-types of political participation. As a result of this analysis, Hypothesis 7 is supported by each of the models.

 

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Conclusion

In this research, analysis has empirically demonstrated that both digital skills in general and each of the four skill types positively affect general political participation. Similarly, exposure to political content through social media positively affects general political participation. Exposure to political content through social media, digital skills level, and political capital, together, significantly predict general political participation level and political participation types. Digital skill level significantly predicts all types of political participation and overall level of political participation, with the exception of off-line political participation.

While the digital skill levels strongly predict levels of civic participation, and to a lesser extent online political participation, digital skills do not appear associated with off-line political participation in this study. Off-line participation includes traditional activities such as voting, working for political campaigns, donating money to candidates, and displaying political bumper stickers, as well as less conventional behaviors, such as protesting, boycotting, and buying products for political reasons [4]. All of these activities are already existing in our lives before the digital age, and thus it is understandable why digital skills do not explain off-line participation. On the other hand, online political participation requires new skills compared to off-line political participation.

Putnam (1995) describes civic engagement as people’s connections with the life of their communities, not merely with politics [5]. Despite this, he was pessimistic about the effect of media use on engagement, and today it is known that SNS use helps people to expand their social networks while making those network more heterogeneous, increasing social interaction, and blurring the boundaries between public and private (Gil de Zúñiga and Valenzuela, 2011; Kim, et al., 2013; Skoric, et al., 2016). The empirical analyses conducted in this study confirm that, among a previously unstudied, non-Western population, previous finding reported in the literature still stand, and that Internet use is mostly related to online, then to civic and least off-line forms of political participation (Chae, et al., 2019). However, a nuance revealed in the present study, while confirming the positive association previously identified between Internet use (especially SNS) and participation, indicated that skillful Internet use more strongly explains civic participation than they do online political participation.

However, a nuance revealed in the present study, while confirming what has been previously identified between skills and participation, indicated that digital skills more strongly explain civic participation than they do online political participation.

Since Turkish culture is highly collective and Turks more strongly community-minded than Western societies, this cultural difference may explain why civic engagement is more strongly affected, as the Turkish population is more likely to take political sentiments, and to express them in community action vs. the relatively distanced expression in online political participation.

In the end, there is an important relationship between the types of Internet use people undertake and political participation. Information-oriented and active use types lead to more participation, while entertainment-oriented and passive use leads to less participation (Hoffmann, et al., 2017). Similarly, the relationship between SNS use for news and online political participation is greater (Gil de Zúñiga, et al., 2014). In broadest terms, the relationship between digital skills and political participation remains strongly indicated among the study population in northeast Anatolia. More skillful use of the Internet and SNS lead to more heterogeneous political exposure and the expansion of one’s social networks, which in turn tends to result in greater online political participation and civic participation.

 

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Limitations

Although the analyses reported in this study have indicated the positive association between the test variables, the study is not without limitations. The sample size was limited to 400 participants, driven by the digital skills level tests which are highly labor-intensive to facilitate. As noted in previous research, use of large samples is very difficult for this method (see Hargittai, 2002). While it would be possible to increase the sample size using self-identified skill levels, it would undermine the ability to measure digital skills most accurately using performance tests (van Dijk, 2013). Indeed, van Deursen and van Dijk (2011) indicate that the fittest method to measure informational and strategic digital skill levels is to conduct performance tests, even if operational and formal digital skill levels could be measured through self-reporting. In the present study, the sample size was limited in order to maintain more precise measurement of the digital skill levels.

Another limitation is that only Internet users are studied, because the purpose of the study was to determine the relationship between digital skills levels, different skill types, and political participation. Studies that examine the relationship between social networking site usage and political participation show that users exposed to political information on social networking sites react similarly to those exposed to off-line political information (Gil de Zúñiga, et al., 2014). As the study does not measure respondents’ exposure to off-line political information (for example, via television, radio, magazines, or newspapers), it is impossible with the current data to specify whether political action is motivated by online exposure.

Finally, in the current digital environment, most online political participation activities are carried out through social networking sites. Considering all these theoretical reasons, only the people who have membership in at least one social networking site are included in the study. In the research, the criteria of having an account of at least one social networking site was determined, but no distinction was made between which social networking site(s) respondents used. Recent studies on social networking sites reveal that the use of different social networking sites may be utilized for different purposes (Dimitrova, et al., 2014). Therefore, future studies should be sensitive to the differences of social networking sites and their specific usage, as certain platforms may be more commonly used for political participation than others. End of article

 

About the authors

Duygu Özsoy is an assistant professor of communications in the Department of Radio, Television and Cinema at Atatürk University (Erzurum, Turkey). Her research focuses on Internet studies and digital technologies, particularly as applied to Turkey’s non-western modernization process and transformation through globalization.
Direct comments to: duyguozsoy [at] atauni [dot] edu [dot] tr

Eyyup Akbulut is an associate professor of communication in the Department of Public Relations and Advertising at Atatürk University (Erzurum, Turkey). His research focuses on public relations, organization-public relationships, and corporate reputations.
E-mail: eyyup [dot] akbulut [at] atauni [dot] edu [dot] tr

Sait Sinan Atlgan is an assistant professor of communications in the Department of Public Relations and Advertising at Atatürk University (Erzurum, Turkey). His research focuses on organizational communication and digital media literacy.
E-mail: sinan [dot] atilgan [at] atauni [dot] edu [dot] tr

Glenn W. Muschert is a professor of sociology in the Department of Humanities and Social Sciences at Khalifa University of Science and Technology (Abu Dhabi, UAE). His research focuses on digital inequalities, sustainable development, and the solution of social problems.
E-mail: glenn [dot] muschert [at] ku [dot] ac [dot] ae

 

Acknowledgements

This research received financial backing as project number 215K159 from TÜBTAK (Scientific and Technological Research Council of Turkey or Türkiye Bilimsel ve Teknolojik Araştrma Kurumu [TÜBTAK]). The authors thank TÜBTAK for funding support.

The authors acknowledge the research assistance of Şeyma Çalklar, Kevser Çelik, Hatice Gökçe, Nur Kaban, Sultan Koca, and Kaan Mert Öztürk.

 

Notes

1. Conroy, et al., 2012, p. 1,535.

2. van Deursen and van Dijk, 2015, p. 783.

3. Results of factor analyses have been omitted to conserve space.

4. Valenzuela, et al., 2009, p. 879.

5. Putnam, 1995, p. 665.

 

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Editorial history

Received 6 June 2020; accepted 9 June 2020.


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This paper is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Digital skills and political participation in northeast Anatolia, Turkey
by Duygu Özsoy, Eyyup Akbulut, Sait Sinan Atlgan, and Glenn W. Muschert.
First Monday, Volume 25, Number 7 - 6 July 2020
https://journals.uic.edu/ojs/index.php/fm/article/download/10854/9566
doi: http://dx.doi.org/10.5210/fm.v25i7.10854