(2014) A Moveable Feast: Do Mobile Media Technologies Mobilize or Normalize Cultural Participation?

Human Communication Research ISSN 0360-3989

ORIGINAL ARTICLE

A Moveable Feast: Do Mobile MediaTechnologies Mobilize or NormalizeCultural Participation?

Wenhong Chen

Department of Radio-TV-Film, College of Communication, University of Texas at Austin, TX 78712-1067, USA

This research draws on national survey data in the United States to investigate the varia-tion of mobile cultural participation by the access to mobile Internet devices, the intensity,diversity, and specific types of app use, sociodemographic characteristics, and in-personcultural participation. Results show that the access to mobile Internet devices and diverseapp use, especially recreational and work-related app use, are positively related to mobilecultural participation. The Hispanic lead, the reversed educational gap, and the disap-peared urban–rural divide in mobile cultural participation suggest that it offers membersof disadvantaged groups a more accessible venue for cultural participation. The strongerrelationships between mobile Internet devices, in-person and mobile cultural participationamong the less educated support the mobilization thesis.

doi:10.1111/hcre.12041

Many cultural organizations have deployed a wide range of digital and mobile tech-nologies for cultural production, promotion, and engagement with stakeholders ina more interactive and participatory media environment. However, mobile culturalparticipation—defined as mediated cultural participation supported by mobile mediaand communication technologies—has not yet received much scholarly attention.As mobile devices and services make possible cultural participation on the go, thisresearch explores mobile cultural participation at the intersection of the literatures ofcultural capital (Bourdieu, 1986; DiMaggio & Mukhtar, 2004; DiMaggio & Ostrower,1990; Lizardo, 2006), digital divides (Hargittai & Hinnant, 2008 ; Selwyn, 2004), andsocial implications of mobile media and communication (Campbell & Kwak, 2011a,2011b; Rojas & Puig-i-Abril, 2009).

Drawing insights from the mobilization thesis and the normalization thesis(Boulianne, 2009; Hirzalla, van Zoonen, & de Ridder, 2011; Norris, 2001; Norris &Inglehart, 2009), this research examines whether mobile cultural participation helpscultural organizations to reach patrons from broader social strata or distracts themfrom in-person cultural participation. Using national survey data in the United States,this research focuses on the variation of mobile cultural participation by the access to

Corresponding author: Wenhong Chen; e-mail: [email protected]

Human Communication Research (2014) © 2014 International Communication Association 1

Mobile Cultural Participation W. Chen

and use of mobile Internet devices, especially the intensity, diversity, and specific typesof app use, sociodemographic characteristics, and in-person cultural participation.

Background: Mobile cultural participation

Bourdieu (1984, 1986, 1989) understood cultural capital as cultural knowledge andcompetencies accumulated by an individual in three forms: the embodied state inthe form of long-lasting dispositions of the mind and body, the objectified state inthe form of the ownership or consumption of cultural goods (e.g., books, art, andother cultural artifacts), and the institutionalized state in the form of educationalqualification. Highlighting the implications of cultural capital, especially highbrowcultural capital, for maintaining class distinction and reproducing social inequalities(Bourdieu & Passeron, 1977), Bourdieu’s seminal work revealed that the intergener-ational transmission of cultural capital via family socialization in upper-middle-classhouseholds served as “the best hidden and socially most determinant educationalinvestment” (1986, p. 244).

Yet, scholars in North America and elsewhere have argued that diverse culturalcapital can be used for spanning class boundaries (Bennett & Silva, 2011; DiMaggio,1987; Lamont & Molnár, 2002). Accordingly, high-status people have shifted fromculture snobs specialized in high culture to culture omnivores with a broad culturalrepertoire, while low-status people tend to be univores with a limited cultural reper-toire (Peterson & Kern, 1996).

More recent studies showed that class affected both cultural omnivorousness andvoraciousness—the diversity and the frequency of cultural participation (Katz-Gerro,2002). As importantly, subgroup cultural capital refers to cultural knowledge andartifacts acquired by subcultural group members, which may have ambivalent andsometimes contentious relationships with mainstream culture, but can be used forin-group status attainment and out-group differentiation (Gelder, 2007).

In empirical research, cultural capital is often operationalized as attendance orparticipation in cultural activities such as visiting museums, galleries, shows, exhibits,or historic sites, as well as attending live music, dance, theater performance, arts,crafts, or music events (DiMaggio & Mukhtar, 2004; DiMaggio & Ostrower, 1990;Lizardo, 2006; López-Sintas & Katz-Gerro, 2005). Americans’ cultural participationhas been declining since the 1980s: Except jazz and art museums, the attendance inboth highbrow (e.g., classical music and ballet) and middlebrow culture (e.g., craftfairs, musical theaters, and historic sites) has dropped across almost all age, gender,and educational groups (DiMaggio & Mukhtar, 2004). More recent research suggests acontinued decline in cultural attendance, especially in terms of visiting museums andgalleries or attending theater, craft fairs or art festivals (National Endowment for theArts, 2013).

As a relatively new form of mediated cultural participation, mobile cultural partic-ipation brings in new dynamics. Using mobile devices such as smartphones or tablets,people can listen to or download information or images before, during, or after their

2 Human Communication Research (2014) © 2014 International Communication Association

W. Chen Mobile Cultural Participation

visit to a museum, art gallery, or historic site, with or without physical presence.They can view or download painting, sculpture, graphic design, photography, orperformance.

Comparing to in-person cultural participation, mobile cultural participation hasgreater spatial and temporal flexibility, which is more spontaneous and less demand-ing of people’s time and resource. Yet, what mobile cultural participation offers is morethan convenience. It allows cultural participation to be more interactive, participa-tory, and networked. Using mobile applications (apps), people can switch betweenthe real and the virtual cultural spaces, generating and sharing content about theircultural appreciation or appropriation with friends or followers in real time. Suchuser-generated content enables users to interact with and mobilize one another forcultural participation.

A recent study of 1,258 arts organizations in the United States identifiedwidespread use of digital and mobile technologies to “create awareness of theirorganization, promote events and exhibits, provide customized experiences forpatrons, sell tickets or merchandise, streamline customer service needs, and expandtheir mission-driven work” (Thomson, Purcell, & Rainie, 2013, p. 3). Nevertheless,more than one fifth of these organizations were concerned that mediated culturalparticipation would decrease in-person cultural participation (Thomson et al., 2013).However, a striking lack of research on mobile cultural participation has hinderedour understanding of its patterns and implications. In particular, does mobile culturalparticipation help to reach people from broader social strata, especially membersof underprivileged groups? Does mobile cultural participation distract people awayfrom in-person participation? That is, do mobile media technologies mobilize previ-ously less active cultural participants or merely offer those who are already active anadditional mode of engagement?

Theoretical framework

This research integrates the literatures on cultural capital, digital divides, and socialimplications of mobile media and communication. In-person cultural participationvaries significantly by the familiar fault lines of social inequalities: class, gender,race, and community type (Bourdieu, 1986; Yaish & Katz-Gerro, 2012). These mark-ers of social inequalities also shape people’s access to, use of, and gain from newmedia and communication technologies (Hargittai & Hinnant, 2008; Selwyn, 2004).An emerging literature on mobile media and communication has, by and large,supported positive or neutral relationships between various aspects of mobile usagepatterns, sociability, civic and political engagement (Campbell & Kwak, 2011a, 2011b;Hampton, Sessions, & Her, 2011).

Thus, a fuller understanding of mobile cultural participation needs to take intoaccount the main effect of usage patterns, sociodemographic characteristics, andin-person cultural participation as well as their interactions. This is necessary becausethe social implications of new media and communication technologies often vary



by users’ sociodemographics and pre-existing inclinations (DiMaggio, Hargittai,Neuman, & Robinson, 2001).

In particular, the mobilization thesis has argued that members of underprivilegedgroups would be empowered as they gain access to previously unavailable technolo-gies (Norris & Inglehart, 2009), while the normalization thesis has emphasized thattechnologies primarily benefit those who are better off or already active (Hirzallaet al., 2011). In what follows, I develop hypotheses and questions on the main effect,and then discuss whether the mobilization or the normalization thesis would betterexplain mobile cultural participation.

Access to mobile devices and usage patternsMobile phones allow users to conduct a range of activities—informational, recre-ational, relational, or work-related—to gratify diverse needs: sociability, mobility, orproductivity (Campbell & Kwak, 2010b; Katz, 2007). Mobile Internet devices, espe-cially smartphones, have become symbols and hubs of a digital lifestyle. The moredevices users own, the greater their digital capability and the more diverse their usagepatterns (Horrigan, 2009). Thus,

H1: Access to mobile Internet devices is related to mobile cultural participation.

First introduced by Apple iPhone in 2007, apps have rapidly become an essentialfeature of mobile Internet devices. Although there has been limited research on thesocial implications of app use, people who use a variety of apps are more likely touse them for new social and cultural practices such as mobile cultural participationbecause of their greater exposure to and affinity of mobile technologies. As Schmitzand Fulk pointed out, “the more types of situations for which a medium is usable(the richer it is perceived to be in term of speed, number of channels, type oflanguage, and personalness), the more useful it may be seen and the more it maybe used” (1991, p. 492). The diversity of mobile phone use was positively relatedto mobile giving: donating to social causes via mobile devices (Chen & Givens,2013). Thus,

H2: Diverse mobile app use is related to mobile cultural participation.

Moreover, the specific types of mobile phone use can have important implica-tions for social interaction and civic engagement. Studies have found that frequentinformational and recreational mobile phone use was associated with civic engage-ment (Campbell & Kwak, 2010a; Rojas & Puig-i-Abril, 2009). Relational mobilecommunication—using mobile phones to maintain social contacts—was positivelyrelated with mobile giving (Chen & Givens, 2013) and attending social leisure activi-ties (Chen, Lo, Wei, Xu, & Zhang, 2012), but not with civic engagement (Campbell &Kwak, 2010a). Research on work-related mobile communication has been centeredon the blurring boundaries between work and life domains. As the literature is thinand inconsistent, a research question is formulated:

RQ1: Is informational, recreational, relational, and work-related app use related to mobilecultural participation, respectively?



More intensive use of mobile devices was associated with users’ innovativeness(Zhong, 2013). The intensity of mobile communication (e.g. the number of voice callsand text messages exchanged) was positively related to attending social leisure activi-ties (Campbell & Kwak, 2010a; Chen et al., 2012). However, the literature has been lessconclusive on the relationships between the intensity of mobile communication andvoluntary group involvement or civic engagement (Campbell & Kwak, 2010a; Chenet al., 2012). Thus,

RQ2: Is the intensity of app use related to mobile cultural participation?

In-person cultural participationA survey of cultural organizations in the United States showed that more than onefifth of cultural organizations were concerned that mediated cultural participationwould decrease in-person participation (Thomson et al., 2013). Indeed, the adop-tion of the Internet has generated similar concerns and debates on whether virtualinteraction would draw people away from face-to-face interaction. The literature oncross-platform media use has demonstrated that people who consume more contentvia one platform often consume more content via other platforms as well (Chen, Funk,Straubhaar, & Spence, 2013; Jennings & Zeitner, 2003).

Users often simultaneously or sequentially deploy multiple modes of commu-nication across platforms to accomplish instrumental or expressive goals such asinformation search (Dutta-Bergman, 2005), relationship maintenance (Hampton &Ling, 2013; Haythornthwaite & Wellman, 1998), or civic participation (Vitak et al.,2011). Thus, active cultural participants in one realm are likely to be active in otherrealms too.

H3: In-person and mobile cultural participation are positively related.

SociodemographicsPeople with privileged class backgrounds, who are better educated, women, urbanand suburban residents, and older people are more active cultural participants(National Institutes of Health, 2012). Both in-person and mediated cultural par-ticipation (e.g., watching TV arts programs) increase with education (DiMaggio& Ostrower, 1990; National Endowment for the Arts, 2013). Early studies showedthat although African Americans had less visual or performing arts attendance thanWhites, there was no significant Black–White gap in mediated cultural participationvia watching TV arts programs (DiMaggio & Ostrower, 1990). More recent researchrevealed that compared with Whites, African Americans and Hispanics were morelikely to participate in the arts through electronic media alone (National Endowmentfor the Arts, 2010, 2011).

The access to and use of mobile Internet devices also vary by sociodemographiccharacteristics (Duggan & Rainie, 2012). Young people lead old people in the breadthand depth of mobile phone use (Smith, 2011). Those who are better educated, men,urban, and suburban residents are more apt to use smartphones (Park, Kim, Shon, &Shim, 2013). Young people, those who are better educated, African Americans and



Hispanics remain more likely to use the mobile Internet and download apps (Duggan& Rainie, 2012; Purcell, 2011). A privileged class background and better education arerelated to Internet activities that may help users to gain cultural capital (Hargittai &Hinnant, 2008). As the literature is thin on mobile cultural participation, a researchquestion is formulated:

RQ3: Does mobile cultural participation vary by age, gender, race, education, andcommunity types?

Mobilization or normalizationThe mobilization thesis (Norris, 2001; Norris & Inglehart, 2009) argues that newcommunication technologies reduce cost for information, communication, andcoordination, and thus create more opportunities for social inclusion. Previouslyunavailable technologies are especially powerful in mobilizing members of under-privileged or underrepresented groups who lack socioeconomic or psychologicalresources. For instance, age and gender gap in political participation became nar-rowed online (Jensen, Danziger, & Venkatesh, 2007). The positive implicationsof social media use for civic engagement are stronger among previously inactiveindividuals (Kim, Hsu, & de Zúñiga, 2013).

Mobile technologies have been considered as a more accessible venue for nar-rowing the digital divides than PCs and the PC-based Internet (Chen & Ling,forthcoming; Donner, 2008). For instance, although racial minorities have been leftbehind in terms of fixed Internet access, African Americans and Hispanics lead otherracial groups in terms of using a greater number of mobile phone functions (Hargittai& Kim, 2010), owning smartphones (Smith, 2013), or using apps to communicate(Purcell, 2011). Supporting the mobilization thesis, age, race and socioeconomicstatus (SES) gaps in offline and Internet donation are narrowed or even disappearedin mobile donation (Chen & Givens, 2013).

By contrast, the Matthew effect, first proposed by Merton (1968), captures the pro-cess of accumulative (dis)advantages. Lacking skills or resources, members of unpriv-ileged groups are less able to take advantage of new technologies (DiMaggio & Garip,2012; DiMaggio et al., 2001). Accordingly, the normalization thesis has argued that theInternet implications are contingent on users’ pre-existing characteristics and incli-nations as technologies tend to stimulate more activities from those who have beenalready active (Hirzalla et al., 2011). One study showed that using mobile Internetdevices did not narrow gaps in online civic participation in disadvantaged communi-ties (Mossberger, Tolbert, & Hamilton, 2012).

Following the mobilization thesis, significant sociodemographic gaps in in-personcultural participation may become narrowed or reversed in mobile cultural participa-tion. Following the normalization thesis, such gaps would remain or become wider.Moreover, both would predict interaction effects as sociodemographic characteristicsmay moderate the relationships between mobile usage patterns, in-person and mobilecultural participation. The mobilization thesis would predict that these relationshipsare stronger among members of disadvantaged groups as mobile technologies offer



them previously unavailable venues for cultural participation. By contrast, the nor-malization thesis would predict that such relationships are weaker among membersof disadvantaged groups as the advantaged are better positioned to utilize new tech-nologies for mediated cultural participation (Selwyn, 2004). Thus,

RQ4: Do sociodemographic characteristics moderate the relationships between the accessto mobile Internet devices, app use, and mobile cultural participation?

RQ5: Do sociodemographic characteristics moderate the relationship between in-personand mobile cultural participation?

Data

This research drew on a national random sample survey in the United States con-ducted by the Pew Internet & American Life Project from July 25 to August 26 in 2011.The survey used a combination of landline and cellular random digit dial (RDD) sam-ples of adults in continental America who had access to a landline or mobile phone.The sample included 2260 adults, among which 1948 were mobile phone users, 1047Internet and social networking sites (SNSs) users and 658 app downloaders.1 Theresponse rate was 13% for the landline and 11% for the mobile sample. To increasegeneralizability, data were weighted in a two-stage procedure (for details, see Purcell,2011). Missing value analysis suggested no systematic pattern of missing data. Hart-man’s single-factor test and confirmatory factor analysis were conducted to test thepresence of common method bias, and results suggested that it was not a concern.After listwise deletion of cases with missing values on variables of interest, the anal-ysis sample included 1746 respondents, among which were 912 Internet and SNSsusers and 573 app downloaders.2

Measures

In-person and mobile cultural participationAdapted from established studies (DiMaggio & Mukhtar, 2004; Lizardo, 2006),in-person cultural participation was a count variable (M = 2.13, SD= 1.76), mea-sured by the sum of five binary items on whether during the last 12 months, arespondent had (1) visited a museum, (2) visited an art gallery, show, or exhibit, (3)attended a live music, dance, or theater performance, (4) attended an arts, craft, ormusic festival, or (5) visited an historic site, park, or monument.

Mobile cultural participation was a count variable measured by the sum of fivebinary items on whether the respondent had “ever used a HANDHELD or MOBILE[capitalization in original] device, such as a cell phone, e-reader or tablet computer,to (1) download or listen to an audio tour at a museum, art gallery, or historic site,(2) view or download information or images from a museum, (3) view or downloadinformation or images from a historic site, park or monument, (4) view or down-load visual arts content, such as painting, sculpture, graphic design or photography,or (5) watch or download a music, dance or theatre performance?” (Pew Internet &American Life Project, 2011, p. 23). Only 8% of respondents reported three to five



types of mobile cultural participation. The variable was recoded into a 0- to 3-pointscale where 3 meant three to five types of mobile cultural participation (M = 0.59,SD= 0.95). About two-thirds of respondents were engaged in in-person and 27% inmobile cultural participation.

Access to mobile Internet devices and app usage patternsThe access to mobile Internet devices was measured by the sum of three binary items:whether the respondent had (1) a smartphone, (2) a tablet computer, or (3) an elec-tronic book device or e-Book reader (M = 0.71, SD= 0.78). Respondents were askedhow many apps they used at least weekly on their mobile phones and tablets, respec-tively. The intensity of app use was the sum of the two items, recoded into a 1- to6-point scale (1= 0 to 6=more than 20, M = 3.73, SD= 1.52).

The diversity of app use was measured by the sum of 11 binary items on whetherthe respondents had downloaded a variety of apps that helped them get more infor-mation about (1) an event they were attending, (2) a destination they were visiting,(3) provided regular updates on news, weather, sports or stocks, helped them (4) learnabout something in which they were interested, (5) shop or make purchases, (6) trackor manage their health, (7) watch movies or TV shows online, as well as apps that (8)used for or with children, (9) with work-related tasks, (10) helped them communicatewith friends or family, and (11) paid apps (M = 5.55, SD= 2.78).

Moreover, the 11 items were further categorized in four specific types of app use.Informational app use was coded as 1 if a respondent had downloaded at least one typeof apps from categories 1–3 listed above and 0 otherwise. Recreational app use wascoded as 1 if a respondent had downloaded at least one type of apps from categories4–8 listed above and 0 otherwise. Work-related app use was coded as 1 if a respon-dent had downloaded apps that helped them with work-related tasks and 0 otherwise.Relational app use was coded as 1 if a respondent had downloaded apps that helpedthem communicate with friends or family and 0 otherwise. Among app downloaders,85% had downloaded recreational, 83% informational, 72% work-related, and 49%relational apps.

User characteristicsRespondents’ mean age was 43. Gender was coded as 1 if female and 0 male, and 51%of the respondents were women. Education was measured by a 1- to 6-point scale(1= less than high school to 6= postgraduate, M = 3.45, SD= 1.60). Race had fivecategories: White (69%), African Americans (12%), Hispanics (13%), Asians (3%),and other racial groups (3%). Community type had three categories: urban (32%),suburban (50%), and rural (18%).

Control: Internet user, Internet activity, SNSs use, and additional sociodemographicsInternet user was coded as 1 if a respondent accessed the fixed Internet or sent orreceived emails at least occasionally and 0 otherwise, following the definition of Inter-net user by the Pew Internet & American Life Project (2011). About 85% of the respon-dents were Internet users. Internet users were asked four binary items on whether they



had used the Internet to (1) send or read e-mail; (2) look online for news or infor-mation about politics; or (3) use a SNS like Myspace, Facebook or LinkedIn; or (4)use Twitter. Internet activity was measured by the sum of these four items (M = 2.78,SD= 0.68).

The frequency of SNSs use was measured by 1- to 6-point scale (1= less oftento 6= several times a day, M = 4.39, SD= 1.57). Partnered was coded as 1 if mar-ried or living with a partner and 0 otherwise. Parent with children under 18 wascoded as 1 if a respondent was a parent or guardian of any children under 18 livingin the same household. A total of 55% respondents were partnered and 34% parentswith young children. Interaction terms were constructed and continuous variablesinvolved in interaction terms were mean centered to avoid multicollinearity. Onlysignificant interaction effects were reported.3

Results

Poisson or negative binomial regression models are often used for count variables.The latter would be more appropriate than the former for overdispersed data (whenthe variance is much larger than the mean), as indicated by the likelihood ratio test ofthe overdispersion parameter. On top of the standard Poisson and negative binomialmodels, zero-inflated models would be more appropriate for count variables with anexcess of zero counts as indicated by the Vuong test (Vuong, 1989). The zero-inflatedmodel assumes two regimes in a population: Members in the first regime alwayshave zero count and members in the second regime can have zero or positive counts.Accordingly, it first uses a logit model to estimate a respondent’s membership in thefirst regime and then a Poisson or negative binomial model to estimate the countfor respondents in the second regime (Long & Freese, 2006). The Stata commandcountfit can be used for choosing the most appropriate model.

In this analysis, 66% of respondents reported zero mobile cultural participationand 27% reported zero in-person cultural participation. The vuong tests and the like-lihood ratio test of the overdispersion parameter suggested the zero-inflated Poisson(ZIP) model as the most appropriate. It first used a logit model to estimate the likeli-hood of a respondent’s membership in the “certain zero” group that always reportedzero in-person or mobile cultural participation, respectively. Then, it used the Poissonmodel to estimate the counts of in-person or mobile cultural participation, respec-tively (Tables 1 and 2). Poisson model was the most appropriate when the analyticalsample was narrowed down to app downloaders (Table 3).

Baseline modelTable 1 reported the results of ZIP models estimating the relationships betweensociodemographic characteristics, in-person cultural participation (Models 1 and 2),and mobile cultural participation (Models 3 and 4), respectively. Although Models 1and 3 included only sociodemographic variables, Models 2 and 4 took into accountwhether in-person and mobile cultural participation were related. Consistent with



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existing studies, Model 1 reported that in-person cultural participation decreasedwith age and increased with education. There was a significant gap in in-personcultural participation by family status or community type: Urban and suburbanresidents were more active than rural residents, and partnered people were moreactive, while parents with children under 18 were less active in-person culturalparticipants.

Model 2 showed that mobile and in-person cultural participation were positivelyrelated. Once mobile cultural participation was taken into account, African Ameri-cans and Hispanics became significantly less active in-personal cultural participantsthan Whites.

Model 3 reported that mobile cultural participation decreased with age andincreased with education. Hispanics had greater mobile cultural participation thanWhites. Yet, there was no significant gap in mobile cultural participation by familystatus or community type. Model 4 confirmed that in-person and mobile culturalparticipation was significantly related. With in-person cultural participation takeninto consideration, education became statistically nonsignificant to mobile culturalparticipation.

The access to mobile Internet devicesTable 2 reported results of ZIP models estimating the relationship between theaccess to mobile Internet devices and mobile cultural participation. Model 5 tookinto consideration whether the respondent was an Internet user, Models 6 Internetactivities and the frequency of SNSs use, and Models 7–9 the interaction effect.The number of mobile Internet devices was significantly related to mobile culturalparticipation (Models 5, 7, and 8). For instance, Model 5 indicated that mobilecultural participation would be 12% (exp[0.11]= 1.12) greater for each additionalmobile Internet device, holding other variables constant. When Internet activity andSNSs use were included, the access to mobile Internet devices became statisticallynonsignificant (Models 6 and 9). In-person cultural participation was positivelyrelated to mobile cultural participation throughout the models. For instance, Model5 showed that mobile cultural participation would be 32% (exp[0.28]= 1.32) greaterfor each unit increase of in-person cultural participation, holding other variablesconstant. Hispanics were significantly more active mobile cultural participants thanWhites throughout the models. Model 5 reported that Hispanics’ mobile culturalparticipation would be 48% (exp[0.39]= 1.48) greater than that of Whites, holdingother variables constant. Mobile cultural participation decreased with age (Models 5,7, and 8), which, however, was statistically nonsignificant when Internet activity andSNSs use were included (Models 6 and 9).

Model 7 reported a significant interaction indicating that the relationship betweenmobile Internet devices and mobile cultural participation was weaker among thebetter educated (b=−0.08, p< .01). Model 8 revealed an interaction indicating thatthe relationship between in-person and mobile cultural participation was weakeramong the better educated (b=−0.12, p< .05). Model 9 showed that this interaction



effect remained significant when Internet activity and SNSs use were included. Inaddition, Internet users had greater mobile cultural participation than nonusers(Models 5 and 8). Greater Internet activity—rather than frequent SNSs use—wassignificantly related to mobile cultural participation (Models 6 and 9).

App usage patternsTables 3 reported results of Poisson models estimating the relationship between appuse and mobile cultural participation. Models 10 and 12 took into account the inten-sity and diversity of app use, while Models 11 and 13 focused on specific types of appuse. Models 10 and 12 showed that diverse–but not intensive—app use was signif-icantly related to greater mobile cultural participation. Mobile cultural participationwould be 13% (exp[0.12]= 1.13) greater for each unit increase in the diversity of appuse, holding other variables constant (Model 10).

Model 11 showed that all of the four specific types of app use—informational,recreational, relational, and work-related—were positively related to mobile culturalparticipation. However, when Internet activities and SNSs use were included, onlyrecreational and work-related app use remained statistically significant. In Model 13,respondents who downloaded recreational apps would have 118% (exp[0.78]= 2.18)more mobile cultural participation than those who did not download such apps.Respondents who downloaded work-related apps would have 28% (exp[0.25]= 1.28)more mobile cultural participation than those who did not download such apps,holding other variables constant.

Throughout Models 10–13, education was negatively related to mobile cul-tural participation. For instance, mobile cultural participation would be 8% less(exp[−0.08]= 0.92) for each unit increase in education, holding other variablesconstant (Model 10). Hispanics and people of other races were significantly moreactive in mobile cultural participants than Whites. Internet use, Internet activity, andSNSs use were not statistically significant to mobile cultural participation when appuse was taken into account.

SummaryH1 was partially supported as greater access to mobile Internet devices was relatedto greater mobile cultural participation. However, when Internet and mobile usagepatterns were included, the access to mobile Internet devices lost its statistical sig-nificance. H2 was supported as diverse app use was significantly related to greatermobile cultural participation. As to RQ1, recreational and work-related app use wassignificantly related to greater mobile cultural participation. As to RQ2, the intensityof app use was not related to mobile cultural participation. H3 was supported for aconsistent, significant relation between in-person and mobile cultural participation.

As to RQ3, although the young, the better educated, and Hispanics individualswere more engaged in mobile cultural participation in the baseline model, onlyHispanics remained statistically significant when Internet and mobile usage patternswere included. Education was negatively related to mobile cultural participation



when app use was considered. Although urban and suburban residents were moreavid in-person cultural participants, there was no significant urban–rural gap inmobile cultural participation.

As to RQ4, the relationship between the access to mobile Internet devices andmobile cultural participation was stronger among the less educated, supportingthe mobilization thesis. As to RQ5, the relationship between in-person and mobilecultural participation was stronger among the less educated, further supportingthe mobilization thesis. There were no significant interaction effects supporting thenormalization thesis.

Discussion

Integrating literatures on cultural capital, digital divides, and social implicationsof mobile media and communication, this research used national survey data inthe United States to examine how mobile cultural participation varies by the accessto mobile devices, app use, user characteristics, and in-person cultural participa-tion. It has advanced the existing literatures by focusing on the mobilization andthe normalization theses and assessing the variation of the implications of mobiletechnologies by social groups and existing practices. It reported several interestingfindings.

First, mobile technologies have opened up new venues for cultural appreciation.Greater access to mobile Internet devices and more diverse app use, especiallyrecreational and work-related app use, were associated with greater mobile culturalparticipation.

Second, as much as cultural production has incorporated physical, digital, andmobile forms, cultural participation has become multiplatform. Despite concerns ofsome cultural organizations (Thomson et al., 2013), there was no evidence that mobilecultural participation turned patrons away from in-person cultural participation.Indeed, the two were positively related.

Third, mobile cultural participation reached patrons from broader social strata.The Hispanic lead, the reversed education gap, and the disappeared gap by com-munity type in mobile cultural participation supported the mobilization thesis.Hispanics were more active mobile cultural participants than Whites. This findingis in line with existing research showing that young Hispanics were more likely touse the picture, video, and music features of their mobile phones than their Whitecounterparts (Hargittai & Kim, 2010).

The less educated were more active in mobile cultural participation when appuse was taken into account. Mobile cultural participation helped to overcome theurban–rural divide in in-person cultural participation. Allowing members of dis-advantaged groups a more accessible and affordable tool for cultural participation,mobile technologies mobilize rather than normalize cultural participation. Furthersupporting the mobilization thesis, the implications of mobile Internet devices andin-person cultural participation for mobile cultural participation were stronger



among the less educated. The results resonate with the notion that mobile technolo-gies were more practical than the PC-based Internet in promoting social inclusion(Donner, 2008).

This research has several limitations. First, the data are cross-sectional. Althoughmobile cultural participation is relatively new and would be impossible without theaccess to and the use of mobile Internet devices, longitudinal studies are needed tospecify causal directions.

Second, the measure of mobile cultural participation in the survey was centeredon using mobile devices for accessing visual and performing arts content. Futureresearch needs to pay more attention to the more interactive, participatory, andnetworked dimension of mobile cultural participation such as generating and sharingcultural-related content.

Third, although the measure of mobile cultural participation built on well-established measures of in-person cultural participation (DiMaggio & Mukhtar,2004; Lizardo, 2006), it did not take into account the concept of subgroup culturalcapital. Future studies need to consider whether mobile media technologies havedifferent implications for the participation in highbrow, middlebrow, lowbrow, andsubgroup cultures.

Fourth, the survey had no questions on voice and text message use. Althoughapps have consumed most of the time users spend on mobile Internet devices, futureresearch should include voice and text message use for a more comprehensive analysis.Future studies also need to develop more refined measures of app use. As importantly,this research focused on whether mobile technologies mobilized or normalized cul-tural participation. Future studies need to explore the mechanisms; that is, how mobiletechnologies mobilize or normalize cultural participation via mobility, relatively lowcost and low skill barriers, or the participatory and networked interactions enabledby mobile media and communication.

Despite these caveats, this research made important contributions. First, althoughcultural organizations have rapidly increased their mobile presence and engagement,few studies have shed light on mobile cultural participation, especially the extent towhich it helps to attract patrons from broader social strata and whether it distractsthem away from in-person cultural participation. This research filled this critical gap.

Second, centering on cultural implications of mobile media appropriation, thisresearch expanded an existing literature primarily focusing on the relational or civicimplications of mobile technologies (Campbell & Kwak, 2011a, 2011b; Hampton et al.,2011; Rojas & Puig-i-Abril, 2009).

Third, supporting the mobilization thesis, this research demonstrated that mobilemedia appropriation could serve as an important link in the “transubstantiation”between economic, social, and cultural capital (Bourdieu, 1986), especially for theless educated, racial minorities, rural residents, and time deprived, such as parentswith young children.

Fourth, the current investigation advanced the literature on the social implicationsof mobile apps in general and for cultural participation in specific. It offered a layered



analysis of the implications of app usage patterns. Even after the access to mobile Inter-net devices was obtained, the diversity and specific types of app use—rather than theintensity of app use—were important to mobile media appropriation.

These findings have practical implications. In a time of declining in-person cul-tural attendance, mediated cultural participation can help to revive cultural participa-tion, attracting patrons from traditionally underrepresented groups. Given the com-plementary relationship between in-person and mobile cultural participation and thebroader social strata represented by mobile cultural participants, cultural organiza-tions should further embrace and invest in their mobile presence and engagement.The significance of recreational and work-related apps suggests that such apps offergreat opportunities for promoting cultural organizations, events, and content as theirusers are more active mobile cultural participants.

At the intersection of digital and social inclusion, mobile media and commu-nication makes cultural participation a moveable feast, especially for members ofdisadvantaged groups. Future research needs to examine the extent to which the accu-mulation of cultural capital and its “transubstantiation” into other forms of capitalsvia mediated cultural participation is as effective as via in-person cultural participa-tion, especially for low SES people and racial minorities. Theoretically informed andempirically grounded, this research will hopefully inspire more studies as mobile tech-nologies enrich the ways in which culture is produced, promoted, and participated.

Notes

1 Mobile-only Internet users made a very small proportion of the sample and thus were noexamined as a specific group. Only 21 out of the 793 respondents who had used theInternet via the mobile phone reported not using the PC Internet and 33 out of the 913respondents who had mobile Internet devices reported not using the PC Internet.

2 Detailed summary statistics of variables used in the analysis are available upon request.3 An alternative scenario of nonlinear inversted U-shaped relationships between the

independent variables and the dependent variables were tested but not identified.

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(2014) A Moveable Feast: Do Mobile Media Technologies Mobilize or Normalize Cultural Participation?

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