Number Matters: The Multimodality of Internet Use as an Indicator of the Digital Inequalities

Journal of Computer-Mediated Communication

Number Matters: The Multimodality of InternetUse as an Indicator of the Digital Inequalities

Lu Wei

College of Media and International CultureZhejiang University

This study explores the multimodality of Internet use as a critical indicator of digital inequalities.Rather than relying on traditional measures of user/nonuser and information/entertainment uses,this study focuses on a broad scope of online activities and investigates them collectively. Results showthat the more modes of Internet activities people are engaged in, the more advanced uses they will addto their online behaviors. Female, older, poorer, and less educated only use the Internet for very limitedbasic applications, which are associated with fewer political communication and participation. Whileprevious research concludes that the type of Internet activities matters, this study suggests that it is thenumber of types that matters in examining potential inequalities and their social consequences.

Key words: Multimodality, digital divide, digital inequalities, Internet use, political participation

doi:10.1111/j.1083-6101.2012.01578.x

There has been a recent conceptual shift in the research of the digital divide. As the Internet haspenetrated most part of the world, the original access divide gradually shrinks while a new formof the digital divide, the usage gap, emerges. Some even argue that the binary term ‘‘divide’’ needto be reconsidered and modified to more appropriate constructs such as continuum, gradations, orinequalities (Gunkel, 2003; Hargittai & Hinnant, 2008; Livingstone & Helsper, 2007; Selwyn, 2004).

In support of this shifting research agenda, this study proposes the concept of multimodal Internetuse as an indicator of digital inequalities. While the term multimodality is usually used in HumanComputer Interaction (HCI) research to refer to different modes of communication according tohuman senses (e.g., body, gesture, gaze, and affective interaction), it has been adopted in many contextsand across several disciplines (Bernsen, 1994; Jaimes & Sebe, 2007). As Internet users are engagedin increasingly wider spectrum of Internet applications, this term has been used to describe the‘‘mixed-mode’’ nature of human’s Internet use (Walther & Parks, 2002).

Defined by the range or breadth of Internet activities, the multimodality of Internet use is arguably abetter gauge of usage gaps than the specific types of online activities, given the mixed findings regardingthe consequences of information and entertainment Internet uses. Since people are using the Internetin multimode, it is not enough to solely focus on certain types of Internet activities when examining thesituations and implications of the actual digital inequalities. Thus, the goal of this study is to explorethe digital inequalities by (1) describing the current situation of multimodal Internet use in Americansociety, (2) identifying the demographic factors that associated with the multimodality of Internet use,

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and (3) investigating the relationships between multimodal Internet use and political variables such aspolitical communication and participation.

From Digital Divide to Digital Inequalities

The original definition of the digital divide is a gap between those who have access to digital technologiesand those who do not (NTIA, 1998; Selwyn, 2004). This term entered public discourse at around themid-1990s. The majority of this body of literature focused on demonstrating the magnitude, interpretingthe nature, and identifying the factors of the digital divide, including age (DiMaggio et al., 2004), raceand ethnicity (Hoffman, Novak & Schlosser, 2000), education (Latimer, 2009), socio-economic status(McLaren & Zappala, 2002), geography (Sylvester & McGlynn, 2010), culture (Drori & Jang, 2003), andinternational disparities (Guillen and Suarez, 2005). All these enterprises are undertaken on the basisof an understanding that the digital divide refers to the disparity in people’s access to information andcommunication technologies, or more particularly, the Internet (Yu, 2006).

As the Internet has become increasingly widespread in the world, most scholars agree that the digitaldivide should encompass more dimensions than the simplified measure of physical access. Mossberger,Tolbert, and Stansbury (2003) claimed that to more accurately understand the digital divide, one mustreconceptualize it to include multidimensional aspects of the social inequalities in the new media age:‘‘an access divide, a skills divide, an economic opportunity divide, and a democratic divide (p. 2).’’Among these dimensions, the usage divide is of particular attention to the researchers. Attewell (2001),for example, classified the digital divide to two steps: the ‘‘first digital divide’’ that refers to the materialaccess to computers and the Internet, and the ‘‘second digital divide’’ that represents the disparitiesin computer and Internet use. Hargittai (2002) suggested a similar differentiation between access andability to use as the first-level and the ‘‘second-level digital divide.’’ More importantly, there is anongoing consensus that the actual use of the Internet is a more prevalent source of inequality than theplain access to the Internet.

Given the limitations of simple binaries of access/no-access or use/nonuse, a few researchers turnedto the types of Internet use to capture a more complex dimension of the digital divide, or a betterterm, digital inequalities. In a recent study, Hargittai and Hinnant (2008) found that those with higherlevels of education and of a more resource-rich background use the Web for more ‘‘capital-enhancing’’activities, including seeking political or government information, exploring career opportunities, andconsulting information about financial and health services. They then concluded that it is the typesof activities for which people use the Internet that matters most in examining potential divides. Forinstance, if the Internet is used as a toy rather than as a tool, it may not enhance the user’s life chances(Jung, Qiu & Kim, 2001). Such a ‘‘usage gap’’ between information and entertainment uses of theInternet, consequently, has been established as a critical divide in the literature (Bonfadelli, 2002;Hargittai & Hinnant, 2008; Livingstone & Helsper, 2007; van Dijk, 2002).

While most agree that information uses are more ‘‘legitimate’’ than entertainment uses, somehave argued that recreational use of the Internet may have beneficial consequences (Livingstone &Helsper, 2007; Sandvig, 2001). In fact, even people with highest degrees may chat or play games onthe Internet from time to time. As we try to avoid the dichotomy of technology haves vs. have-nots,we need to caution about the risk of falling into another bipolar division between particular Internetuses. Alternatively, the range or the breadth of Internet use could be a better indicator of the digitalcontinuum. By looking at the frequency of different types of opportunities taken up online, Livingstoneand Helsper (2007) found that the route to socially-valued activities (on the top of the continuum) maybest (or only) be reached through facilitating entertainment and communication online (on the bottom

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of the continuum). This suggests that the broader and more sophisticated use of Internet people areengaged in, the more benefit and opportunities they will acquire to meet individual and social goals.This study, therefore, conceptualizes the multimodality of people’s Internet use as an indicator of thedigital inequalities.

Multimodal Internet use and its correlates

Multimodality is an inherent but overlooked feature of the Internet. The ‘‘technocentric’’ focus (Parks,2009) of earlier new media research keeps scholarly attention on chasing ‘‘the next big thing.’’ In treatingthe Internet as new, as Baym (2009) noted, ‘‘we have tended to view them as isolated phenomena(p.721).’’ Not only was the online world considered separated from the offline world, what happens inone online environment seemed to stay within its own borders. Previous studies of single applicationshave indeed generated valuable knowledge about what happens within each context, but we know littleabout how these contexts are linked to one another and how multiple use of the Internet is influencedby and influencing people’s everyday life.

Many have already observed that human’s Internet use has become increasingly multimodal or‘‘mixed-mode’’ (Walther & Parks, 2002). It is common that students check their email, log on to theirFacebook, write on Twitter, chat on MSN, share a video on YouTube, post a picture on Flickr, and read astory on Digg, while the professor is lecturing in the class. Increasing numbers of people simultaneouslyintegrate multiple media into their daily communicative experience. The multimodal nature of sociallife in the age of traditional media, such as the telegraph (Standage, 1998), telephone (Fischer, 1992)and postal mail (Baron, 2000; Danet, 2001), is intensified and complexified by the Internet (Baym,Zhang & Lin, 2004; Haythornthwaite, 2005). Some report that users tend to employ additional modesto communicate with those whom they first met through one particular mode of computer-mediatedcommunication (CMC) (Parks & Floyd, 1996). As different modes of CMC have different featuresand thus different effects on online interactions and relationships (Herring, 2002; Ledbetter, 2008; Xie,2008), it is vital to scrutinize not only the individual but the collective effects of multimodal Internetuse (Xie, 2008).

Existing literature, however, focuses on the background and effects of specific types of Internetuse rather than the multimodality of CMC. For instance, Howard, Rainie and Jones (2001) foundthat education is positively associated with certain types of Internet use, such as sending e-mail,searching for financial, political, or government information, and banking online. Madden (2003)discovered that users with higher education and household income are less likely to download musicor use instant messaging, but more likely to use the Internet for news, work, travel arrangementand product information. Extending the knowledge gap hypothesis from knowledge possession toknowledge production, Wei (2009) revealed that users with higher socioeconomic status (SES) tend touse the tool of blog in a more informational way, contribute more political knowledge in the form offilter blogs, and have stronger social influence than do lower status segments.

With regard to the consequences of Internet use, past research is also dominated by the examinationof information vs. entertainment uses. Consistent with the findings for traditional media such asnewspapers (Newton, 1999) and television (Prior, 2005; Putnam, 2000), most studies reported that theinformational uses of the Internet are positively associated with political knowledge, participation, andthe production of social capital in general, which is depleted by entertainment uses of the Internet(Drew & Weaver, 2006; Kim, 2008; Shah et al., 2005).

Few studies empirically examined the antecedents and consequences of the multimodal Internetuse as a unique construct. Being aware of this gap in the literature, Livingstone and Helsper (2007) have


done some explorations on the inequalities in people’s multimodal Internet use. Measuring the breadthof online activities by the number of opportunities taken up by the users, they found that not only age,gender and SES, but also the amount of use and online expertise all contribute to the variations in themultimodality of Internet use. Nevertheless, their sample was limited to children and young people inthe UK, and they did not look into the consequences of multimodal Internet use. Thus, this researchattempts to answer the following questions with a national representative sample in the US:

(1) What is the current situation of multimodal Internet use in American society?(2) How to explain the variation in the multimodal Internet use?(3) What are the relationships between multimodal Internet use and political variables such as political

communication and participation?

Method

Data in this study come from a random-digit telephone survey conducted by the Pew Internet &American Life project entitled ‘‘Civic Engagement Survey’’ between August 12, 2008 and August 31,2008. A nationally-representative sample of 2,251 adults, age 18 and older, was interviewed. The marginof error for this sample is +/−2%.

Following Livingstone and Helsper (2007), the multimodality of Internet use was measured by thenumber of activities users are involved in. Eleven questions asked whether respondents ever use theInternet to do any of the following things, including email, news, political or campaign information,blog, Twitter, social networking sites, reservation, etc. If the answer was ‘‘Yes,’’ it was coded as 1. If‘‘No,’’ zero. An index of the multimodality of Internet use (M = 3.64, SD = 2.86, alpha = .70) wascreated by summing the scores of all these items.

Eight items were employed to measure user’s political communication. Respondents were asked,how often have they received information asking them to, and sent information to others to ask themto, get involved in a political activity, by the forms of email, phone, letter, and in person? The internalconsistency of this index is .73 (M = 2.75, SD = 1.64).

Political participation also was measured by eight dichotomous questions. Respondents were askedif they have attended a political rally or speech, an organized protest of any kind, a political meetingon local, town or school affairs, if they have worked or volunteered for a political party or candidate,made a speech about a community or political issue, been an active member of any group that tries toinfluence public policy or government, participated in a walk, run or ride for a cause, and worked withfellow citizens to solve a problem in their community. All eight items were summed to create an indexof political participation (M = 1.19, SD = 1.60), with an alpha of .72.

Suggested by previous studies (see Delli Carpini & Keeter, 1996; Eveland & Scheufele, 2000; McLeod,Scheufele, & Moy, 1999; Scheufele, 2002), several demographic variables and political variables play arole in influencing the relationship of media use and political outcomes. These demographic variablesinclude sex (dummy-coded male, male = 49%), race (dummy-coded white, white = 72%), education(a 1-4-point scale from less than high school to college and above; M = 2.65, SD = 1.02), income (a1-9-point scale representing 9 ranges of percentiles from the lowest [less than 10] to the highest [150 ormore]; M = 5.04, SD = 2.40), and age (a 1-6-point scale representing 6 ranges of percentiles from theyoungest [18-24] to the oldest [65 and above]; M = 3.64, SD = 1.60). Political variables include politicalpartisanship and orientation. For Democrat-Republican partisanship, respondents were asked if theyconsider themselves a Republican, Democrat or Independent on a 1-3-point scale from Democrat toindependent to Republican (M = 1.74, SD = .94). For Democrat-Republican orientation, respondentswere asked if they lean more to the Republican Party or more to the Democratic Party on a 1-3-point


scale from lean more to the Democratic Party to independent to lean more to the Republican Party(M = 1.65, SD = 1.02).

A number of studies found that the frequency of general Internet use is associated with politicalparticipation (Krueger, 2002; Norris, 2001; Quintelier & Vissers, 2008; Shah, et al., 2005). It was thusincluded in the model as a control variable to describe how often people use the Internet in general,not for any specific activities (a 1-3-point scale from less often/never to several times a week todaily; M = 1.95, SD = 1.26). Moreover, political discussion (a 1-5-point scale from never to everyday; M = 3.25, SD = 1.42) was controlled as well because it was found to be a significant correlateof political participation by numerous studies (Eveland & Hively, 2009; Quintelier & Vissers, 2008;Scheufele, 2002; Shah, et al., 2005; Sotirovic & McLeod, 2001).

Results

The first research question asked about the current situation of multimodal Internet use in Americansociety. Crosstabs in Table 1 show that all sociodemographic characteristics matter except race.Specifically, men are engaged in a little more types of Internet activities than women. The number ofactivities increases when the levels of education and income advance. It needs at least some collegeeducation and a family income of over 40k to go beyond the average multimodality of Internet use.

Table 1 Multimodality of Internet use, by demographics

Average Multimodality F Sig.

Male 3.81 20.63 .000Female 3.48

}

White 3.63 .33 .567Color 3.58LT HS 1.36 597.54 .000HS GRAD 2.81SOME COLL 4.28COLLEGE+ 5.34

⎫⎪⎬⎪⎭

18-24 5.25 291.90 .00025-34 4.9735-44 4.3245-54 3.4755-64 3.1265+ 1.42

⎫⎪⎪⎪⎪⎪⎪⎬⎪⎪⎪⎪⎪⎪⎭

LT 10k 2.01 113.5410k-under 20k 2.5820k-under30k 2.8730k-under 40k 3.3040k-under 50k 4.11 .00050k-under 75k 4.8375k-under 100k 4.50100k-under 150k 5.22150k+ 5.45

⎫⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎬⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎭

Overall average 3.64


Table 2 Type of Internet activities, by the number of activities engaged in (%)

Number of Internet Activities

1 2 3 4 5 6 7 8 9 10 11

Email 69.8 84.7 92.9 93.6 97.5 99.3 98.4 100 100 100 100News 11.4 28.0 63.2 76.7 90.3 89.0 96.8 98.1 100 100 100Travel service 8.2 39.5 50.7 65.2 76.3 84.6 84.6 92.9 98.9 92.6 100DIY info 8.6 19.9 41.1 53.9 66.1 79.1 78.2 81.4 95.0 100 100Politics 1.2 7.9 20.7 47.9 70.1 75.2 89.4 90.4 100 88.9 100Search people .8 7.5 17.0 26.0 33.9 57.8 85.6 90.7 90 100 100Read blog .0 1.6 4.6 15.8 27.8 52.2 75.6 93.1 93.9 94.5 100SNS .0 6.7 9.1 15.7 29.4 39.4 59.6 81.7 93.4 100 100Write blog .0 .8 1.3 2.1 4.2 13.4 19.1 42.6 76.7 100 100Twitter .0 1.9 .0 .5 2.1 5.8 8.8 16.3 36.2 92.6 100Dating .0 1.6 .2 3.4 3.1 4.4 4.4 13.4 16.1 29.6 100% of N 3.9 5.9 8.7 12.2 13.8 11.0 8.0 5.8 2.9 .9 .1

Note. The shading indicates those activities engaged in by more than 50% in the relevant column.

In contrast, the older the age, the fewer modes of Internet use people reported. Those aged 45 andolder have a number of Internet activities below the average. Overall, the average number of Internetactivities engaged in by Americans is around three out of eleven surveyed by this study. Therefore, thecurrent level of American people’s multimodal Internet use is still very low.

Consistent with Livingstone and Helsper’s (2007) findings, going online is a progression withsystematic differences between those who engage in more and those who engage in fewer Internetactivities. Table 2 demonstrates an orderly relationship between the number and the type of Internetactivities. It maps a continuum in the multimodality of Internet use. The shaded area indicates activitiesengaged in by at least half of the respondents.

Generally, the number is associated with the type in an interesting but intuitive manner. First, thereare certain types of activities for a certain number. When people engage in a specific number of activities,the majority of the users are concentrated to some specific activities. For instance, if people have onlythree types of daily Internet activities, they usually use e-mail, read news, and get travel information.

Second, as the number increases, more advanced types of activities emerge. In other words, themore modes of Internet activities people are engaged in, the more sophisticated as well as participatoryuses they will add to their online behaviors. For example, if people’s daily Internet activities increasesfrom three to five, they will include DIY information and politics to the three basic uses. Also, if onehas some advanced Internet activities such as writing blog and using Twitter, he or she is most likely toundertake other less advanced activities as well. In short, those basic users usually focus on e-mail andnews functions of the Web, whereas all-round users tend to utilize the Internet in a greater breadth.

A combination of Table 1 and 2 helps reveal some structural inequalities in people’s multimodalInternet use. Users of different sociodemographic backgrounds tend to have different number ofInternet activities. And as the number is related to the type, such differences in number may translate todisparities in type. Specifically, female, older, poorer, and less educated tend to engage in fewer Internetactivities that are usually basic applications.

In addition, a crosstab analysis of Internet activities by demographics may further illustrate the usepatterns of diverse social groups (see Figure 1-4). According to Figure 1, the gender gap of Internet


Note. The values on the vertical axis are percentages.

Figure 1 Internet actitivies, by gender


use is most evident in politics with men participating in more online political activities than women.Figure 2 shows that, users with low and high education differ the most in the Internet activities ofpolitics, reading and writing blog, and twitter. The patterns in Figure 3 and 4 demonstrate the greatestgaps in the use of Social Networking Sites (SNS), blog writing and Twitter, among those with differentage and income. Coincidentally, all these activities are located at the higher level of the multimodalityladder in Table 2. Compared to other uses, they are more advanced and participatory Internet activitiesthat could be more socially beneficial.

How to explain this variation in the multimodal Internet use? Regression results in Table 3, firstcolumn, reveal that the number of modes is associated with more frequent general Internet use, ayounger age, more political talk, a higher education and income. Consistent with the crosstabs, there


Figure 2 Internet activities, by education




Figure 3 Internet activities, by age



Figure 4 Internet activities, by income


is no significant relationship between race and the multimodality of Internet use. Political identityand orientation do not have significant relationships with multimodality either. The model explains63.6 percent of the variance in multimodal Internet use.

The final question of this research is regarding the political consequences of multimodal Internetuse, such as political communication and participation. To isolate the influence of multimodality,hierarchical regression analyses were performed with demographics, political talk, and Internet useentered as a control block, followed by multimodal Internet use and political communication as separateblocks. The findings were presented in the other two columns of Table 3. Results show that the variationin multimodal Internet use is strongly associated with user’s political communication, which in turn


Table 3 Regression predicting multimodality of Internet use, political communication, and politicalparticipation

Multimodality Political communication Political participation

Sex-male −.01 −.01 .03Age −.18∗∗∗ .08∗∗ .05∗

Education .06∗∗ .04 .08∗∗

Race-white −.00 −.01 −.01Income .06∗∗∗ −.11∗∗∗ .12∗∗∗

Dem-Rep −.01 .10∗∗∗ .04Dem-Rep lean .01 −.03 −.00Political talk .16∗∗∗ .27∗∗∗ .10∗∗∗

Internet use .61∗∗∗ −.07 −.08∗

R2change (%) 63.6 16.3 16.6Multimodality .30∗∗∗ .23∗∗∗

R2change (%) 3.3 3.5Political comm .26∗∗∗

R2change (%) 5.5Final R2(%) 63.6 19.6 25.6

Note. ∗p < .05. ∗∗p < .01. ∗∗∗p < .001.

has a robust correlation with political participation, controlling all other variables. Multimodality isalso directly and positively associated with political participation, after control. Multimodal Internetuse contributes 3.3 percent and 3.5 percent of the variance in political communication and politicalparticipation respectively.

Discussion

This study explores the multimodality of Internet use as a critical indicator of the digital divide, or abetter term, digital inequalities. It operationalizes multimodality in the number of Internet activitiesand investigates its current situations and correlates in American society. Three key findings will havesome important theoretical and practical implications.

First of all, this research maps an intriguing pattern of multimodal Internet use. The datareveal a progression from basic single use to full range utilizations with some advanced applications.Coincidentally, the staged process illustrated in Table 2 parallels with an upward direction from Web1.0 uses such as Email, news and information, to Web 2.0 applications including social networking sites,blogs and Twitter. This is exactly the evolution trajectory of Internet technology and it characterizes therelationship between the number and the nature of Internet activities. Therefore, among the generalpopulation, the number of Internet activities means a lot regarding what types of activities peopleare engaged in. If one have only a couple of daily Internet uses, it is very likely that those uses areabout handling e-mail and getting news. In contrast, if one is involved in a significant number ofInternet activities, some more participatory (Jenkins, 2007) and thus capital-enhancing actions are thenincluded. As such, we should probably not have too much concern about the recreational use of theInternet, because generally nobody can avoid it. However, we do need to pay close attention to howmany opportunities people take up on the Internet.


Second, the association between multimodal Internet use and sociodemographics warns that thedigital inequalities persist. Consistent with the central factor of the digital divide, those who have ahigher SES tend to take up more opportunities when going online and have more sophisticated andcomprehensive use of the Internet than do those lower status segments. It is not a problem that theunderprivileged use the Internet for amusement and communication. Everybody does. The problemis that they might have nothing beyond that. It seems that now most people are using the Internet,sometimes even doing the same things. But a new form of inequalities, a more concealed one, isrooted beneath the widespread Internet access. That is, the formerly technology haves maintain theiradvantage and become more multimodal Internet users than those formerly technology have-nots. AsLuders (2008) stated, a potential national and international digital divide is concerned with unequalmultimodal skills to work with multimodal Internet applications. The lack of access to technological,social, and economic resources prevents those information-poor from taking a comprehensive andproductive part in a convergent new media society. As the offline routes to various social resourcesgradually transfer to online, such a structural inequality in multimodal Internet use will become a majorthreat to people’s digital inclusion.

Besides SES, the age gap on the Internet goes on. In line with findings from Loges and Jung (2001),seniors are pursuing a significantly narrower scope of goals and activities online than younger people.Although Livingstone and Helsper (2007) found that opportunity take-up increases with age amongthe 9- to 19-year-olds, this study clearly reports a negative relationship between age and the number ofInternet activities among users aged 18 and over. An interpretation is that, within the 9-19-year-oldscohort, mature ones tend to have more skills and expertise than do kids; but overall, the young cohortengages in more activities than do older cohorts, which is consistent with the well documented claimthat young people are ‘‘the Internet generation’’ (Facer & Furlong, 2001) and the most connected agegroup (Loges & Jung, 2001).

Cody et al. (1999) envisioned the benefit of Internet engagement to seniors about a decade ago:

Training adult learners is important because of the increasing numbers of this segment of thepopulation and because providing Internet access to this group theoretically provides a number ofsignificant benefits including the ability to enroll in distance learning courses on-line for life-longeducation, increased knowledge of news, current events, and medical/health breakthroughs,increased connectivity with family members who may live far away, increased intergenerationalcommunication, increased perceptions of social support, and the ability to feel mentally alert,challenged, useful and to feel ‘‘younger’’ (pp. 269-270).

Unfortunately, findings from this study depict a harsh reality that older people engage in a farnarrower range of Internet activities. The social uses such as SNS, blog writing and Twitter have notbeen well integrated to senior’s Internet use. This might result in a state of social exclusion ratherthan inclusion. Of course, older people choose this lower level of multimodality for some reasons,like their concerns about privacy (Lenhart et al., 2000). Whatever good reasons they have, however,when ‘‘people transfer more and more of politics, commerce, education, and recreation to the Internetwithout contemplating the consequences of that change for people who . . . prefer not to rely on thatmedium for those purposes (Loges & Jung, 2001, p. 559),’’ seniors’ Internet use pattern is no longertheir own personal issue.

The third and the most important finding of this study is that multimodal Internet use is associatedwith people’s political communication and participation. This lends support to the underlyingassumption of this research: Number matters.


On the one hand, it validates the exciting potential of the Internet to revive the democratic publicsphere. A public, according to Habermas (1962) and Dewey (1927), exists as a discursive interactionalprocess. ‘‘Atomized individuals, consuming media in their homes,’’ as Peter Dahlgren (2005, p.149) putit, ‘‘do not comprise a public.’’ When people’s multiple Internet activities facilitate their communicativeexchange with fellow citizens, the Internet becomes a powerful communication tool that is able to ‘‘openthe first truly boundless space of communication (Trenz, 2009, p.34).’’ Moreover, the Internet hassignificantly increased the possibility for individual citizens to participate actively in public discourse(Gripsrud, 2009), and has fostered what Henry Jenkins (2007) called a ‘‘participatory media culture’’.Jenkins defined it as ‘‘a culture with relatively low barriers to artistic expression and civic engagement,strong support for creating and sharing one’s creations, and some type of informal mentorship wherebywhat is known by the most experienced is passed along to novices’’ (p.3). This is exactly the new culturalform promoted by a variety of advanced Internet functions, mostly Web 2.0 applications, as opposedto the read-only culture that characterizes Web 1.0 era. Unlimited amount of user-generated content(UGC) produced everyday through blog, Twitter, and SNS has transformed media audiences fromcontent consumers to content producers. As Yochai Benkler have put it:

The network allows all citizens to change their relationship to the public sphere. They no longerneed to be consumers and passive spectators. They can become creators and primary subjects. It isin this sense that the Internet democratizes. (Benkler 2006, 272)

The greater multimodality of Internet use, according to the results reported here, the more advancedand participatory Internet applications users will engage in, and then the more political participationpeople will have. More importantly, this participatory culture in the virtual world has been extendedto the real world. Users’ participatory activities online, as indicated by this study, have a significantrelationship with their offline engagement.

On the other hand, however, the current situation of Americans’ multimodal Internet use does not,at least so far, afford these enthusiastic celebrations of the Internet. Given the low level of multimodalInternet use (a mean score of 3.64 out of 11) and the associated low level of political participation (amean score of 1.19 out of 8), it alarms that such an optimistic description outlined above is far from areal picture. Admittedly, with 24 hours in a day, and an ever-booming number of Internet applicationsthat can be accessed almost at any place and on any platform, it is not surprising that people only use arelatively low number of them and restrict the set to mostly traditional Web 1.0 applications. But as thenumber of Internet activities links to people’s political participation that is encouraged in a democraticsociety, such low level of multimodality should not be overlooked.

Further, the already low levels of multimodality are unevenly distributed among the population,which is probably a more disturbing problem than low average level itself. Female, older, poorer, andless educated, compared to their younger and higher status counterparts, only use the Internet for verylimited basic applications, which are associated with fewer political communication and participation.Consequently, as Trenz (2009) suggested, the emancipatory potential of the Internet to unboundpolitical communication and strengthen the participatory and interactive elements of the public sphereremains quite limited. Rather than replacing the representativeness of the ‘‘refeudalized’’ national publicsphere (Habermas, 1962), the Internet continues to maintain a stage ‘‘for the representation of powerand the proclamation of decisions, not for the making of those decisions through public discussion(Gripsrud, 2009, p.7).’’

The structural inequalities that have existed since the emergence of the access divide perseverethrough the phase of usage divide. The new digital inequalities, indicated by the multimodality ofInternet use, are perhaps more difficult to bridge. The access divide would gradually fade out as


long as sufficient technological resources are provided. As the Internet has spread to the majorityof the American population, the physical digital divide has disappeared based on some of the socialdemographic criteria like gender (Ono & Zavodny, 2003; Wasserman & Richmond-Abbott, 2005). Thedisparities in Internet use, in contrast, are more strongly associated with people’s interests and skills,which in turn are more sensitive to SES (Eveland & Scheufele, 2000; Kim, 2008; Wei & Hindman, 2011;Wei & Zhang, 2008). Therefore, greater training efforts need to be made to improve people’s abilitiesand skills to involve in multiple Internet activities, particularly Web 2.0 applications. Meanwhile, goodinformation campaigns are also necessary to help citizens realize what Castells (2002) pointed outthat digital exclusion is one of the most damaging forms of exclusion in our society. We should, asWarschauer (2003) called on, ‘‘re-orient the focus from that of gaps to be overcome by provision ofequipment to that of social development to be enhanced through the effective integration of ICT intocommunities and institutions (p. 14).’’

This study has a few limitations. First, the measures of multimodal Internet use employed inthis study are not exhaustive, though they include current major applications. Future studies shouldtake into account as many Internet activities as possible to reach a more accurate description of themultimodality of Internet use. Second, due to the limits of secondary data, the frequency of andtime spent on each Internet activity are not considered. A measure consist of both breadth and depthdimensions of Internet use should generate some deeper insight into how people are engaged in multipleonline activities and what consequences such multimodal Internet use will have. Last but not the least,the direction of the relationship between multimodal Internet use and political participation is notspecified, like most studies based on cross-sectional data. Future research should establish a causalmodel between multimodal Internet use and political engagement by utilizing longitudinal data. Also,it is important to examine whether the effects of multimodal Internet use on political participation areincreasing over time, as recent meta-analysis suggested (Boulianne, 2009).

In summary, this study accentuates the multimodality of Internet use as a critical indicator of digitalinequalities. Other than relying on traditional measures of user/nonuser and information/entertainmentuses, this study focuses on a broad scope of online activities and investigates them collectively. Whileprevious research concludes that the type of Internet activities matters, this study suggests that itis the number of types, or the multimodality of Internet use that matters. Since few people usethe Internet for only one purpose, it is important to map the digital inequalities in the form ofvariation in multimodality. Although the reality is that the levels of multimodal Internet use are ratherlow and unequally distributed among different segments of the American population, the significantassociation between multimodality and political participation does represent a potential of the Internetto rejuvenate a participatory public sphere. Policy makers should shift their agenda from simpleprovision of equipment to the enrichment of citizen’s Internet use, especially among lower statussegments and senior citizens, to help enhance their life chances and social inclusion.

Acknowledgments

This research is supported by The Project-sponsored by SRF for ROCS, SEM, and by Qianjiang TalentGrant in Zhejiang Province (QJC1002004). The author would like to thank the anonymous reviewersfor their constructive comments and suggestions.

References

Attewell, P. (2001). The first and second digital divides. Sociology of Education, 74, 252–259.


Baron, N.S. (2000). Alphabet to Email: How written English evolved and where it’s heading. New York:Routledge.

Baym, N. K. (2009). A call for grounding in the face of blurred boundaries. Journal ofComputer-mediated Communication, 14(3), 720–723.

Baym, N.K., Zhang, Y.B., & Lin, M.C. (2004). Social interactions across media: Interpersonalcommunication on the Internet, telephone and face-to-face. New Media & Society, 6(3), 299–318.

Benkler, Y. (2006). The wealth of networks: How social production transforms markets and freedom. NewHaven, CT: Yale University Press.

Bernsen, N.O. (1994). Foundations of multimodal representations: A taxonomy of representationalmodalities. Interacting with Computers, 6(4), 347–371.

Bonfadelli, H. (2002). The Internet and knowledge gaps: A theoretical and empirical investigation.European Journal of Communication, 17, 65–84.

Boulianne, S. (2009). Does Internet use affect engagement? A meta-analysis of research. PoliticalCommunication, 26(2), 193–211.

Castells, M. (2002) The Internet galaxy: Reflections on the Internet, business, and society. Oxford: OxfordUniversity Press.

Cody,M. J., Dunn,D., Hoppin, S., &Wendt, P. (1999). Silver surfers: Training and evaluating Internetuse among older adult learners. Communication Education, 48, 269–286.

Dahlgren, P. (2005). The Internet, public spheres, and political communication: Dispersion anddeliberation. Political Communication, 22,147–162.

Danet, B. (2001). Cyberpl@y: Communicating online. Oxford: Berg.Delli Carpini, M. X., & Keeter, S. (1996).What Americans know about politics and why it matters. New

Haven, CT: Yale University Press.Dewey, J. (1927). The public and its problems. New York: Henry Holt.DiMaggio, P., Hargittai, E., Celeste, C., & Shafer, S. (2004). From unequal access to differentiated use:

A literature review and agenda for research on digital inequality. In K. Neckerman (Ed.), Socialinequality (pp. 355–400). New York: Russell Sage Foundation.

Drew, D., & Weaver, D. (2006). Voter learning in the 2004 presidential election: Did the media matter?Journalism & Mass Communication Quarterly, 83, 25–42.

Drori, G. S., & Jang, Y.S. (2003). The global digital divide: A sociological assessment of trends andcauses. Social Science Computer Review, 21(2), 144–161.

Eveland, W. P., Jr., & Hively, M. H. (2009). Political discussion frequency, network size, and‘‘heterogeneity’’ of discussion as predictors of political knowledge and participation. Journal ofCommunication, 59, 205–224.

Eveland, W. P., Jr., & Scheufele, D. A. (2000). Connecting news media use with gaps in knowledge andparticipation. Political Communication, 17, 215–237.

Facer, K., & Furlong, R. (2001). Beyond the myth of the ‘‘Cyberkid’’: Young people at the margins ofthe information revolution. Journal of Youth Studies, 4(4), 451–469.

Fischer, C.S. (1992). America calling: A social history of the telephone to 1940. Berkeley, CA: Universityof California Press.

Gripsrud, J. (2009). Digitizing the public sphere: Two key issues. Javnost-the Public, 16(1), 5–16.Guillen, M. F., & Suarez, S. (2005). Explaining the global digital divide: Economic, political and

sociological drivers of cross-national Internet use. Social Forces, 84(2), 681–708.Gunkel, D. J. (2003). Second thoughts: Toward a critique of the digital divide. New Media & Society, 5,

499–522.Habermas, J. (1962). The structural transformation of the public sphere. Cambridge, MA: MIT Press.


Hargittai, E. (2002). Second-level digital divide: Differences in people’s online skill. First Monday, 7(4).Retrieved January 15, 2005 from http://firstmonday.org/issues/issue7_4/hargittai/#author

Hargittai, E., & Hinnant, A. (2008). Digital inequality: Differences in young adults’ use of the Internet.Communication Research, 35, 602–621.

Haythornthwaite, C. (2005). Social networks and Internet connectivity effects. Information,Communication and Society, 8(2), 125–147.

Herring, S. C. (2002). Computer-mediated communication on the Internet. In B. Cornin (Ed.),Annual review of information science and technology (Vol. 36, pp. 109–168). Medford, NJ:Information Today.

Hoffman, D. L., Novak, T. P., & Schlosser, A. E. (2000). The evolution of the digital divide: How gapsin Internet access may impact electronic commerce. Journal of Computer-MediatedCommunication, 5(3). Retrieved May 15, 2009 fromhttp://www.ascusc.org/jcmc/vol5/issue3/hoffman.html

Howard, P. N., Rainie, L., & Jones, S. (2001). Days and nights on the Internet: The impact of adiffusing technology. American Behavioral Scientist, 45, 383–404.

Jaimes, A., & Sebe, N. (2007). Multimodal human computer interaction: A survey. Computer Visionand Image Understanding, 108(1-2), 116–134.

Jenkins, H. (2007). Confronting the challenges of participatory culture: Media education for the 21stcentury. Chicago, IL: MacArthur Foundation.

Jung, J.-Y., Qiu, J. L., & Kim, Y.-C. (2001). Internet connectedness and inequality: Beyond the‘‘divide’’. Communication Research, 28, 507–535.

Kim, S.-H. (2008). Testing the knowledge gap hypothesis in South Korea: Traditional newsmedia, the Internet, and political learning. International Journal of Public Opinion Research, 20,193–210.

Krueger, B. S. (2002). Assessing the potential of Internet political participation in the United States.American Political Research, 30(5), 476–598.

Latimer, C. (2009). Understanding the complexity of the digital divide in relation to the quality ofHouse campaign websites in the United States. New Media & Society, 11(6), 1023–1040.

Ledbetter, A. M. (2008). Media use and relational closeness in long-term friendships: Interpretingpatterns of multimodality. New Media & Society, 10(4), 547–564.

Lenhart, A., Rainie, L., Fox, S., Horrigan, J., & Spooner, T. (2000).Who’s not online: 57% of thosewithout Internet access say they do not plan to log on. Retrieved May 20, 2001 fromhttp://www.pewinternet.org

Livingstone, S., & Helsper, E. (2007). Gradations in digital inclusion: Children, young people and thedigital divide. New Media & Society, 9, 671–696.

Loges,W. E., & Jung, J. Y. (2001). Exploring the digital divide: Internet connectedness and age.Communication Research, 28, 536–62.

Luders, M. (2008). Conceptualizing personal media. New Media & Society, 10(5), 683–702.Madden, M. (2003). America’s online pursuits. Washington, DC: Pew Internet and American Life

Project.McLaren, J., & Zappala, G. (2002). The ‘‘digital divide’’ among financially disadvantaged families in

Australia. First Monday, 7(11). Retrieved March 5, 2009 fromhttp://www.firstmonday.dk/issues/issue7_11/mclaren

McLeod, J. M., Scheufele, D. A., & Moy, P. (1999). Community, communication, and participation:The role of mass media and interpersonal discussion in local political participation. PoliticalCommunication, 16, 315–336.


Mossberger, K., Tolbert, C. J., & Stansbury, M. (2003). Virtual inequality: Beyond the digital divide.Washington, DC: Georgetown University Press.

National Telecommunications and Information Administration. (1998). Falling through the net II: Newdata on the digital divide. Retrieved May 15, 2009 fromhttp://www.ntia.doc.gov/ntiahome/net2/falling.html.

Newton, K. (1999). Mass media effects: Mobilization or media malaise? British Journal of PoliticalScience, 29, 577–599.

Norris, P. (2001). Digital divide: Civic engagement, information poverty, and the Internet worldwide.New York: Cambridge University Press.

Ono, H., & Zavodny, M. (2003). Gender and the Internet. Social Science Quarterly, 84, 111–121.Parks, M. (2009). What will we study when the Internet disappears? Journal of Computer-Mediated

Communication, 14(3), 724–729.Parks, M. R., & Floyd, K. (1996). Making friends in cyberspace. Journal of Communication, 46,

80–97.Prior, M. (2005). News vs. entertainment: How increasing media choice widens gaps in political

knowledge and turnout. American Journal of Political Science, 49, 577–592.Putnam, R. D. (2000). Bowling alone: The collapse and revival of American community. New York:

Simon and Schuster.Quintelier, E., & Vissers, S. (2008). The effect of Internet use on political participation: An analysis

of survey results for 16-year-olds in Belgium. Social Science Computer Review, 26(4), 411–427.Sandvig, C. (2001). Unexpected outcomes in digital divide policy: What children really do in the public

library. In B. M. Compaine & S. Greenstein (Eds.), Communications policy in transition: TheInternet and beyond (pp. 265–293). Cambridge, MA: MIT Press.

Scheufele, D. A. (2002). Examining differential gains from mass media and their implications forparticipatory behavior. Communication Research, 29(1), 46–65.

Selwyn, N. (2004). Reconsidering political and popular understandings of the digital divide. NewMedia & Society, 6, 341–362.

Shah. D. V., Cho, J., Eveland, W. P., Jr., & Kwak, N. (2005). Information and expression in a digitalage: Modeling Internet effects on civic participation. Communication Research, 32, 531–565.

Sotirovic, M., & McLeod, J. M. (2001). Values, communication behavior, and political participation.Political Communication, 18, 273–300.

Standage,T. (1998). The Victorian Internet: The remarkable story of the telegraph and the nineteenthcentury’s on-line pioneers. New York: Walker.

Sylvester, D. E., & McGlynn, A. J. (2010). The digital divide, political participation, and place. SocialScience Computer Review, 28(1), 64–74.

Trenz, H. (2009). Digital media and the return of the representative public sphere. Javnost-the Public,16(1), 33–46.

Van Dijk, J. (2002). A framework for digital divide research. Electronic Journal of Communication, 12.Retrieved January 15, 2004 from http://shadow.cios.org:7979/journals/EJC/012/1/01211.html

Walther, J. B., & Parks, M. (2002). Cues filtered out, cues filtered in: Computer mediatedcommunication and relationships. In M. L. Knapp, J. A. Daly & G. R. Miller (Eds.), The handbookof interpersonal communication (3rd ed., pp. 529–563). Thousand Oaks, CA: Sage.

Warschauer, M. (2003). Technology and social inclusion: Rethinking the digital divide. Cambridge, MA:MIT Press.

Wasserman, I. M., & Richmond-Abbott, M. (2005). Gender and the Internet: Causes of variation inaccess, level, and scope of use. Social Science Quarterly, 86, 252–270.


Wei, L. (2009). Filter blogs vs. personal journals: Understanding the knowledge production gap on theInternet. Journal of Computer-Mediated Communication, 14(3), 532–558.

Wei, L. & Hindman, D. B. (2011). Does the digital divide matter more? Comparing the effects of newmedia and old media use on the education-based knowledge gap. Mass Communication andSociety, 14(2), 216–235.

Wei, L., & Zhang, M. (2008). The impact of Internet knowledge on college students’ intention tocontinue to use the Internet. Information Research, 13(3) paper 348. Retrieved December 9, 2008from http://InformationR.net/ir/13-3/paper348.html

Xie, B. (2008). Multimodal computer-mediated communication and social support among olderChinese Internet users. Journal of Computer-Mediated Communication, 13, 728–750.

Yu, L. (2006). Understanding information inequality: Making sense of the literature of the informationand digital divides. Journal of Librarianship and Information Science, 38(4), 229–252.

ABOUT THE AUTHOR

Lu Wei is an Associate Professor in the College of Media & International Culture at Zhejiang University.His research interests include the adoption, use, and social consequences of new media technologies.

Address: College of Media & International Culture, Zhejiang University, 148 Tianmushan Rd.,Hangzhou, Zhejiang, 310028, P. R. China. Email: [email protected]


Number Matters: The Multimodality of Internet Use as an Indicator of the Digital Inequalities

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