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New Media Use,Sociodemographics, andVoter Turnout in the 2000Presidential ElectionGang (Kevin) Han Ph.D. aa Department of Communication , State Universityof New York , FredoniaPublished online: 15 Apr 2008.

To cite this article: Gang (Kevin) Han Ph.D. (2008) New Media Use,Sociodemographics, and Voter Turnout in the 2000 Presidential Election, MassCommunication and Society, 11:1, 62-81, DOI: 10.1080/15205430701587644

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New Media Use, Sociodemographics,and Voter Turnout in the 2000

Presidential Election

Gang (Kevin) HanDepartment of Communication

State University of New York at Fredonia

Based on General Social Survey data, this study employs logit models to clarify theeffects of new media use and sociodemographic characteristics on voter turnout inthe 2000 presidential election. It also discusses the predicting power of social-demographics on new media use behavior. Findings highlight that the behavior ofactively seeking political information online, which can be expected by the level ofeducation and income of Internet users, raised their likelihood of voting. GeneralInternet exposure, which is reduced by age and affected by gender, however, couldnot increase the turnout as expected. Among sociodemographic indicators, educa-tion counted the most in the 2000 presidential election. People’s sociodemographiccharacteristics were stronger predictors than their new media use behavior forvoter turnout.

The relationship between mass media and political participation, especially elec-toral activities, has attracted much concern in political science, and in mass com-munication as well. As Conway (1991) observed, “the impact of the mass mediaon political participation is a subject of continuing dispute” (p. 81), where scholarsprovide conflicting views about mass media effects on voting behavior.

Mass Communication & Society, 11:62–81, 2008Copyright © Mass Communication & Society Divisionof the Association for Education in Journalism and Mass CommunicationISSN: 1520-5436 print / 1532-7825 onlineDOI: 10.1080/15205430701587644

Gang (Kevin) Han (Ph.D., Syracuse University, 2007) is an assistant professor at the Departmentof Communication, SUNY-Fredonia. His main research interests include: public relations, news fram-ing and framing effects in electoral or non-electoral civic engagement, and Internet-based media andonline public opinion. He is a former faculty at the Journalism School of Fudan University, Shanghai,China, and a former associate with Ogilvy Public Relations Worldwide.

Correspondence should be addressed to Gang (Kevin) Han, Department of Communication, 314McEwen Hall, State University of New York at Fredonia, Fredonia, NY 14063. E-mail: gang.han@fredonia.edu

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When new media—specifically, the Internet, in this study—began to be widelyadopted in the American society, its influence on elections was far from beingclear, although surveys (e.g., Pew Research Center, 2000a, 2000b) discover thatcampaign 2000 firmly proved the Internet as a major source of election news andinformation. This study, based on the General Social Survey (GSS) data, employslogit models to clarify the effects of new media use vis-à-vis sociodemographiccharacteristics on voter turnout in the 2000 presidential election. The analysis firstlooks at how sociodemographics predicted Web behavior, then examines how bothforecasted the voter turnout independently as well as jointly.

NEW MEDIA USE AND SOCIODEMOGRAPHICS

Demographics and socioeconomic status (SES) are traditionally discussed as pre-dictors of media use (Kosicki &Yuan, 2001; McLeod, Scheufele, & Moy, 1999). Aseries of nationwide surveys during the past decade discussed not only their signif-icant correlation with traditional media use (Stemple & Hargrove, 1996) but also achanging albeit “standard” pattern of the relationship between Internet use andsociodemographics in terms of age, gender, education, and income.

Stempel and Hargrove (1996) reported that only 5.3% of the respondents oftheir survey regularly used the Internet and online service in 1995. The usage in-creased with education and income and was “greatest for those 35 to 54 years oldand least for those more than 55” (Stempel et al., 2000, p. 72). In an updated surveyin 1999, they found that more than 30% of respondents became regular users of theInternet. Users of online services also increased considerably from 3.4% in 1995 to19.3% in 1999. Meanwhile, men used the Internet substantially more than women.People younger than 35 have been the heaviest users and “the difference betweenthose less than 35 years old and those more than 55 years old was huge” (Stempelet al., 2000, p. 75). Income and education have remarkably positive correlationswith the use of the Internet and online media.

Pew Research Center’s (1999) survey on Internet use conducted in the same pe-riod reported that 23% of Americans went online in 1996 and 41% of Americanadults used the Internet in 1998. Generally, Internet users are substantially younger(80% younger than 50), better educated (70% college educated), and more affluentthan the U.S. average, and among them, men (52%) outnumber women (p. 9).Most recently, Pew Internet & American Life Project (2005) surveys found that26% of Americans age 65 and older go online, compared with 67% of those ages50 to 64, 80% of those ages 30 to 49, and 84% of those ages 18 to 29. Twenty-ninepercent of those with subsecondary education have access to the Internet,compared with 61% of high school graduates and 89% of college graduates.Internet users living in the highest-income households not only have the highest

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percentage of access to the Internet (93%) but also are most likely to have a fastconnection—71% of them have a broadband connection at home.

In general, the gender gap in Internet use is gradually diminishing. Men, espe-cially young, White, well-educated, and fairly affluent men, were the earliestadopters of the Internet. Pew’s 1995 survey shows that about 58% of the onlinepopulation was male. Five years later, Internet users were evenly divided betweenmen and women, although the difference—49% men versus 44% women—wasstill significant. Ten years later, the respective proportions became almost equal.Some 68% of men and 66% of women are now Internet users, with no statisticallysignificant difference between the groups. Younger women are more likely thanyounger men to be online, whereas older men are more likely than older women tobe online (see Pew Internet & American Life Project, 2005).

As to specific engagement with the Internet, nevertheless, gender difference isstill there. For example, heavy online news consumers include more better-educated men than women (64% vs. 36%) according to Pew’s survey in 1998 (PewResearch Center, 1999). But there are no real age differences. Pew Internet Projectin 2002 confirmed the persistence of this pattern of online news use, that is, onlinenews audience tends to be young, well-educated, and affluent male. Gender gapand education gap remained pronounced.

Pew’s 2005 survey further suggests that, compared with women, men are morelikely to use the Internet to get political information. Men communicate more withonline special interest groups and are more likely to engage themselves in onlinechatting or discussion groups than are women.

Scheufele and Nisbet (2002) stressed that, despite the continuing increase of the“online citizen” (p. 60) in America, their demographic difference cannot be ig-nored. Gender, college education, and high income influenced considerably onlinenews use. Consequently, before discussing the influence of sociodemographicsand new media use on voter turnout in the 2000 general elections, this study firstproposes a set of hypotheses to look at the relationship between sociodemographicvariables and new media use:

H1: Sociodemographic characteristics are positively correlated with new me-dia use. Specifically,

H1a: People spend more time online in general if they are younger, better edu-cated, have higher incomes, and if they are men.

H1b: People spend more time online interacting with other net users if they areyounger, better educated, have higher incomes, and if they are men.

H1c: People visit Web sites for news or current events more frequently if they areyounger, better educated, have higher incomes, and if they are men.

H1d: People visit Web sites for political information more frequently if they areyounger, better educated, have higher incomes, and if they are men.

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TRENDS OF VOTER TURNOUT

Verba and Nie’s (1972) classic study on political participation suggests both that“voting is the most widespread and regularized political activity, and in terms ofthe overall impact of the citizenry on governmental performance it may be thesingle most important act” and that “voting and campaign activity are thus two ofthe major ways in which individuals can participate in politics” (p. 46).

Nevertheless, there has been a continued decline in the turnout of U.S. presiden-tial elections for more than 4 decades (e.g., Conway, 1991; Frank, 2002). In the1950s and 1960s the voter turnout for U.S. citizens of voting age was typically inthe high 50% to low 60% range (Frank, 2002). In the 1970s, it dropped to around55% (Miller & Shanks, 1996). By the late 1980s the turnout was around 50%,where it has remained for most subsequent presidential elections (Brody, 1978;Frank, 2002). In 2000, the turnout of voting-age population was 50.4% (Finkel &Freedman, 2004).

To better understand the decline of voter turnout, a number of studies in socialscience have been carried out by evaluating the relative impact of various factors,such as social resources or social structures (Burstein, 1972; Nie, Powell, &Prewitt, 1969), SES (Beeghley, 1986), political generations and generational dif-ferences (Miller & Shanks, 1996), campaign finance attitudes (Box-Steffensmeier,Grant, & Rudolph, 2004), ideology (Jacoby, 2004), party coalitions and group sup-port (Stanley & Niemi, 2004), and psychological involvement in politics (e.g., par-tisan identification, political efficacy, political trust and candidate evaluation; seeAbramson & Aldrich, 1982; A. H. Miller, 1974; Shaffer, 1981), to name a few.Among these variables, demographic attributes (e.g., Kanthak & Norrander, 2004)are regarded as indispensable indicators.

VOTER TURNOUT AND SOCIODEMOGRAPHICS

The correlation between voter turnout and such sociodemographic variables asage, gender, education, and income has thus been under scrutiny. Verba and Nie(1972) pointed out that “voting specialists” “come disproportionately from lower-education and income groups,” which include “older citizens, Catholics, big-citydwellers and to a small extent, women” (p. 97). They also found that college-educated citizens or those with high incomes are quite “underrepresented amongthose who limit their activity to voting” (p. 97).

Shaffer’s (1981) data shows that the changing age distribution of the electoratehas important influence on the variation of voter turnout. Conway (1991) indicatedthat citizens ages 30 to 65 appear to vote at higher rates than their older or youngercounterparts. Wolfinger and Rosenstone (1980) argued, however, that althoughearly studies show a curvilinear relationship between age and turnout, the effect of

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age is of little significance. Frank (2002), along with others (e.g., Miller & Shanks,1996) pointed out that the gender gap, usually understood as a function of age, isproven to have little influence on voter turnout these days.

Education, on the other hand, has been found to be the most influential socialcharacteristic related to turnout (e.g., Wolfinger & Rosenstone, 1980). Miller andShanks (1996) employed “standard cohort analysis” (p. 42) to evaluate the changingcorrelationsof turnoutalong threestages in thepolitical lifeofAmericancitizensbe-tween 1952 and 1992. They found that education is a powerful predictor promotingvoter turnout both within the “pre-New Deal generation” (p. 84) and the “New Dealgeneration” (p. 87). Likewise, education, in Wolfinger and Rosenstone’s (1980)study, has a very strong independent effect on the likelihood of voting, controllingfor all other demographic variables.

Scholars have also confirmed the strong predicting power of income. Miller andShanks (1996) advised that income “was a consistent contributor to voter andnon-voter differences in the New Deal cohorts” and helped “stabilize turnout lev-els” (p. 88). Conway (1991) suggested that those who earn more are more likely tovote. Verba, Nie, and Kim (1978) and others have even argued that income is morepredictive than education.

Nevertheless, although the role of demographics in turnout has been widelystudied, mixed findings always exist. Teixeira (1987) concluded, for example, thatelevated schooling years, income, and job status had no consistent positive effecton voting turnout between 1960 and 1980. In this sense, “a clear-cut consensus …has yet to be developed” (Frank, 2002, p. 45).

The second hypothesis put forward here thus tries to test the independent effectsof sociodemographic variables on turnout, especially in the first U.S. presidentialelection of the 21st century.

H2: Sociodemographics are positively correlated with voter turnout. Specifi-cally, those who are older, better educated, and have higher incomes aremore likely to vote. In addition, women are more likely to vote than men.

VOTING AND NEW MEDIA USE

It is worth noting that previous studies addressing the effects of media use on vot-ers usually discuss traditional media, in particular, use of television and newspapernews (e.g., Capella & Jamieson, 1996; Glaser, 1965; McLeod & McDonald, 1985;Patterson, 2001; Shaffer, 1981; Simon, 1996; Teixeira, 1987; Weaver, Drew, &Wu, 1998; Wu, 1995). This study shifts attention to the new media.

The social effects of new media adoption and use are moot issues for earlierstudies (Kosicki & Yuan, 2001). Some scholars hail the new media, as they believethat the Web opens a new sphere in which people can learn to participate in the

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political world (Browning, 1996), which will consequently benefit democracy.Others, on the contrary, are suspicious about the positive political implication ofthe new media because of the ease it allows the audience in filtering online infor-mation, which is capable of making them more disconnected from others in theircommunities (see Kosicki & Yuan, 2001). Still others worry that the new digitaltechnology would expand the information gap between the haves and have-nots(e.g., Graber, 1996). More scholars, because of the increasing literature, continueto discuss the two sides of the story, that is, the pros and cons of the Internet’s effecton the democratic process (e.g., Johnson & Kaye, 1998; Scheufele & Nisbet,2002).

The study of the relationship between voting behavior and traditional media useis a mixture of conflicting views, and so is the discussion regarding the extent towhich Internet use can promote voter turnout. The skepticism over the positive linkbetween Internet use and the likelihood to vote has seemed to be plausible. For ex-ample, Bimber (2001) found that there is no direct link between election-relatedInternet use and voter turnout, even though his earlier study (Bimber, 1997, ascited in Johnson & Kaye, 1998), along with Hill and Hughes (1998), reports thatInternet users are more likely to vote.

In corroboration with the aforementioned, the Pew Research Center demon-strates that controlling for other factors related to participation, Internet users areno more likely to be engaged in political processes (Pew Research Center, 2000b)and show no greater tendency to vote than do nonusers (Pew Research Center,2000a). It is also the case that the audience for election news has shown less inter-est in engaging in online political activities than in retrieving political information(Pew Research Center, 2000b).

Moreover, Johnson and colleagues (1996, as cited in Johnson & Kaye, 1998)found that use of political Web sites was unrelated to the likelihood of voting forClinton or the intent to vote in general, although it was positively related to thelikelihood of voting for Dole. Scheufele and Nibset (2002) thus concluded that theInternet is limited in promoting citizenship.

There is evidence, nevertheless, that advocates the positive influence of pur-poseful or active use of new media on voter turnout. The Pew Research Center(2000b) discovered, for instance, that the audience for online campaign news in2000 increased fourfold over 1996 (18% from 4%). More important, 43% of elec-tion news consumers said online campaign news affected their voting decisions, upfrom 31% in 1996. The effect of online campaign news has been particularly evi-dent among young people. Half of election news consumers younger than 30 re-ported the information they received online made them want to vote for or against aparticular candidate.

Consequently, the third set of hypotheses is raised to address the central con-cern of this study—the predictive power of new media use on voter turnout, con-trolling for the alternative explanation by sociodemocratic variables.

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H3: New media use is significantly correlated with voter turnout, controllingfor sociodemographics, in terms of age, gender, education, and income.Specifically,

H3a: The more time people spend on the Internet, the lower the voter turnout.H3b: The more time people spend on online interaction with other Web users,

the lower the voter turnout.H3c: The more frequently people visit Web sites for news or current events, the

higher the voter turnout.H3d: The more frequently people visit Web sites for political information, the

higher the voter turnout.

Finally, new media use is compared with sociodemographics, with the hypothe-sis that the latter have stronger predictive power than the former on voter turnout,based on the aforementioned literature review.

H4: Sociodemographics can predict more voter turnout than new media use.

METHODOLOGY

Data Set

Unlike many previous studies on voter turnout, which mainly analyzed AmericanNational Election Studies (ANES) data (see Frank, 2002; Weisberg & Wilcox,2004), this study is based on data collected in the GSS for year 2002 (N = 2,325).

GSS is an omnibus, personal interview survey of U.S. households conducted bythe National Opinion Research Center. It uses a representative national sample ofnoninstitutionalized English-speaking adults ages 18 years and older living in theUnited States. Data have been collected in February, March, and April every yearfrom 1972 through 1993, except for 1979, 1981, 1992; and every 2 years from1994 through 2004. The response rate is 70%.1

Measurement2

Sociodemographics. Demographic items, such as age, gender, education,and SES indictors such as income, are important predictors of media use and polit-ical participation (McLeod et al., 1999; Verba, Schlozman, & Brady, 1995). Fourindicators—age, gender, education, and income—were chosen in this study to

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1For further details of GSS information, see http://webapp.icpsr.umich.edu/cocoon/ICPSR-STUDY/04295.xml

2See the appendix for GSS variables and question wording.

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examine the predictive power of social characteristics on new media use as well ason voter turnout.

Age is measured as actual years of respondents’ age; those who are youngerthan 18 are eliminated. Because there may exist a curvilinear relationship betweenage and voter turnout according to previous research (Turner, Shields, & Sharp,2001), this study also incorporates age-squared as an independent variable whendiscussing the influence of age on voter turnout.

Education is measured in the actual highest year of schooling completed by therespondent, which goes from Grade 1 to the eighth year in higher education.

Income represents respondents’ pretax income for last year, which has 23 cate-gories, from “under $1,000” to “$110,000 or over.” This study includes all the re-spondents who do not earn regular wage income, because suffrage does not dependon having income. Considering that the variables included are related to individualrespondents, this study uses the variable measuring their individual incomes ratherthan their family incomes.

Gender, as a dummy variable, is categorized into two groups (male = 1, female= 2).

New media use. Eveland and Scheufele (2000) pointed out communicationscholars have not yet agreed on a criterion for measuring news media use behavior.Other than media exposure, scholars have considered including media attentionvariables. Some propose to combine measures of exposure and attention. Others,however, advocate separating these two measures in the same regression equation(see Eveland & Scheufele, 2000). Suffice it to say that there is no consistent mea-surement of new media use available for universal research purposes.

Four dimensions in this study are examined to evaluate new media use behav-ior: (a) online exposure (except for e-mail, the time per week spent on the Internet,including visiting Web sites and using Web services); (b) online interaction (timespent in chat rooms, news groups, or other forms of online interaction with othernet users), and online information seeking, including both (c) news accessing (a4-point scale measuring the frequency of visiting Web sites for news and currentevents during the past month); and (d) political information retrieving (a 4-pointscale measuring the frequency of visiting Web sites for political information).Those who are eligible to vote but do not use a computer are coded as zero on themeasure of Internet use.

Voter turnout. The dependent variable was coded as respondents’ answer to“whether or not you voted” in the 2000 election. Respondents ineligible to vote orwho failed to answer this question were eliminated, and the remaining responseswere recoded (voted = 1, did not vote = 0).

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Data Analysis

Multiple regressions are applied first to examine how sociodemographic variablespredict different modes of new media use, followed by binary logist regressionsthat explain the impact of new media use, as well as sociodemographic indicators,on voter turnout in the 2000 presidential election.

RESULTS

This study expects that four aspects of new media use behavior—that is, generalInternet exposure, online interaction, news Web sites accessing, and online politi-cal information retrieving—are influenced by people’s sociodemographic charac-teristics in terms of age, education, gender, and income. It focuses on the signifi-cant effect that new media use may have on voter turnout, on top of the influenceexerted by sociodemographic indicators. Accordingly, four sets of research hy-potheses are proposed to test these theoretical expectations.

The Prediction of Sociodemographics on New Media Use

The first set of hypotheses centers on the relationship between sociodemographicsand Internet use. Using adjusted R2s and standardized bs, four regression modelsin Table 1 reveal how age, education, gender, and income predict new media usebehavior.

Model 1 demonstrates the influence of sociodemographics on general Internetexposure, wherein 6.3% of variance can be explained by age, education, and gen-der. Education is the strongest indicator of general online exposure. Women spendless time than men using the Internet, and the older the people, the less time theyspend surfing the Internet.

Unexpectedly, income is unrelated to general online exposure. What is more,along with age, it is negatively associated with the time spent on online interaction.In Model 2, only .6% of variance of online interaction can be predicted by incomeand age.

Adjusted R2s, 13.6% and 11.3%, respectively, for Model 3 and Model 4 repre-sent a similar pattern whereby sociodemographic indicators are predictive of on-line information seeking behavior, in which education and income account fortheir increase and education is more important than income. Meanwhile, increas-ing age is hooked to a decrease in the frequency of online news accessing, as is thefemale gender. But gender is irrelevant to the frequency of online political infor-mation retrieving.

Among the four models, age is negatively correlated with all four kinds of newmedia use behavior discussed, that is, younger people spend more time than older

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TABLE 1Regression Analysis of Sociodemographic Variables on New Media Use

(DV)

Model 1: Online Exposure Model 2: Online InteractionModel 3: Online News

AccessingModel 4: Online Political Info.

Retrieving

(IV) � Adjusted R2 � Adjusted R2 � Adjusted R2 � Adjusted R2

063**** .006** .136**** .113****Age –.151****

(.009)–.083****

(.003)–.159****

(.002)–.160****

(.001)Education .144****

(.054).005

(.016).248****

(.011).239****

(.007)Gender –.084****

(.296)–.034(.089)

–.054**(.060)

–.039(.038)

Income .027(.020)

–.057*(.006)

.097****(.004)

.059**(.003)

Note. N = 2,325. Standard errors are in parentheses. DV = Dependent Variables; IV = Independent Variables.*p < .05. **p <.01. ****p < .0001

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people not only on the general use of the Internet but also in using Internet for cer-tain purposes. Education is the most powerful indicator when predicting active on-line information seeking, both for news and political contents, as well as the gen-eral exposure to the Internet. Education, nevertheless, cannot help explain the timespent on online interaction. Although it has no say on the time spent on Internet ex-posure, income is positively correlated with the frequency of online informationseeking behavior and negatively associated with the time spent on online interac-tion. In addition, gender can forecast online exposure and news content seeking; inother words, men not only use the Internet more heavily than women in general butalso access news Web sites more often than women.

As a whole, these four variables can predict online information-seeking behav-ior much better than online exposure and interaction behavior. Online news access-ing can be estimated by all these four sociodemographic variables. People visitWeb sites for news or current events more frequently if they are male, are younger,are better educated, and have higher incomes. Well-educated young people spendmore time with the Internet in general and visit Web sites for political informationmore frequently than those who are either older or less well educated. Meanwhile,having high income increases the frequency of political information seeking butdecreases an individual’s time spent on interacting with other net users. Moreover,men use the Internet more than women generally, and the younger the Internet us-ers, the more likely they use interactive function of the Web.

Therefore, for the first set of hypotheses, H1c is confirmed, and H1a, H1b, andH1d are partially supported.

The Predictive Power of Sociodemographics and NewMedia Use on Voter Turnout

To test the other three hypotheses sets, three logit models are used in Table 2 to il-lustrate the significant effects of sociodemographics and new media use on thelikelihood of voting.

Sociodemographic characteristics serve as independent variables in Model 1,where education, age, and income account for the variance, with a decreasing or-der of weights. Similar to previous studies, education answers for the variation themost, whereas gender does not matter in this model. Age-squared, nevertheless,cannot clarify the assumed curvilinear relationship with voter turnout. Odds ratioestimate proves that the new ratio of voter to nonvoter will be as 1.314 times as theold one when schooling increases 1 year. Likewise, as long as age adds 1 year, aswell as income moves up 1 unit on its scale, the new ratio of voter to nonvoter willbe as 1.059 times and 1.034 times as old ones, respectively. H2 is thus partiallysupported.

Model 2 reveals that the independent predictive power of new media use behav-ior variables on voter turnout is much weaker than that of sociodemographics. It isworth noting that online political information retrieving helps raise the odds ratio:

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TABLE 2Binary Logit Models of Predicting Voter Turnout in 2000 Presidential Election by Demographic and New Media Use Indicators

(DV)

Model 1 Model 2 Model 3

(IV) �

Likelihood

Ratio (�2) � �

Likelihood

Ratio (�2) � �

Likelihood

Ratio (�2) �

Sociodemographic 458.033**** — — — 485.004****

Age .553*** (.017) 1.059 .574*** (.017) 1.061

Age-squared –.064 (.000) 1.000 –.068 (.000) 1.000

Education .419****

(.021)

1.314 .385**** (.022) 1.285

Gender .031 (.102) 1.119 .032 (.103) 1.122

Income .147****

(.007)

1.034 .144**** (.008) 1.034

New media use — — — 43.607****

Online exposure –.078* (.008) .980 –.061 (.009) .985

Online interaction –.033 (.023) .972 –.004 (.024) .996

Online news accessing .045 (.058) 1.055 –.010 (.064) .988

Online political info. retrieving .164** (.099) 1.376 .192*** (.108) 1.454

Note. N = 2,325. Standard errors are in parentheses. IV = Independent Variables. DV = Dependent Variables.

*p < .05. **p < .01. ***p < .001. ****p < .0001.

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The voter to nonvoter ratio multiplies itself by 1.376 when the frequency of visit-ing a Web site for political information increases on the scale. The growing onlineexposure, in contrast, decreases voter turnout. Online news accessing, unfortu-nately, cannot explain the change of voter turnout as expected, which on the otherhand can be forecasted by all four sociodemographic variables evaluated in thisstudy. Meanwhile, online interaction is not able to give a reason to the change inthe likelihood of voting either. In H3, H3a and H3d are confirmed.

Model 3 includes all independent variables, which displays a slightly strongerpredictive power than Model 1 on voter turnout. Among all variables discussed inthis study, online political information retrieving has the strongest predictingpower, considering that the odds ratio mounts to 1.454 from 1.376 in Model 2. Inthe meantime, similar to Model 1, the contributions of education, age, and incomeare also significant. Among them, education is still the most important indicator.Unlike Model 2, the explanatory function of online exposure, however, cannot beclarified in Model 3. The final model reveals that active online political informa-tion seekers were more likely to vote in 2000 than those who less frequently usedor did not use the Internet for the same purpose, controlling for the influence ofsociodemographic predictors. Because three of four sociodemographic indicatorsin this study give significant explanation to the variance of the likelihood of voting,whereas only one new media use variable matters in this model, H4 is thus verified.

DISCUSSION

Previous studies have shown that a number of factors account for the change invoter turnout (e.g., Finkel & Freedman, 2004). The role of Internet-based media inelections, however, needs more scrutiny, as the Internet has already become an in-creasingly important communication channel in political campaigns. This studyassesses GSS data by employing logit models to reveal the effects of new mediause as well as sociodemographic characteristics on voter turnout in the 2000 gen-eral election. Particular attention is paid to the independent explanatory power ofnew media use on voter turnout. The influence of sociodemographics on new me-dia use behavior is also examined.

This study first selects four of the most important sociodemographic indicators(i.e., age, gender, education, and income) to take a close look at how they deter-mine new media use behavior in terms of general online exposure, online interac-tion, online news accessing, and online political information retrieving.

Logit models then prove the steady influence of demographics on voter turnout.Age, education, and income—except for gender—can help estimate the varianceof voter turnout. For the 2000 presidential election, those who were better educatedand older were more likely to go to the voting booths than those who were lesseducated and younger. It is worth noting that, age, in this study, is negatively corre-

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lated with new media use but positively associated with voter turnout. Becauseage-squared is not a statistically significant indicator in the analysis presentedhere, the strong positive linear relationship between age and voter turnout verifiesearlier findings suggesting turnout actually increases with age, when other socio-demographic characteristics were controlled (e.g., Campbell, Converse, Miller, &Stokes, 1960; Conway, 1991; Walfinger & Rosenstone, 1980).

The key concern of the analysis is the impact of new media use on voter turnout.Findings provide insights in evaluating the role of new media use in elections.First, this study gauges the effect of new media use on a general election takingplace when the Internet had been widely adopted for the first time in the UnitedStates in such elections. Specifically, it highlights that active online informa-tion-seeking behaviors—in particular the seeking of political information—whichis linked to potential voters’ education and income level, raised the turnout in2000. Online political information seeking is the strongest predictor among all in-dependent variables according to their odds ratio, although not all four dimensionsof new media usage discussed are able to explain more about the likelihood of vot-ing in 2000, on top of the influence of people’s sociodemographic characteristics.This suggests that those who seek political information online may be interested inpolitics. High levels of exposure to political information further stimulate politicalengagement, and as a result encourage political participation. This evidence beliesthe claimed disconnection between political Web sites usage and general voting in-tention (e.g., Johnson & Kaye, 1998) while confirming the earlier discovery (e.g.,Pew Research Center, 2000b) about the positive influence of new media use onturnout, even given that political information seekers do not necessarily limitthemselves to accessing online election news or campaign messages.

Second, this study confirms that general Internet exposure, wherein the youngoutnumber the old and the men outnumber women, is not able to increase turn-out. On the contrary, the more time people spend on the Internet, the less likelythey go out to cast ballot. This may respond to previous findings that Internetmakes its users apathetic and detached from politics, on one hand; on the otherhand, this is also in accord with conventional wisdom about the weights of ageand gender in the determination of voting behavior, according to which, youngercitizens are less interested in voting than older people, as men are less interestedin voting than women. Therefore, although the gender’s influence on the turnoutis insignificant in this study, once age and gender have been held constant, it ishard to claim that the decrease of turnout, in this respect, is merely broughtabout by general Internet exposure.

Online news accessing is testified not to be as an effective predicator as onlinepolitical information retrieving for turnout, although both educational level and in-come similarly justify the increase of the frequency of these two kinds of online in-formation-seeking activities. Likewise, using online interactive service has noth-ing to do with turnout. Many people check out a variety of content from the

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Internet for different purposes, some for information and others just for fun. Whenthey view online news, they do not have to read political news. Chatting with peo-ple on the other end of the cable may also disconnect Internet users from the poli-tics in the real world. Even if they talk about politics in a chat room, it does notmean they would really want to take part in political activities personally. Thisproof seems to support the argument on the limited role of the Internet in mobiliz-ing citizens’ political participation (Scheufele & Nibset, 2002) as well as earlierconcerns about the negative political implications of the new media (see Kosicki &Yuan, 2001).

Nevertheless, it is still too early to make such a conclusion. As mentioned ear-lier, the evaluation of the role of new media use in voting behavior is not aready-made measurement. There are no consistent criteria in assessing traditionalmedia use, not to mention new media. Scholars may observe some dimensions andleave out others (McLeod & McDonald, 1985). In this sense, different measures ofnew media use behavior may produce mixed, sometimes contradictory findings.Findings in the study presented here indeed advocate that purposeful use of theInternet matters in elections. The result partially validates the necessity of distin-guishing online political information seeking from Internet exposure as well as on-line general news use when the new media is discussed. Internet is a convergedcommunication channel and a “one-stop shopping” information market as well.Internet-based media use should be assessed according to the purpose of its users.Tentatively, analyzing the four purpose-oriented aspects by employing GSS data isa worthy endeavor in optimizing the measurement of new media use.

Future studies can aim at incorporating sociodemographic indicators andnew media use variables into a single path analysis to map a whole picture ofthe influence brought up by the new media to political engagement in theInternet era.

ACKNOWLEDGMENTS

An earlier version of this paper was presented to the Mass Communication Divi-sion at the International Communication Association (ICA) 56th Annual Confer-ence, Dresden, Germany, 2006. The author would like to thank Dr. JamesShanahan and anonymous reviewers for their insightful comments.

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APPENDIXTABLE A1

GSS Variables and Question Wording

IV GSS Variables Question Wording

Sociodemographics Age AGE (Code the exact age of respondents)Education EDUC A. What is the highest grade in elementary school or high school that (you/your

father/your mother/your [husband/wife]) finished and got credit for? CODEEXACT GRADE.

B. IF FINISHED 9th-12th GRADE OR DK*: Did (you/he/she) ever get a highschool diploma or a GED certificate? [SEE D BELOW.]

C. Did (you/he/she) complete one or more years of college for credit—notincluding schooling such as business college, technical or vocational school?

IF YES: How many years did (you/he/she) complete?D. Do you (Does [he/she]) have any college degrees? (IF YES: What degree or

degrees?) CODE HIGHEST DEGREE EARNED.Income RINCOM98 Did you earn any income from (a certain occupation asked in a previous question) ?

Yes ....... (ASK A)A. IF YES: In which of these groups did your earnings from (a certain occupation

asked from a previous question) for last year—[1973–1997]—fall? That is,before taxes or other deductions. Just tell me the letter.

Gender SEX (Code respondent’s sex)

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New media use Online exposure WWWHR Not counting e-mail, about how many minutes or hours per week do you use theWeb? (Include time you spend visiting regular Web sites and time spent usinginteractive Internet services like chat rooms, Usenet groups, discussion forums,bulletin boards, and the like.)

A. Hours per week?Online interaction CHATHR Earlier you mentioned that you spend [number in answer to Q.769]

(minutes/hours) using the World Wide Web in a typical week. About howmany of those do you spend using chat rooms, news groups, bulletin boards,discussion forums, and other forms of online interaction with other Net usersnot just browsing on your own?

A. Hours per week?Online news accessing NEWS30 In the past 30 days, how often have you visited a Web site for?

E. News and current events.Online political

information retrievingPOL30 In the past 30 days, how often have you visited a Web site for?

G. Political information?DV

Voter turnout VOTE00 In 2000, you remember that Gore ran for president on the Democratic ticketagainst Bush for the Republicans. Do you remember for sure whether or notyou voted in that election?

Note. IV = Independent Variables; DV = Dependent Variables.

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