Ethnicity, place, andcommunication technology

Effects of ethnicity on multi-dimensionalinternet connectedness

Yong-Chan KimDepartment of Community and Behavioral Health,

University of Iowa, Ames, Iowa, USA

Joo-Young JungGraduate School of Interdisciplinary Information Studies,

University of Tokyo, Tokyo, Japan, and

Sandra J. Ball-RokeachAnnenberg School for Communication,

University of Southern California, Los Angeles, California, USA

Abstract

Purpose – The purpose of this paper is to examine the unique effect of ethnicity on people’s internetconnectedness. Internet connectedness is a multi-dimensional relationship that individuals form withthe internet.

Design/methodology/approach – Survey findings from a study of four ethnic groups living inseven residential areas within ten miles from the Los Angeles Civic Center indicate that ethnicity has asignificant unique effect not only on the rate of people’s internet access, but also on the threedimensions of the internet connectedness index: context and history; scope and intensity; andcentrality, after controlling for individual socio-economic factors.

Findings – The results indicated that African-Americans lagged behind other ethnic groups in allthree dimensions of their internet connectedness. This suggests that the ways in which the internet isincorporated into people’s everyday lives are likely to differ by geo-ethnic areas.

Originality/value – Implications of these results are discussed from a “communicationinfrastructure framework,” which provides an ecological framework to interpret the ethnicdifferences in the multiple dimensions of internet connectedness.

Keywords Ethnic groups, Internet, United States of America

Paper type Research paper

Previous academic and policy-oriented studies of the digital divide in the USA found asignificant inequality among different ethnic groups. However, few researchers haveclearly articulated a theoretical framework to understand the unique effect of ethnicityon individuals’ connections to new communication media. Many have considered theethnic digital divide as a mere reflection of the difference in socio-economic status(Dutton et al., 1989; Hoffman et al., 2000; Nie and Erbing, 2000). Seen from this

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This paper is part of the ongoing Metamorphosis research project, funded by the AnnenbergSchool, the Annenberg Center for Communication at the University of Southern California, andLos Angeles County First Five Proposition 10 Commission.

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Information Technology & PeopleVol. 20 No. 3, 2007pp. 282-303q Emerald Group Publishing Limited0959-3845DOI 10.1108/09593840710822877

perspective, the ethnic digital divide is expected to disappear as computers and theinternet turn from being a “luxury” to a “necessity.” Indeed, several reports havealready indicated that ethnic divides are closing in the USA (Holms, 1997; NTIA, 2002).

However, other reports, studies and comments were released challenging the notionof a “closing ethnic divide” by examining the digital divide beyond questions of merephysical access (Attewell, 2001; Morino Institute, 1995; Jung et al., 2001; Children’sPartnership, 2000; Wilhelm and Thierer, 2000). They suggest alternative conceptualframeworks such as “the second digital divide” (e.g. divides based on computer skills,Attewell, 2001), a content-based divide (Children’s Partnership, 2000; Wilhelm andThierer, 2000) or a capability divide (Morino Institute, 1995). Now researchers agreedthat we should look beyond mere access to explore deeper kinds of divides amongsocio-economic and ethnic groups.

In accordance with the suggestions of these researchers (Attewell, 2001; Norris,2002; Wilhelm and Thierer, 2000), we seek to go beyond a conception of the ethnicdigital divide as a gap between those who have internet access and those who do not.We have developed a concept of “Internet connectedness,” a multidimensionalrelationship between the internet and individuals. Based on the concept of internetconnectedness, the current study will embrace both quantitative and qualitativeaspects of the ethnic digital divide.

To examine the effect of ethnicity on internet connectedness, we compare fourethnic groups – whites, African Americans, Latinos[1], and Asians – in Los Angelesmetropolitan areas. By examining these four ethnic groups embedded in specificspatial and temporal contexts rather than discussing ethnic effects using nationwideaggregate data, we attempt to provide a context-sensitive discussion about ethniceffects on internet connectedness. We begin by asking if there is a unique contributionof ethnicity to the likelihood of having access to the internet, or if ethnic variation isfully explained by socioeconomic factors. In addition, we ask if ethnic variance has aunique effect on the ways in which people connect to the internet after they acquirephysical access; i.e. is there a difference in the context that surrounds internet users, thescope and intensity of their internet activities, and their perceptions of the internet’scentrality in their everyday lives[2]?

Ethnicity and communication mediaPrevious studies that examined ethnicity as an independent factor shaping levels andtypes of connections to various communication media were not many in number andlacked a systematic mode of interpretation. Even in the long tradition of research ontechnology adoption (Rogers, 1995), little research has examined ethnicity as adynamic and unique factor influencing individuals’ adoption and uses ofcommunication technologies. When researchers found an ethnicity effect oncommunication behaviors, it was usually considered as a reflection of othersocio-economic factors (Greenberg and Dervin, 1970).

In general, although ethnic effects in communication studies have beenmarginalized, there have been several important studies that examined and reportedthe unique influence of ethnicity on communication behaviors. These include researchreporting a unique ethnic effect on motivation for media use (Albarran and Umphrey,1994; Subervi-Velez et al., 1994), media effects (Newhagen, 1994; Children’sPartnership, 2000), program preferences (Albarran and Umphrey, 1994), types of

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information pursued through media use (Ribisl et al., 1998), evaluation of media content(Becker et al., 1992), level of understanding of media system operation (Becker et al.,1992), level of active use (Carroll et al., 1993), telephone adoption (Fischer, 1992), andlikelihood of subscription to pay cable channels (Albarran and Umphrey, 1993).

Despite these studies, it is fair to say that, in general, ethnicity has not beenprioritized in past communication inquiries. There are several theoretical andmethodological reasons for this. First, with the emphasis on modernization in twentiethcentury social science, ethnic or cultural differences were often treated as hierarchicallylinear disparities, where one ethnicity should follow the cultures and customs of“others” in order to adopt a modernized lifestyle in order to advance. Such linearconceptions of modernity, for example, often guided modernization programs (Lerner,1958), diffusion of innovations projects (Rogers, 1995)[3] or assimilation approachesabout immigrants in the USA (Park, 1923). In particular, the influence of the ChicagoSchool’s assimilation research may be an important reason for poor articulation ofethnicity as a significant factor in communication studies (Park, 1915). In this tradition,the ethnicity of a specific group is hypothesized as a factor that will progressively loseground in the extant urban ecology of the USA when the group “succeeds” in adaptingitself to “mainstream” society.

In addition, there are methodological reasons that include the difficulty of definingand operationalizing ethnicity. Ethnicity cannot be captured by a unidimensionalmeasure since it can be defined in many different ways, such as regional origin,language, history, religion, or cultural practices. Another methodological note onethnicity is that, pragmatically speaking, it is neither easy nor economical to gather asufficiently large sample of a single ethnic group required to statistically test the uniqueeffect of ethnicity. In many previous studies, ethnic minority samples were not largeenough to perform valid statistical comparisons with a larger sample of whites. Inaddition, data collection in English inevitably excludes members of many ethnic groupsin the USA who are neither comfortable nor capable of communicating in English.

However, recent ethnic studies have suggested that ethnicity persist independent ofsocial, cultural, or economic assimilation of immigrants into their host societies.Greeley (1974, p. 203) said “the importance of ethnicity as a predictor variable can nolonger be ignored by American social research” and “diversity among religioethnicgroups [in the USA] is of similar magnitude to the diversity found in various nations incross-national studies.” Even after achieving socioeconomic mobility in their hostsociety, ethnic groups still maintain their ethnic identity, values, norms and culture(Portes and Zhou, 1992). In addition, largely due to the new communicationtechnologies, new immigrants in the USA do not abandon their social ties to theircountries of origin (Lien et al., 2004). Lien et al. (2004, p. 22) said, “people frequentlymaintain strong social, economic, symbolic, and political transnational ties that enablethe formation of multiple identities, particularly in nation-states with multiple orpolyethnic rights.” In multiethnic societies such as Los Angeles, this trend of persistentethnicity would have affected what people think, feel and do about new informationtechnologies such as the internet.

Ethnicity and internet studiesWhen compared to previous studies of “old” communication technologies, most USempirical research on the internet included ethnicity as one of the main independent

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factors in studying adoption and usage patterns. This trend is reflected in severalnation-wide surveys, such as those conducted by the US Department of Commerce’sNational Telecommunication and Information Administration (NTIA, 1995, 1999, 2000,2002), the Pew Internet and American Life Project (Pew, 2001a, b; Spooner and Raine,2001) and the Vanderbilt University elab research group (Hoffman et al., 2000; Novakand Hoffman, 1998).

Some of these studies specifically tested and confirmed a unique effect of ethnicityon individuals’ connection to computers or the internet. Three NTIA reports (NTIA,1995, 1999, 2000), based on Current Population Survey data, showed that ethnicity wasa significant cultural factor in the digital divide after controlling for incomeand education. In the 2000 report, they demonstrated that income and educationexplained only about half of the variance in people’s internet use (NTIA, 2000). Fromextended focus group data, Wilhelm and Thierer (2000) also observed a significantunique ethnicity effect on the level of internet connections.

Going beyond differences in internet access, several studies examined ethnicdifferences in how the internet is incorporated into people’s everyday life. A PewInternet Project’s report, Hispanics and the internet, suggested that online Latinoswere more likely than online whites to search for information about books, moviesand other activities, to download and listen to music, and more likely to go onlinejust for fun (Spooner and Raine, 2001). Latinos were as likely as whites to look fora job, get health and medical information, and get housing information online.These results suggest that Latinos, once online, are as broadly and intenselyconnected to the internet as whites. On the other hand, Wilhelm and Thierer (2000)found that after gaining access to the internet, African Americans and Latinoswere not able to incorporate the technology in a way that would move them up thesocial ladder, especially because of the lack of content on the internet targeted tothese minority groups. According to Wilhelm and Thierer (2000, p. 62), “minoritiesare perceived as marginalized actors in the dominant society’s euphoria overinformation technology, then they too will not see the value in cultivating certainskills and training.”

In contrast to studies showing persistent ethnic effects on the digital divide, otherstudies reported a trend toward “closing ethnic divides.” Unlike their own previousreports, NTIA’s, 2002 report titled “A nation online: how Americans are expandingtheir use of the internet” suggested that the ethnic divide was closing. The reportemphasized that African American and Latino populations showed much higherincreases in adoption rates than white and Asian American populations. A StanfordUniversity study reported that ethnic differences vanished after controlling for incomeand education (Nie and Erbing, 2000). Along the same lines, Novak and Hoffman (1998)found that a significant portion of ethnic differences was explained by income andeducation[4].

As a way to resolve such conflicting results – persistent or closing ethnic divide –we suggest a contextual approach to ethnic effect on internet connectedness. Instead ofusing national-level data that would show ethnic similarities and differences only inabstract term, we suggest examining ethnicity in specific socio-geographic contexts.We conceptualize this approach as a geo-ethnic approach. In the next section, wediscuss the concept of geo-ethnicity in more detail.

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Geo-ethnicityMany social theorists (Castells, 2000; Giddens, 1991, 1999; Thompson, 1995) havesuggested that novel ways of understanding the relationships among place, time, andidentity (e.g. ethnicity) are necessary for comprehending contemporary socialenvironments under the forces of globalization, new communication technologies, andnew population dynamics. In contrast to earlier days when people’s shared history(time) and identity (shared belief and ethnicity) are almost fixed in a certain place, therelationship among the three components – time, place, and identity – in today’severyday life has become more complex and dynamic (Appadurai, 1990). This is thecase especially in mega cities around the world, including many US cities – such asLos Angeles, New York, Chicago, Seattle, and Miami – where population dynamicshave dramatically changed due to new and diverse immigrant groups (Myers, 1999).

In the changing social environment, it is critical to locate individuals in a matrix ofspace/time and identity when examining people’s connections to communicationresources. One of the ways to contextualize people’s connections to communicationtechnologies is to identify the “communication environment” surrounding people’severyday lives. For instance, economic, political, or cultural values that individualsmay evidence in their connections to the internet are likely to be influenced by theircommunication environments characterized by factors of time/space (where they livegeographically) and identity (who they are).

Communication infrastructure theory (Ball-Rokeach et al., 2001) provides concreteways of understanding the ecological relationship between internet connections andcommunication environments by articulating and empirically unveiling the“communication infrastructures” of diverse urban residential environments. Acommunication infrastructure is a storytelling network set in its communicationaction context (Ball-Rokeach et al., 2001). It consists of the everyday conversation, or“storytelling,” that individuals, media, and community organizations produce anddisseminate (the neighborhood storytelling network), and the resources of residentialareas that promote or constrain communication among storytellers (communicationaction context, e.g. parks, schools, safe streets, libraries, etc.). As an entrepreneur has torely upon access to the financial and technical features of an economic infrastructure tobuild a successful business, the individual citizen or family has to have access to aviable communication infrastructure to produce social-, cultural-, and community-levelvalues as well as personal-level values with a new communication technology.

Following this theoretical approach, we propose an ecological and dynamic conceptof ethnicity – what we call “geo-ethnicity”[5] – as a way to examine ethnicity in thecontext of place and time. We define geo-ethnicity as ethnically articulated attitudesand behaviors grounded in a specific temporal and spatial situation. That is,geo-ethnicity is a multilevel phenomenon as individual- or group-level experiencesembedded in a specific geographical, temporal, and cultural context (Eriksen, 1991;Featherstone and Lash, 1999; Flora, 1998; Tilly, 1978). Several scholars have alreadyemphasized the importance of contextualizing ethnicity. Tilly (1978) pointed out thatethnicity is not so much an individual characteristics as it is “labeled connectionsamong people.” Eriksen (1991, 1996) viewed ethnicity as both a formation of interactionand context. According to him, ethnicity is understood as:

. . . a learned and internalized context of shared meaning bounded spatially, temporally, andsituationally which does not presuppose either the existence of “an integrated culture” or that

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of independent individuals developing their mutual understanding from scratch (Eriksen,1991, p. 142).

Fischer’s (1975) works on urban subculture also illustrated the ways in which ethnicityas urban subculture was contextualized by external and internal factors affectingspecific ethnic groups, such as the size of urban places, population size, level ofbetween-group contacts, and level of “urban-ness.”In short, geo-ethnicity is not an attribute that belongs to individuals (Tilly, 1978). Itworks as a social, cultural, and communication “environment” surrounding individualsin a particular time and place. Therefore, geo-ethnicity is a concept that is aimed atbringing community-level analysis to the study of individuals’ adoption and use ofcommunication technology. In the early 1970s, Aiken and Alford (1970, p. 843) pointedout that:

. . . [m]ost of the studies of innovation have used as units of analysis either individuals ororganizations, and little attention has been given to innovation in community systems,although community systems are continually introducing new ideas, activities, processes,and services.

Geo-ethnicity can be used as a conceptual tool that will enable us to examine how anew communication technology is incorporated into individuals’ everyday lives incontext of their community environment.

Methodologically, we suggest that in order to examine the effect of geo-ethnicity onthe levels and types of people’s internet connections, researcher would better usecontextual data that contain information about the local context of ethnic groups –where they live, who they live with, and their cultural, economic, and communicationenvironment: for example, not just Latinos in general but Latinos living in a specificneighborhood. Many digital divide studies employing nation-wide survey data treatethnicity as one of many individual demographic characteristics, without taking intoaccount this context. As a result, such studies are likely to discount local contextinfluences that may interact with ethnicity in affecting people’s internet behavior. Inaddition, the majority of digital divide studies only compare whites andAfrican-Americans and, sometimes, Latinos. Even when other minority groups suchas Asians are included, the sample size is usually too small to generate statisticallymeaningful discussions.

A multidimensional measure of internet connectednessAs more and more people gain access to the internet, we need to expand inquiry byaddressing the types of “connectedness” patterns people develop with the internet. Bypatterns of connectedness, we do not mean the technical aspects of accessing theinternet, but multiple ways in which people build relationships with the internet. Wedeveloped an internet connectedness index (ICI) where “connectedness” is defined as aqualitative and multidimensional relationship between individuals and the internet. ICIis based on the assumption that the digital divide is more than access. Post-access,people and groups exhibit variations in the quality of their access. The ICI is composedof three dimensions (Table I):

(1) history and context of internet connectedness, mostly reflecting conditions ofeconomic disparity;

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(2) scope and intensity of internet connectedness, concerning the depth and breadthof people’s internet connectedness; and

(3) centrality of people’s internet connectedness, focusing on the subjectiveperception of the internet’s importance in people’s lives.

We found that among internet users, higher income and education levels wereassociated with higher ICI scores. In examining the relationship between ICI scores andage, we found that younger people had significantly higher scores in the historyand context dimension and the scope and intensity dimension, while older peopleevidenced centrality dimension scores as high as younger people. These studies haveshown that the ICI has the potential to capture multi-dimensional inequalities reflectedin people’s relationships with the internet.

Research questionsThis study tests the unique effects of ethnicity on individuals’ multidimensionalconnectedness to the internet with the cases of four geo-ethnic samples – Whites,African-Americans, Latinos, and Asians in Los Angeles metropolitan areas. Weexamine four research questions regarding the effects of ethnicity on:

. internet access (whether an individual has internet access or not);

. the context and history;

. the scope and intensity; and

. the centrality dimensions of internet connectedness.

These research questions are tested after controlling for income, education, gender, ageand immigration history. Immigration history is entered as one of the covariatesbecause whether one is a new or an old immigrant is likely to be an important factorinfluencing the extent to which ethnicity affects individuals’ communication behaviors.

In addition to physical access, some ICI dimensions are likely to work aspre-requisites or contributing conditions for other ICI dimensions. For example, thecontext/history dimension is likely to be a pre-requisite condition for the other two ICIdimensions, i.e. those who have broader contexts and longer experience withthe internet are in a better situation to have broader and more intense

Dimensions Items

Context and history Number of years the person owned a home computerNumber of tasks that the person intended to accomplish through theinternet connectionNumber of sites where people have access to the internet

Scope and intensity Number of goals that the person has with respect to going onlineNumber of activities in which the person participates on the internetFrequency of the person’s participation in online interactive activities

Centrality Level of effect the internet has on the person’s personal livesHow much the person would miss his/her computer if it vanished one dayHow much the person would miss the internet if it vanished one day

Table I.Three dimensions of theinternet connected index

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internet connectedness. To observe the unique effect of ethnicity on each ICI dimension,we control for pre-requisite dimensions of internet connectedness, in addition, to thesocio-economic factors mentioned above. For the same reason, we control for ime spentonline in our analyses of the scope/intensity and centrality dimensions.

Our four research questions are:

RQ1. Does ethnicity have a significant effect on having or not having internetaccess, after controlling for income, education, age, gender, and immigrationhistory?

RQ2. Does ethnicity have a significant effect on the context and history of internetconnectedness, after controlling for income, education, age, gender,immigration history, and time spent online?

RQ3. Does ethnicity have a significant effect on the scope and intensity of internetconnectedness, after controlling for income, education, age, gender,immigration history, time spent online, and the context, and historydimension score?

RQ4. Does ethnicity have a significant effect on the centrality of internetconnectedness, after controlling for income, education, gender, age,immigration history, time spent online, the context and history, and thescope and intensity dimension score?

MethodParticipantsA total of 1,812 respondents, composed of 238-321 adults (18 years or older) in each offour areas in Los Angeles participated in this study. The ethnicities and study areasinclude whites in the Westside and South Pasadena, African-Americans in GreaterCrenshaw, Latinos in East LA and Pico Union, and Asians (Korean-origin residents ofKoreatown and Chinese-origin residents of Greater Monterey Park). The residentialplaces of these four ethnic groups are all within 10 miles of the Los Angeles CivicCenter. Table II for the sample characteristics of these ethnic groups.

Research procedureThe survey was administered by telephone using random digital dialing. Thetelephone interviews were conducted in the preferred language of the respondents withspecially trained bilingual interviewers to capture the best possible representation ofan ethnic group in a specific area (especially new immigrant’ areas such as Koreatown,East LA, Pico Union, and Monterey Park). The languages employed in survey datacollection were English, Spanish, Korean, and Chinese (Mandarin and Cantonese). Thedata collection period extended from June 1998 to December1999.

The overall response rate was 31 percent when calculated most conservatively bydividing the number of completed interviews by the number of theoretically eligiblephone numbers. There were differences in response rate among study samples.Mexican-origin and Central American-origin study samples had the highest (41 and40 percent, respectively), and the Westside white sample had the lowest (20 percent)response rate. The overall completion rate (the percent of eligible respondents –targeted ethnicity living in the target area – who completed an interview) was

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62 percent, which ranged from low rates in the Korean-origin (47 percent) andChinese-origin (56 percent) samples to relatively high rates in Mexican-origin andSouth Pasadena white samples (each 73 percent). Although there may have beensample biases due to the response rate, as is the case in other survey research, the basiccharacteristics of our sample show good conformity to the population characteristics inthese areas.

MeasuresInternet access was measured by asking: “Do you have an internet connection, whetherit be home, work, school or other places?” The areas differed significantly from a63 percent access rate in White areas, 53 percent among Chinese respondents,44 percent in Crenshaw African-Americans, 38 percent in Koreatown, 17 percentamong Central Americans living in Pico Union, and 16 percent among East LAMexican-origin residents.

The ICI consists of three dimensions and nine items. The dimensions were derivedfrom an exploratory factor analysis. Since, the ICI measure presumes at least minimalaccess to the internet, it was administered only among the subset of respondents whohave any level of internet access (n ¼ 770).

As previously noted, the three ICI sub-indices are:

(1) history and context of internet connectedness;

(2) scope and intensity of internet connectedness; and

(3) the centrality of internet connectedness.

Ethnic groups

WhitesAfrican-Americans Latinos Asians

LA sub-areasSouthPasadena Westside

GreaterCrenshaw

East LosAngeles

PicoUnion

GreaterMontereyPark

GreaterKoreatown

N ¼ 251 N ¼ 250 N ¼ 252 N ¼ 250 N ¼ 250 N ¼ 321 N ¼ 238Householdincome(mean $) 61,000 72,000 42,000 27,500 20,000 30,950 35,000Percentage, ¼ $35,000 17 11 47 81 90 57 59Percentage. ¼ $75,000 38 52 16 2 1 12 9

Level ofeducationPercentage , ¼high school 8 8 28 75 79 40 34Percentage . ¼college grad. 66 69 37 8 6 41 53Median age 45 47 42 34 33 41 35Percent female 57 55 60 60 55 51 52

Table II.Profiles of study samples

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History and context of internet connectedness consists of three items: home computerhistory, task scope, and site scope. Home computer history is operationalized as thenumber of years a person has owned a PC at home. Task scope concerns the number oftasks for which a person connects to the internet. Respondents were asked whetherthey connect to the internet for work-related, school-related, and personal-related tasks.The answers to these three questions were aggregated to reflect the breadth of tasks.Site scope was created by adding up the number of places where a person connects tothe internet, which includes home, work, school, a community center or organization, apublic library, and a cybercafe or commercial places proving internet connection suchas Kinko’s. Reliability analysis of this sub-index yielded an a of 0.84.

Scope and intensity of internet connectedness concerns the goals that motivateinternet connections, and the breadth and depth of online activities. The three itemsthat constitute this sub-index are goal scope, activity scope, and time spent oninteractive online activities. Goal scope was derived by asking how many of six goalsrespondents pursued by participating in online activities. The six response categorieswere derived from the Media System Dependency Scale (Ball-Rokeach, 1985, 1998;Grant et al., 1991; Loges, 1994). It included two understanding goals: to stay on top ofevents and groups that you care about (social understanding) and to express yourselfor your opinions (self-understanding); two orientation goals: to accomplish business,financial, or work tasks (action orientation) and to get advice on how to deal with otherpeople such as doctors and other health professionals (interaction orientation); and twoplay goals: to play or amuse yourself (self-play), and for social reasons such as makingnew friends (social play).

Activity scope was measured by counting the number of affirmative answers inresponse to the question “What internet or web activities do you participate in, otherthan e-mail?” Response categories were bulletin boards; chat rooms or IRC;MUDs/MOOs/MUSHs; game playing/online gaming; mailing lists;newsgroups/USENET; research/information; shopping; and surfing the web. Therange of this activity scope measure was 0-10.

Time spent on interactive online activities reflects the intensity of people’sconnectedness to interactive online activity through their response to the question “Notcounting personal e-mail, how often do you participate in any online activitiesinteracting with other people (such as newsgroups, bulletin boards, chat rooms, MUDs,game-playing)?” Reliability analysis of the scope and intensity sub-index produced ana of 0.94.

The third sub-index is the centrality of internet connectedness. Centrality is thedegree to which a certain medium is embedded into one’s everyday life in the ecologyof other co-existing communication media. In the case of internet connectedness,centrality indicates perceived importance of the internet in a person’s communicationenvironment. The centrality dimension of the ICI includes positive evaluation of theinternet’s effects on one’s personal life, computer dependency relations, and internetdependency relations. The first item, positive valuation of the internet’s effects onpersonal life, is based on a survey question asking whether the internet has a positiveor negative effect on the respondent’s life.

The second and third items, computer dependency relations and internetdependency relations, were derived from responses to the question:

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Imagine that you woke up tomorrow to find that the computer/internet had vanished. Usingthe ten point scale where “1” means you wouldn’t miss it at all because your daily life couldproceed as normal and “10” means you would miss it in an extreme amount, how much wouldyou miss being able to use your computer/go online?

This item encompasses people’s cognitive, affective and evaluative perceptions aboutthe internet, and directly captures the subjective centrality of computers or the internetin people’s everyday lives. Reliability analysis of the items in this sub-index produced amarginally acceptable a of 0.66[6].

Time spent online was measured by asking respondents “Including e-mail,approximately how many hours did you spend on the internet last week?” Educationallevel was measured by asking respondents the highest grade or year of school theycompleted. Seven response categories ranged from eighth grade or less to having agraduate degree. Income was measured as the combined income of all householdmembers from all sources for the previous year. Area means (mean income of specificgeo-ethnic group) were used to replace missing values when respondents did not reporthousehold income. Age of the respondents was determined by asking them to statetheir age on their last birthday. Frequency distributions were run to determine fivenaturally forming age categories. Gender was coded into 0 (female) and 1 (male).Immigration generation was measured by asking: “Who in your family first came tothe United States?” The four response categories ranged from first generation (child,niece, nephew, me, spouse, siblings), second (parents, aunts, uncles, etc.), third (grandparents) and fourth and more (great grand parents or earlier) generations.

AnalysisLogistic regression and analysis of covariance (ANCOVA) were employed to determinewhether there would be differences among the various geo-ethnic groups with regardto internet access and each of ICI dimensions. To compare internet access and ICIdifferences among the study areas, z tests for proportions were used. The covariates ofage, income, education, gender, and immigration generation were held constant toderive the unique effects of ethnicity. In addition, for the tests of scope/intensity andcentrality dimensions of internet connectedness, time spent online and context/historydimension scores were entered as covariates in addition to income, education, age,gender, and immigration history. For the same reason, a scope/intensity dimensionscore was added to the group of covariates to test for the effect of ethnicity oncentrality of internet connectedness.

ResultsMost of the socio-economic status variables such as income, education, age, and genderwere significant factors explaining individuals’ internet access: males are more likelyto have an internet access than females; both income and education have positiveeffects on having an internet access; and the younger, the more likely to get connectedto the internet (Table III).

Logistic regression analysis revealed differences in the nature of internetconnections among the four geo-ethnic groups after controlling for income,education, age, gender, and immigration generation (RQ1) (Table IV). Whites hadthe highest likelihood of having internet access, followed by Asians and AfricanAmericans. Latinos had the lowest likelihood of being connected to the internet.

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Regarding the effect of ethnicity on internet connectedness, we first examinedwhether ethnicity had a unique effect on the context/history dimension of the ICI(RQ2). As shown in Table V, an ANCOVA test indicated that ethnicity had asignificant effect on the context/history dimension of the internet connectedness aftercontrolling for income, education, age, gender, and immigration history (F ¼ 14.50,df ¼ 3, p , 0.001). In addition to the overall effect, pair-wise comparisons between thefour ethnic groups regarding each ICI dimension were conducted (Table VI). Asiansand whites showed the highest score on the context and history dimension with nosignificant difference between them. These two groups were followed by AfricanAmericans living in Greater Crenshaw while Latinos living in either East Los Angelesor Pico Union had the lowest average context/history dimension score.

In addition to ethnic group membership, income, education, and age weresignificant correlates of the context/history dimension; the younger, and higher thelevels of income and education, the more likely individuals are to have high scores inthe context/history dimension of the internet connectedness. Gender and immigrationhistory, on the other hand, were not significant factors.

Third, we tested whether ethnicity made a significant difference in thescope/intensity dimension of the ICI, again controlling for income, education, age,gender and immigration history (RQ3). In this case, we also employed thehistory/context dimension score and the amount of time spent online as covariates

Variable B S.E. Wald Df Sig. R Exp (B)

Age 20.82 0.05 236.734 1 * * * 20.37 0.44Gender 0.43 0.12 12.59 1 * * * 0.08 1.54Income 0.23 0.04 34.25 1 * * * 0.13 1.25Education 0.48 0.05 100.08 1 * * * 0.24 1.61Immigration history 0.02 0.05 0.29 1 Ns 0.00 1.02Ethnic groupa 60.98 3 * * * 0.18White 1.62 0.2 47.37 1 * * * 0.16 5.04Black 1.17 0.25 22.34 1 * * * 0.11 3.22Asian 1.29 0.19 48.73 1 * * * 0.16 3.65Constant 21.94 0.24 66.71 1 * * *

Note: aThe Latino group was used a reference

Table IV.Logistic regressionanalysis of internet

access

Home computer (percentage) Internet connection (percentage)

White/Jewish in the Westside 0.58 0.64White/Protestant in South Pasadena 0.53 0.64African Americans in Crenshaw 0.53 0.45Latinos in East LA 0.26 0.17Latinos in Pico Union 0.29 0.18Asians (Korean) in Koreatown 0.51 0.38Asians (Chinese) in Monterery Park 0.75 0.60Grand Mean 0.52 0.44

Table III.Three dimensions of theinternet connected index

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as these two factors were likely to have a significant influence on scope/intensitydimension. The overall effect of ethnic membership on the scope/intensity dimensionwas not statistically significant (Table VII). However, looking more closely at pair-wisedifferences between the four ethnic groups as shown in Table VI, a significantdifference was found between the Latino and the Asian groups. Latinos were connectedto the internet in broader and more intense ways than Asians when controlling forincome, education, age, gender, immigration history, the scope/history dimension, andtime spent online. Among the covariates, only age (younger) and time online hadsignificant positive effects on the scope/intensity dimension.

Fourth, we examined the effect of ethnicity on the subjective dimension, thecentrality of the internet connectedness (RQ4). In addition to the SES variables,context/history and scope/intensity dimension scores, and time spent online were

Source of variation SS Df MS F PModel 810.06 8 810.06 23.36 0.000Error 3,298.57 761 3,298.57Total 66,929.44 770CovariatesIncome 121.63 1 121.63 28.06 0.000Education 108.17 1 108.17 24.95 0.000Age 67.96 1 67.96 0.000Gender 16.29 1 16.29 3.76 NsImmigration history 2.17 2.17 0.50 NsMain effectsEthnicity 188.58 3 62.86 14.50 0.000R 2 ¼ 0.20Grand mean ¼ 9.03Group N Adjusted meanWhite 316 9.31African-American 111 8.63Asian 258 9.33Hispanic 85 7.64

Table V.ANCOVA: context andhistory of internetconnection by ethnicity(income, education, ageand gender, immigrationhistory controlled)

Mean differenceEthnicity Context and history Scope and intensity Centrality

White Black 0.68 * * * 20.39 0.59 *

Asian 20.01 20.01 0.67 * *

Latino 1.67 * * * 20.79 0.17Black White 20.68 * * 0.39 20.59 *

Asian 20.70 * 0.37 0.07Latino 0.98 * * 20.40 20.42

Asian White 0.01 0.01 20.67 * *

Black 0.70 * 20.37 20.07Latino 1.69 * * * 20.77 * 20.50

Latino White 21.67 * * * 0.79 20.17Black 20.98 * * 0.40 0.42Asian 21.69 * * * 0.77 * 0.50

Table VI.Pairwise comparisonamong ethnic groups inthe dimensions of internetconnectedness

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controlled for in the analysis. As shown in Table VIII, a significant effect of ethnicityon centrality of the internet connectedness was found. With regard to pair-wisecomparisons (Table VI), whites express significantly higher internet centrality thanAsian and African-American respondents. Interestingly, the Latino centrality scorewas not significantly different than that of whites. Among the covariates, higher

Source of variation SS Df MS F PModel 796.06 10 796.06 11.35 0.000Error 5,255.39 749 5,255.39Total 6,051.45 759 6,051.45CovariatesIncome 9.04 1 9.04 1.29 NsEducation 24.41 1 24.41 24.41 NsAge 210.38 1 210.38 29.98 * * *

Gender 0.18 1 0.18 0.03 NsImmigration history 13.03 1 13.03 1.86 NsContext of history 2.98 1 2.98 0.43 NsTime online 285.07 1 285.07 40.63 * * *

Main effectsEthnicity 38.73 3 38.73 1.84 NsR 2 ¼ 0.13Grand mean ¼ 8.56Group N Adjusted meanWhite 313 8.21African-American 108 8.89Asian 256 8.56Hispanic 83 9.42

Table VII.ANCOVA: scope and

intensity of internetconnection by ethnicity(income, education, age

and gender, immigrationhistory controlled)

Source of variation SS Df MS F pModel 1,145.79 11 1,145.79 22.06 0.000Error 3,530.20 748 3,530.20Total 4,675.39 759 4,675.39CovariatesIncome 0.03 1 0.03 0.01 NsEducation 42.29 1 42.29 8.96 * *

Age 1.26 1 1.26 0.27 NsGender 10.66 1 10.66 2.26 NsImmigration history 0.24 1 0.24 0.05 NsContext and history of internet connect 83.58 1 83.58 17.71 * * *

Scope and intensity of internet connect 1.82 1 1.82 0.39 NsTime online 521.56 1 521.56 110.51 * * *

Main effects 1Ethnicity 57.16 3 19.05 4.04 * *

R 2 ¼ 0.25Grand mean ¼ 7.96Group N Adjusted meanWhite 313 8.29African-American 108 7.69Asian 256 7.62Hispanic 83 8.12

Table VIII.ANCOVA: centrality ofinternet connection by

ethnicity (income,education, age and

gender, immigrationhistory controlled)

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education, a higher context/history dimension score and more time spent online hadsignificant positive effects on the centrality dimension of internet connectedness.

DiscussionThe research findings indicate that ethnicity is a unique contributing factor in thedynamics of the digital divide in Los Angeles metropolitan areas. Ethnicity has aneffect not only on the quantitative question of having internet access, but also withrespect to the qualitative dimensions of the ICI – context/history, scope/intensity, andcentrality. This finding generally holds after controlling for individual’ssocio-economic status variables (income, education, age, gender, and immigrationhistory). Although a large portion of the digital divide can be attributed to individuals’socio-economic characteristics, our results consistently indicate that ethnicity has aunique effect on whether and how individuals connect to the internet. From thecommunication infrastructure perspective, ethnic differences in internet connectednessshould be examined in context of the existing communication environments in whichdifferent ethnicities lead their everyday lives. In the following paragraph, we willdiscuss our findings with more in-depth contextual information about the four ethnicgroups in Los Angeles.

The four ethnic groups are sampled from seven sub-areas in Los Angeles that varyin the extent to which the larger communication infrastructure facilitate or constrainthe level of internet connection. For example, when we counted the number of placesfor getting internet and other telecommunication services such as Kinkos, we foundthat Koreatown, East LA (Latino area) and Crenshaw (African-American area) do nothave any Kinkos in their areas, while there are five Kinkos in the white areas (four inthe Westside and one in South Pasadena). On the other hand, a different kind ofcommercial internet service is available and popular in Asian communities in LosAngeles such as Koreatown and Monterey Park. The internet cafes, or PC Bang inKorean, are flourishing in these Asian American neighborhoods, providing cheapinternet services to young residents (Graham, 2002). These cybercafes are equippedwith computers with high-speed broadband internet connections to provide youngpeople in these neighborhoods with the optimum environment for playing onlinegames. These different types of internet service providing agents, which are part of thelarger communication infrastructures, illustrate the geo-ethnic variation in availabilityof communication resources and cultural bias to the ways in which suchcommunication resources are used.

Aside from the physical characteristics of a place, individuals who reside andcongregate there collectively influence the area’s communication infrastructure. Peoplein an ethnic enclave are likely to share particular internet-related goals, such as a desirefor getting services in their native language, maintaining connections to people in theircountry of origin, and a desire for internet applications that are particularly popularin certain culture. That is, the ways in which ethnic factors influence people’s internetconnectedness are understood in specific residential settings in which different ethnicgroups maintain different socio-cultural relationships within their residential areas andbeyond, especially the country of origin. For example, much higher internet accessrates among Asians compared to Latinos of similar socioeconomic status can beattributed partly to the different internet diffusion rates and connection patterns intheir countries of origin – Asian countries having much higher internet penetration

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rates than Latino countries (Cohen et al., 2003; Netvalue, 2000; Nielsen/NetRatings,2001).

Our comparisons of the four ethnic groups provide an interesting illustration in thisregard. The Latino sample had the lowest rate of internet access, spent the leastamount of time online, and had the lowest average score in the history/contextdimension of ICI. However, their average score for the scope/intensity dimension of ICIwas significantly higher than the Asian sample when socio-economic status, thehistory/context dimension, and time spent online were held constant.

Looking at the state of communication infrastructure in the Latino communities inLos Angeles, a high level on the scope/intensity dimension of the ICI may reflect therelatively sparse availability of economic, cultural and communication resourcesavailable in their areas. According to our focus group study that was conducted withsub-samples of our survey respondents, Latino respondents mentioned the lack ofquality goods and services as one of the most serious problems in their neighborhoods.For example, there is no shopping mall with major department stores, no good qualitygrocery stores, and even no first-run movie theater in their neighborhoods. This meansthat the residents in the areas have to go out of their own neighborhoods to get a broadrange of economic and cultural goods and services. Seen from the communicationinfrastructure perspective, a lack of economic, cultural, and communication resourcesin these areas could make the internet a very important tool. More generally, ICI highscope and intensity would be expected in areas where important goals cannot beachieved without going out of one’s residential area.

The white and Latino samples exhibited significantly higher levels of internetcentrality than the Asian and African American samples, after controlling forsocio-economic variables, time spent online, the history/context dimension, and thescope/intensity dimension. This high centrality scores imply that whites and Latinosmay have incorporated internet-related capabilities more deeply into the conduct oftheir everyday personal, family, and work lives in the pursuit of economic, social, andcultural capital (Becker, 1999; Bourdieu, 1986; Coleman, 1988). Such pursuits engage acentral relationship with the internet regardless of how intensely or broadly connectedor how much time they spend on the internet.

The centrality is related to the types of goals individuals seek on the internet. Forexample, if the internet is used for work-related goals or economic transactions, it islikely to play a central role in people’s lives. On the other hand, in the lives of peoplewho use the internet only for the purpose of, for example, games, the internet is lesslikely to be in a central part of people’s lives no matter how much time they spendonline. To apply our operational definition of centrality, the possible disappearance ofthe internet is likely to be taken more seriously for the former than the latter group ofpeople. According to an additional analysis with our survey items, we found that whiterespondents connected to the internet more for business and finance related goals,while Asians and African Americans connected more for entertainment related goals.

Latinos’ high centrality score also seems to demonstrate that once a physical accessto the internet is provided and skills and motivations for internet uses are developed,Latinos are ready to place the internet in a central part of their lives and use the newcommunication technology for getting access to critical resources for their lives in theUSA such as jobs, health, or social connectedness. Thus, even though Latinos andwhites show similar levels of internet centrality, it seems that the reasons behind them

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are different between these two ethnic groups. While whites place the internet in acentral part of their lives to reinforce their existing connections to social, economic, orcultural resources, Latinos may do it because internet might be the only way to haveaccess to critical information, knowledge, or basic resources in their local environmentscharacterized by the lack of such resources.

It seems that our study brings up some concerns about Asian andAfrican-American communities in terms of their capacity to incorporate the internetto produce social, economic, and cultural values. Even if our Asian respondents spentmore time online than any other ethnic groups included in this study, and their score ofthe history/context dimension of the ICI was the highest, this advantage was notcarried to the intensity/scope and the centrality of the ICI. From the communicationinfrastructure perspective, it partially reflects a low level of integrity among theirconnections to various locally-based communication resources. In our previous studywhich used the same data, we found that Asian communities are behind other ethniccommunities in terms of the level of integrity of their neighborhood storytellingnetwork (composed of connections to local media, community organizations, and otherresidents) and the level of community engagement. Such unstable nature ofcommunication infrastructure in these new immigrant areas might make it hard fortheir residents to incorporate the internet into their everyday activities, includingeconomic or business transactions that are likely to be carried on in their local areas.

Our results indicated that African-Americans in our study lagged behind otherethnic groups in all three dimensions of their internet connectedness. In our previousstudy, this same African-American community showed the highest level of attachmentto their neighborhood compared to other ethnic communities in Los Angeles despitetheir low level of income and education. In such a high social capital (i.e. mutual trustand social connectedness among neighbors) and low economic/human capital (i.e. lowincome and education) area, it may be possible that African-Americans are more likelyto go to their social and neighborly networks to achieve their everyday goals ratherthan developing skills to use new tools which require the investment of economic andeducational resources and time.

This suggests that the ways in which the internet is incorporated into people’severyday lives are likely to differ by geo-ethnic areas: for example, ourAfrican-American area, with high social capital and low economic/human capitals,showing different internet connectedness patterns from the white areas where bothsocial and economic/human capitals are high, and also from the Latino areas whereboth social and economic/human capitals are low. This way, the level of social capitalis likely to interact with other communication resources available in specific areas toaffect people’s internet connectedness. This interpretation implies that policy makersand practitioners working on the digital divide issue should understand differentdynamics of social and communication resources in different areas.

The findings of this study present several implications for the ethnic digital dividein metropolitan areas in the USA. First of all, it provides evidence that the digitaldivide, especially ethnic digital divide, is not closing, in contrast to what theDepartment of Commerce’s 2002 report and others have recently claimed. Rather, ourstudy shows that ethnicity combined with a locale continues to be a significant factorinfluencing ways in which individuals maintain their relationships with the internet.The claim that different ethnic groups show similar patterns of internet use once they

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go online (Nie and Erbing, 2000) is also challenged by the results presented in thisstudy. The findings reported here suggest that policy makers and practitionersworking on the digital divide issue should understand various communicationresources in specific geo-ethnic areas, in addition to the individuals’ internet usepatterns. When developing a program to help residents have a more productiveconnection to the internet in different communities, the distinct “communicationinfrastructures” of different areas, and ethnic compositions of the areas should be wellunderstood. The understanding of geo-ethnic characteristics of specific communitieswill be particularly necessary when discussing how different socio-cultural groupsconnect to the internet. Such environmental factor will continue to intervene in theprocess of incorporating the internet and other communication technologies intoindividuals’ everyday lives.

Notes

1. Both Hispanics and Latinos are used in the USA to refer to immigrants from Mexico andother central or South American countries while the term “Hispanics” has been used as anofficial one used by the US Governments. However, as scholars and Latino (or Hispanic)communities have criticized the lable “Hispanic” as racist. We use the label Latino in ourpaper. For more discussion of this issue, see Alcoff (2005) and Layes-Bautista (1980).

2. In the context of this paper, we understand everyday life as “family relation, routines,cultural practices, and spaces” (Lister, 2003, p. 221) through which people make sense of thenew media technologies and build unique ways to connect to them.

3. According to Omi and Winant (1994, p. 9), this way of thinking – i.e. ethnicity is what peoplehave to overcome in order to modernize their lifestyles – can be traced back to the greatsocial theorists of the nineteenth century, such as Marx, Weber and Durkheim who sawracial and ethnic bonds, divisions, and conflicts as remnants of pre-industrial socialformations which would become less significant as modernity took place.

4. The gap between Whites and African Americans with regard to the PC ownership isexplained by income, while the gap between these two ethnicities in terms of work relatedcomputer access is explained by education. That is, ethnicity is not a significant factor whencontrolling for income and education, respectively. However, education did not explain PCownership, and income did not explain work computer access. Differences between Whitesand African American in “use” or on-line activities are mostly explained by internet history(i.e. number of years using the internet). Although they put a large focus on the ethnic divide,Novak and Hoffman devote their analyses to finding other variables that can explain awayethnic differences. They do not pursue the question of what the ethnic differences meanindependent of other socio-economic factors.

5. The term geo-ethnicity has already been used by anthropologists (Bhagabati, 1982) todescribe the impact of natural and physical environments on ethnic identity andcharacteristics of tribal people.

6. To further test the dimensional structure of the ICI, exploratory factor analysis wasperformed. Three factors emerged (with eigenvalues greater than one), accountingcollectively for 70 percent of the variance. An oblique factor analysis, in which factors areallowed to correlate with one another, is reasonable in this case, where it is expected that thethree subdimensions of internet connectedness are related to each other (i.e. as parts ofa larger concept). Allowing the factors to rotate clarifies the distinction between the factorloadings of items in each factor. Each item loaded in its predicted factor, with rotated factorloadings in excess of 0.6 in all cases.

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References

Aiken, M. and Alford, R.R. (1970), “Community structure and innovation: the case of publichousing”, The American Political Science Review, Vol. 64 No. 3, pp. 843-64.

Albarran, A.B. and Umphrey, D. (1993), “An examination of television motivations and programpreferences by Hispanics, Blacks, and Whites”, Journal of Broadcasting & ElectronicMedia, Vol. 37 No. 1, pp. 95-103.

Albarran, A.B. and Umphrey, D. (1994), “Marketing cable and pay cable services: impact ofethnicity, viewing motivations, and program types”, Journal of Media Economics, Vol. 7No. 3, pp. 47-58.

Alcoff, L.M. (2005), “Latino vs. Hispanic: the politics of ethnic names”, Philosophy & SocialCriticism, Vol. 31, pp. 395-407.

Appadurai, A. (1990), “Disjuncture and difference in the global cultural economy”, Public Culture:Bulletin of the Center for Transnational Cultural Studies, Vol. 2 No. 2, pp. 1-24.

Attewell, P. (2001), “The first and second digital divides”, Sociology of Education, Vol. 74,pp. 252-9.

Ball-Rokeach, S.J. (1985), “The origins of individual media system dependency: a sociologicalframework”, Communication Research, Vol. 12, pp. 485-510.

Ball-Rokeach, S.J. (1998), “A theory of media power and a theory of media use: different stories,questions, and ways of thinking”, Mass Communication & Society, Vol. 1 Nos 1/2, pp. 5-40.

Ball-Rokeach, S.J., Kim, Y.C. and Matei, S. (2001), “Storytelling neighborhood: paths to belongingin diverse urban environments”, Communication Research, Vol. 28 No. 4, pp. 392-428.

Becker, L.B., Kosicki, G.M. and Jones, F. (1992), “Racial-difference in evaluations of the massmedia”, Journalism Quarterly, Vol. 69 No. 1, pp. 124-34.

Becker, P.E. (1999), Congregations in Conflict: Cultural Models of Local Religious Life, CambridgeUniversity Press, New York, NY.

Bhagabati, A.C. (1982), “Emergent tribal identity in North-East India”, in Chaudhuri, B. (Ed.),Tribal Development in India: Problems and Prospects, Inter-India Publications, Delhi.

Bourdieu, P. (1986) in Richardson, J. (Ed.), Handbook of Theory and Research for the Sociology ofEducation, Greenwood Press, New York, NY, pp. 241-58.

Carroll, R.L., Silbergleid, M.I., Beachum, C.M., Perry, S.D., Pluscht, P.J. and Pescatore, M.J. (1993),“Meanings of rado to teenagers in a niche-progarmming era”, Journal of Broadcasting &Electronic Media, Vol. 37 No. 2, pp. 159-76.

Castells, M. (2000), The Rise of the Network Society, 2nd ed., Malden, Blackwell, MA.

Children’s Partnership (2000), Online Content for Low-income and Underserved Americans: TheDigital Divide’s New Frontier, Children’s Partnership, New York, NY.

Cohen, E.L., Ball-Rokeach, S.J., Jung, J-Y. and Kim, Y.C. (2003), “Storytelling civic actions afterSeptember 11th”, in Noll, M. (Ed.), Crisis Communications: Lessen from September 11th,Rowman & Littlefield Publishers Inc., Lanham, MD, pp. 31-44.

Coleman, J.S. (1988), “Social captial in the creation of human capital”, American Journal ofSociology, Vol. 94, pp. 95-120.

Dutton, W., Sweet, P.L. and Rogers, E.M. (1989), “Socioeconomic status and the early diffusion ofpersonal computing in the United States”, Social Science Computer Review, Vol. 7, pp. 266-7.

Eriksen, T.H. (1991), “The cultural contexts of ethnic differences”, Man, Vol. 26 No. 1, pp. 127-44.

Eriksen, T.H. (1996), “Culture, class and connections”, American Journal of Sociology, Vol. 102No. 1, pp. 217-51.

ITP20,3

300

Featherstone, M. and Lash, S. (1999), Space of Culture: City-Nation-World, Sage, London.

Fischer, C.S. (1975), “The study of urban community and personality”, Annual Review ofSociology, Vol. 1, pp. 67-89.

Fischer, C.S. (1992), America Calling: A Social History of the Telephone to 1940, University ofCalifornia Press, Berkely, CA.

Flora, J.L. (1998), “Social capital and communities of place”, Rural Sociology, Vol. 63 No. 4,pp. 481-506.

Giddens, A. (1991), Modernity and Self-Identity: Self and Society in the Late Modern Age,Stanford University Press, Stanford, CA.

Giddens, A. (1999), Runaway World: How Globalization is Reshaping Our Lives, Profile Books,London.

Graham, J. (2002), “Cybercafes serve an explosive brew”, USA Today, February 7, p. 1D.

Grant, A.E., Gutherie, K.K. and Ball-Rokeach, S.J. (1991), “Television shopping: a media systemdependency perspective”, Communication Research, Vol. 18 No. 6, pp. 773-98.

Greeley, A.M. (1974), “Political participation among ethnic groups in teh United States:a preliminary reconnaissance”, American Journal of Sociology, Vol. 80 No. 1, pp. 170-204.

Greenberg, B. and Dervin, B. (1970), “Mass communication among the urban poor”, PublicOpinion Quarterly, Vol. 34 No. 2, pp. 224-35.

Hoffman, D.L., Novak, T.P. and Schlosser, A.E. (2000), “The evolution of the digital divide: howgaps in internet access may impact electronic commerce”, Journal of Computer MediatedCommunication, Vol. 5 No. 3.

Holms, T.E. (1997), “Seeing a future with more blacks exploring the internet”, USA Today,February 18.

Jung, J-Y., Qiu, J.L. and Kim, Y.C. (2001), “Internet connectedness and inequality: beyond the“divide”, Communication Research, Vol. 28 No. 4, pp. 507-35.

Layes-Bautista, D.E. (1980), “Identifying ‘Hispanic’ populations: the influence of researchmethodology upon public policy”, American Journal of Public Health, Vol. 73, pp. 353-6.

Lerner, D. (1958), The Passing of Traditional Society: Modernizing the Middle East, The FreePress, New York, NY.

Lien, P-T., Conway, M.M. and Wong, J. (2004), The Politics of Asian Americans: Diversity andCommunity, Routledge, New York, NY.

Lister (2003), New Media: A Critical Introduction, Routledge, London.

Loges, W.E. (1994), “Canaries in the coal mine: perceptions of threat and media systemdependency relations”, Communication Research, Vol. 21 No. 1, pp. 5-23.

Morino Institute (1995), From Access to Outcomes: Raising the Aspirations for TechnologyInitiatives in Low-income Communities, Morino Institute, Ruston, VA.

Myers, D. (1999), “Demographic dynamism and metropolitan change: comparing Los Angeles,New York, Chicago, and Washington, DC”, Housing Policy Debate, Vol. 10 No. 4, pp. 915-54.

NTIA (1995), Falling through the Net: A Survey of the “have-nots” in Rural and Urban American,Department of Commerce, Washington, DC.

NTIA (1999), Falling through the Net: Defining the Digital Divide, Department of Commerce,Washington, DC.

NTIA (2000), Falling through the Net: Towards Digital Inclusion, Department of Commerce,Washington, DC.

Effects ofethnicity

301

NTIA (2002), A Nation Online: How Americans are Expanding their Use of the Internet,Department of Commerce, Washington, DC.

Netvalue (2000), “Singapore and Korea lead Asia in web usage”, available at: www.infowar.com/survey/00/survey_090600a_j.shtml

Newhagen, J.E. (1994), “Media use and political efficacy: the suburbanization of race and class”,Journal of American Society for Information Science, Vol. 45 No. 6, pp. 386-94.

Nie, N.H. and Erbing, L. (2000), Internet and Society: A Preliminary Report, Stanford Institute forthe Quantitative Study of Society, Stanford, CA.

Nielsen/NetRatings (2001), “South Korea and Taiwan dominates Asian internet usage”, availableat: www.eratings.com/news/20010308.htm

Norris, P. (2002), Digital Divide: Civic Engagement, Information Poverty, and the InternetWorldwide, Cambridge University Press, New York, NY.

Novak, T.P. and Hoffman, D.L. (1998), “Bridging the racial digital divide on the internet”, Science,April 17.

Omi, M. and Winant, H. (1994), Racial Formation in the United States: From the 1960s to the1990s, 2nd ed., Routledge, New York, NY.

Park, R.E. (1915), “The city: suggestions for the investigation of human behavior in an urbanenvironment”, American Journal of Sociology, Vol. 20, pp. 577-612.

Park, R.E. (1923), “The natural history of the newspaper”, Journal of Sociology, Vol. 24 No. 3,pp. 273-89.

Pew (2001a), Asian-Americans and the Internet: The Young and the Connected, Pew Internet &American Life Project, Washington, DC.

Pew (2001b), More Online, Doing More: 16 Million Newcomers Gain Internet Access in the LastHalf of 2000 as Women, Minorities, and Families with Modest Incomes Continue to SurgeOnline, Pew Internet & American Life Project, Washington, DC.

Portes, A. and Zhou, M. (1992), “Gaining the upper hand: economic mobility among immigrantand domestic minorities”, Ethnic and Racial Studies, Vol. 15 No. 4, p. 491.

Ribisl, K.M., Winkleby, M.A., Fortmann, S.P. and Flora, J.A. (1998), “The interplay ofsocioeconomic status and ethnicity on Hispanic and White men’s cardiovascular diseaserisk and health communication patterns”, Health Education Research, Vol. 13 No. 3,pp. 407-17.

Rogers, E.M. (1995), Diffusion of Innovation, 4th ed., The Free Press, New York, NY.

Spooner, T. and Raine, L. (2001), Hispanics and the Internet, Pew Internet & American LifeProject, Washington, DC.

Subervi-Velez, F.A., Berg, C.R., Constantakis-Valdes, P., Noriega, C., Rios, D.I. and Wilkinson,K.T. (1994), “Mass communication and Hispanics”, in Padilla, F. (Ed.), Handbook of

Hispanic Cultures in the United States: Sociology, Arte Publico Press, University ofHouston, Houston, TX, pp. 304-57.

Thompson, J.B. (1995), The Media and Modernity: A Social Theory of the Media, StanfordUniversity Press, Stanford, CA.

Tilly, C. (1978), From Mobilization to Revolution, Addison-Wesley, Reading, MA.

Wilhelm, A.G. and Thierer, A.D. (2000), “Symposium: many sectors of society technicallydisadvantaged”, Insight on the News, Vol. 16 No. 33.

ITP20,3

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About the authorsYong-Chan Kim (PhD, University of Southern California) is an Assistant Professor of HealthCommunication in the Department of Community and Behavioral Health at the College of PublicHealth at the University of Iowa. Yong-Chan Kim is the corresponding author and can becontacted at: ykim2000@gmail.com; yong-chon-kim@uiowa.edu

Joo-Young Jung (PhD, University of Southern California) is a Research Professor at theUniversity of Tokyo. E-mail: jungjy@yahoo.com

Sandra J. Ball-Rokeach (PhD, University of Washington) is a Professor and the PrincipalInvestigator of the Metamorphosis project at the Annenberg School for Communication at theUniversity of Southern California. E-mail: ballrok@usc.edu

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