Abstract

Keywords: wireless Internet, social interactions, face-to-face relationship, Internet use in public spaces

Introduction

As computer and the Internet have permeated everyday life, communication through the Internet has been a common activity of Internet users (Hampton, 2007). The Internet provides convenient channels to increase social contacts with others. Online interaction facilitated by digital connection creates a situation in which users negotiate their time online with “real-life” socializing. In addition, the spread of social media helps people traverse online and offline social relationships through online interactions. Studies of how the Internet influences individuals’ social relationships have presented contrasting results. Some studies found that Internet use created new relationships and maintained or strengthened existing social ties (Robinson, Kestnbaum, Neustadtl, & Alvarez, 2000; Kraut et al., 2002; Hampton & Wellman, 2003). Other studies showed that Internet use contributed to a decrease in the size of people’s social circles because time using the Internet reduced social activities and face-to-face interaction (Kraut, et al, 1998; Nie, Simpser, Stepanikova, & Zheng, 2005).

Ubiquitous wireless Internet access adds a new dimension to the question of how the Internet may influence the structure of social relationships. One significant change of the modern computer network is an increase in wireless access to the Internet in various places. As of April 2009, nearly 56% of Internet users have logged onto the Internet on a wireless connection either at home, at work, or someplace else (Horrigan, 2009). This means that more than half of Internet users, mainly using laptops or other mobile devices, have surfed the Internet or checked e-mail by means of a Wi-Fi connection or a cell phone network. Horrigan (2009) reports that those who rely on wireless access as their means of connecting to the Internet often develop different behaviors than their wired counterparts. In particular, Wi-Fi makes it possible to integrate intensive Internet use with the use of urban public space (Hampton & Gupta, 2008). According to Hampton and Gupta (2008), public spaces play a unique role in shaping and maintaining social networks, opinions and democracy. Thus it is relevant to examine how wireless Internet use influences social relationships, when personal Internet use penetrates into public spaces.

The goal of this study is to investigate implications of wireless Internet use for college students’ social relationships. To conduct a detailed analysis of the relationship between wireless use and social relationships, this study distinguishes wireless Internet use by the location and time that Internet use takes place. To understand the complex effects of the Internet on social relationships investigating where and when people use the Internet is as important as how much they use it (Nie, Hillygus, & Erbring, 2002). Specifically, this study examines how college students’ wireless use at different locations is related to the amount of face-to-face time spent with friends and acquaintances. It also investigates college students’ wireless use on weekdays and weekends and its association with time spent with friends and acquaintances.

Literature review

Internet Use and Social Relationships

A December 2009 survey found that 74% of Americans ages 18 and older use the Internet and 60% of them have home broadband connections (Rainie, 2010). As Internet use has risen consistently, benefits become diverse, as was the case with do traditional utilities such as telephone, television, and radio. Particularly, from the early days of networked computers to the present, communication with others has been the most frequent use of the Internet (Putnam, 2000). Since devices for online communication have become common, people are able to use multiple channels to stay in touch. Instant messaging, social networking, blogging, and e-mail have gained ground as communications tools (Jones, 2009). In Jones’ survey of online activities, 91% of adult Internet users use e-mail, and 38% and 35% use instant messaging and social network sites, respectively. Those who use the Internet for communication frequently contact their friends and family. Although online communication takes place in a virtual setting, it makes people engage in the same quality and forms of social interaction as co-workers, friends, and people at the corner pub or potluck dinner (McKenna & Bargh, 1999).

As the Internet becomes an increasingly important mode of communication, researchers increasingly aim to understand and discuss its effect on offline social relationships. Some scholars argue that the Internet stimulates positive change by creating new social ties and maintaining existing relationships. First, Internet users create new relationships through virtual communities (Rheingold, 2000) in order to produce and consume a sense of sharedness and belongingness (Kelemen & Smith, 2001). Participating in online communities, individuals can gain access to more diverse information and resources and help each other seek information. The frequent communication with strangers increases overall communication and may lead to larger networks. According to Cohen, Brissette, Skoner, and Doyle (2000), people who have social ties of this type demonstrate more trust and greater social tolerance so they can cope with daily trouble more effectively, and they tend to be physically healthier.

A different perspective relegates the new technology to a less central role in changing modes of communication and social relationships. Quan-Haase and Wellman (2002) argue that the Internet supplements rather than replaces traditional modes of communication. Specifically, this line of scholarship asserts that the Internet sometimes provides a convenient and effective supplement to telephone and face-to-face contact. Flanagan and Metzger (2001) consider the Internet “a multidimensional technology used in a manner similar to other, more traditional technologies” (p. 153). As the Internet easily connects geographically dispersed people, it continues and complements face-to-face and telephone contact with family, friends, colleagues, and other acquaintances.

This type of Internet use could help maintain existing ties (Koku, Nazer, & Wellman, 2001). The Internet facilitates communication across time and distance so that people connect with distant as well as local family, friends, co-workers, and business contacts (Hampton & Wellman, 2003). As cars, planes, trains, and phones maintain ties with family and friends who become separated, people keep contact with friends and relatives via the Internet. Since communication on the Internet is not limited by geographical boundaries, the Internet may allow for a greater frequency of communication among people who have already strong relationships (Park, 2010). In fact, in one study Internet users had more contact with their closest ties such as family members and friends than non-users (Hampton & Wellman, 2003). Therefore, communication through the Internet facilitates a close emotional relationship between family members and close friends who have not seen each other for a long time (Stern, 2008).

Other studies have produced contrasting findings regarding the relationship between Internet use and offline social relationships. Kraut et al. (1998) reported the negative association of Internet use and face-to-face interactions. Their study concludes that high Internet use is related to declines in face-to-face communication with family, smaller social circles, and higher levels of loneliness, stress, and depressive symptoms. Quan-Haase et al. (2002) support those findings by correlating high Internet use with lower social contact offline and higher depression and loneliness. The ease of online communication might encourage people to spend more time alone, to talk online with strangers or to form superficial “drive-by” relationships at the expense of deeper discussion and companionship with friends and family (Putnam, 2000, p. 179).

Even if people use the Internet to talk with close friends and family, online interaction might displace higher-quality face-to-face and telephone conversation. Kraut and Attewell (1997) argue that people using e-mail regard it as less valuable than other modes of communication in maintaining social relationships. As the quality of online interactions increase, some assert that the Internet simultaneously decreases stronger, offline interactions. Riphagen and Kanfer (1997) conclude that people who use e-mail heavily have weaker social relationships than those who do not. Specifically, those who use the Internet heavily report spending less time communicating with their families (Cole, 2000). The negative association between Internet use and offline social relationships is explained by the displacement hypothesis, that Internet use takes time away from other activities, in particular from face-to-face interaction. Previous studies (Nie & Erbring, 2000; Nie, 2001; Nie & Hillygus, 2002; Nie et al., 2005) found that time spent using the Internet is negatively associated with time spent with family, TV viewing, and sleeping. People cannot spend time on offline when they are devoted to using the Internet (Nie, Hillygus, & Erbring, 2002).

In the early phase of the studies regarding Internet use and social relationships, critics held the diffusion of the Internet as evidence of individuals’ increasing alienation from others and other negative effects. However, as benefits of the Internet in facilitating social interactions are highlighted, scholars become attentive to its positive effect. Although Kraut et al. (1998) proposed the pessimistic view on the relationship between Internet use and offline socializing, they presented contrasting findings which overturn their previous results in 2002. In their survey investigating the relationship between Internet use and social involvement and psychological well-being, they found that Internet use is positively associated with increases in the sizes of local and distant social circles and their face-to-face interaction with friends and family. Their study also observed that people who use the Internet are more likely to become involved in community activities and feel greater trust in other people.

Based on the ability of the Internet to cultivate different types of social relationships, scholars remain interested in related positive outcomes of Internet use for interpersonal relationships. In particular, as social network sites (SNSs) have become a new mode of online communication, scholars have explored their social implications in maintaining different types of social relationships. The bulk of SNS research has focused on the potential of SNSs to bridge (or create) a gap between online and offline connections. Donath and boyd (2004) were among the first to hypothesize that online social networking may increase the weak ties a person could form because the technology is suited to maintain these ties cheaply and easily. This proposition was tested by Ellison, Steinfield, and Lampe (2007) using survey data from a small sample of U.S. undergraduate students. They found that use of Facebook was strongly associated with maintaining or solidifying existing offline relationships, rather than meeting new people.

This new platform of online communication allows users to search for other registered users and to expand their social circles from established relationships. Thus boyd (2008) describes SNSs as “networked publics” that support sociability, just as unmediated public spaces do. Using SNSs, people traverse online and offline social networks, establish intimacy, and connect friends and family ties. According to Subrahmanyam, Reich, Waechter, and Espinoza (2008), SNSs are used to stay in touch with friends and relatives based on offline lives. Raacke and Bonds-Raacke’s findings (2008) findings also indicated that college students use SNSs for reasons such as making new friends and reconnecting with old friends. These studies inspire discussion about SNSs in light of the effect that online interactions have on individuals’ communication and social needs.

Diffusion of the Wireless Internet into Everyday Life

Alongside growth of the Internet over the past decades, the availability of wireless broadband Internet access is growing as a result of a great deal of corporate and community efforts. Established wireless carriers and a plethora of start-ups have invested in a range of technologies that offer easy mobile access to the Internet in urban regions (Bar & Galperin, 2004). The proliferation of the wireless Internet has produced claims that ad hoc, self-organized networks of grassroots users’ inexpensive high-speed wireless Internet now challenge existing technologies, regulatory regimes, and industries (Rheingold, 2002).

The penetration of the wireless Internet was realized by the rise of the wireless local area networks (LANs) and the launching of mobile devices such as Web-connected wireless phones, laptops, and personal digital assistants. Wi-Fi standard, a popular platform enabling broadband connectivity, is driven by users who buy inexpensive radio equipment and build the wireless LANs over unlicensed frequencies. Particularly in the U.S. of the early 2000s, Wi-Fi network infrastructure proceeded rapidly in the hands of phone companies, cable providers, ISPs (Internet service providers), cooperatives, nonprofits, municipalities and user groups. The mass-market boost for Wi-Fi helps other vendors use Wi-Fi access points and expansion cards. Most laptops now come with built-in Wi-Fi capabilities. In 2002, T-Mobile began offering Wi-Fi access in addition to its traditional cellular phone service. As a result, by 2004, the worldwide population of Wi-Fi users has reached total 30 million, which is 52% of Americans (IT Facts, 2004). By mid-decade there were more than 25,000 Wi-Fi hotspots in the U.S. (Jiwire, 2005). According to Horrigan (2009), 56% of surveyed Americans have accessed the Internet by wireless means such as laptops, cell phones, and game consoles.

Wi-Fi technology was developed for sharing Internet connections between computers in a home or office. Wi-Fi has since become available in a growing number of public places in many parts of the world. The first public Wi-Fi models were used as a business plan for coffee shops and other retail businesses. As the service broadens to all types of businesses, free and for-fee Wi-Fi access has proliferated in public places like shopping areas and community centers, some parks, but most notably coffee shops (Sanusi & Palen, 2008).

The nature of Wi-Fi in public spaces differentiates it from fixed Internet connections. Besides saving wiring expenses, Wi-Fi offers significant mobility benefits. Meanwhile, physical distance and the boundaries between the public and private space are altered (Hampton & Gupta, 2008). In the past, the fixed nature of desktop computers limited the potential for Internet use in public spaces. With a few exceptions such as libraries, Internet cafés, and community technology centers, Internet use was confined to the home and workplace. The connection between Internet use and home connectedness generated concern that new media use was increasingly becoming privatized (Graham & Marvin, 1996). This argument is consistent with observations of other home-based media, including television and telephone, which have been linked to increased privatism (Fischer, 1992; Putnam, 2000).

Mobility and accessibility of wireless connection have played a central role in changing space and interpersonal relationships in modern society (Boden & Molotch, 1995). The spread of mobile communication affects people’s lives and relationships (Katz & Aakhus, 2002). Wireless devices speed up the pace and efficiency of life but also allow more flexibility in business and professional settings as well as in family and personal life. People can harness spare time that seemed to require little attention, such as waiting in an airport. They can use this time to socialize, get information or share messages through the wireless Internet. In addition, wireless users can communicate with others in cyberspace while at the same time communicating in person offline. Likewise, the wireless Internet challenges people to reconsider space theoretically and practically, because it offers another layer for interaction in public spaces (Sanusi & Palen, 2008). In other words, wireless technology affects the way people interact face to face, since people use the wireless Internet as a meeting place in which they would otherwise have face-to- face relationships.

The growth of wireless Internet access raises competing possibilities regarding its effect on social relationships. According to Hampton and Gupta (2008), wireless use will diversify the composition of people’s social networks by increasing public interaction. The authors also propose that public wireless use will reinforce existing close ties by distracting from interactions with co-present others. Online communication in public spaces raises the question of ubiquitous social connectivity and creates the notions of “co-location,” a spatial relationship among individuals, and “co-presence,” a social relationship (Zhao & Elesh, 2008). According to Zhao and Elesh’s findings, relationships with people co-locating are affected by online interactions with co-present others, since online social contact in public requires prior acquaintanceship.

While there is a significant body of literature addressing how fixed Internet use influences the ways people relate with others, few studies have addressed how the use of wireless Internet influences social life. Scholars have pondered the effects of changes in technology on social relationships (Putnam, 2000; Hampton & Wellman, 2003). They have debated how social changes driven by technological development affect ties with friends, neighbors, kin, and workmates. As ways of use as well as access to communication technologies change, so do the existing social interactions. In past decades, scholars have been concerned with the possible impact of the telegraph (Standage, 1998) and the telephone (Fischer, 1992). Putnam (2000) contended that television is the most likely suspect in a decline in social trust and civic engagement. He suggests that the rise of television viewing is closely associated with the time period of a decline of interpersonal relationships.

Ubiquitous wireless networking adds a new dimension to such a debate. Given the expanding changes enabled by the diffusion of the wireless Internet, it is time to give the subject concentrated scholarly attention. Hampton and Gupta’s (2008) observation of Wi-Fi use in coffee shops demonstrates that Wi-Fi usage in public spaces affect users’ communication patterns. Wi-Fi users tend to communicate with co-located others whom they encounter while working in the public space. This observation suggests that the deployment of ubiquitous Wi-Fi may influence the structure of social networks and social relationships. In fact, coffee shops with Wi-Fi access are the domain of students who are looking for a change of scenery or wanting to escape conventional study places such as library or home (Sanusi & Palen, 2008). It is not unusual to find people working or studying in public spaces with Wi-Fi access. Previous research shows the possibility that wireless Internet use in public spaces facilitates serendipitous encounters (Hampton & Gupta, 2008; Sanusi & Palen, 2008). However, it is unclear whether wireless Internet use will facilitate or decrease face-to-face interactions with existing social contacts.

College Students as a Primary Internet User Group

The increase of Internet use on college campuses allows for rich investigation into college students’ usage. As early adopters of Internet technology, youth rely on the Internet to gather information and to communicate with friends, family, and classmates (Morgan & Cotten, 2003). Internet users who are 18-29 years old have been among the most wired demographic groups from the onset of Internet growth (Lenhart, Purcell, Smith, & Zickuhr, 2010). Internet use among young adults reached 80% penetration in January 2002 and 83% in August 2003 (Madden & Rainie, 2003). As of September 2009, 93% of young adults (ages 18-29) go online (Lenhart et al., 2010). According to Lenhart et al., over the past decade, young adult have remained the age group most likely to go online even as the Internet population has grown, and even as other age cohorts such as 65 and older have increased the percentage of their populations online. Hoffman, Novak and Venkatesh (2004) argue that the Internet is pervasive in the lives of young adults and that college social life has been transformed by the Internet.

Given that Internet usage has become prevalent among college students and youth generally, researchers are beginning to examine how Internet use is related to college students’ interpersonal relationships or well-being (e.g., Morgan & Cotten, 2003; Baym, Zhang, & Lin, 2004). Baym et al. (2004) compared college students’ interpersonal communication across media including the Internet, telephone and face-to-face. The study showed that the more people with whom students communicated with using the Internet, the more they communicated with face-to-face and on the telephone. People having face-to-face conversations were most likely to be engaged in other activities such as online interactions or telephone calls simultaneously. Morgan and Cotten (2004) argue that college freshmen’s Internet activities are significantly related to a high level of social support and well-being.

College students represent an appropriate sample to understand the rise of the Internet in social life because they are ‘pioneers’ for whom social Internet use has already become frequent and even mundane (Jones, 2002). Particularly, it is notable that communication is an important Internet usage among various online activities. Jones (2002) reported that 42% of college students used the Internet primarily to communicate socially, while 38 % used it for class homework and 10% used the Internet for entertainment. In addition, the average student spent one to three hours a week communicating with others online.

The present study focuses on college students’ wireless Internet use and offline social relationships. In the survey conducted by Lenhart et al. (2010), 81% of those ages 18-29 were wireless Internet users. In fact, 57% of wireless Internet users said staying in touch was an important use of wireless connectivity (Horrigan, 2009). Despite the high rates of wireless adoption among this age group that includes the college student population, almost no research has investigated their wireless Internet use. Since wireless connection integrates Internet use into public spaces where socializing also takes place, it may influence users’ face-to-face relationships with their friends and acquaintances.

Research questions

This study examines the association between time spent on the wireless Internet and time spent with friends and acquaintances. Since most of the participants in this study (89%) live with roommates or a partner, or live alone, the amount of time that they spend with their family is negligible (only 0.4 hours on average per week). For this reason, it is difficult to discern the relationship between wireless Internet use and family interactions.

In addition, the present study controls for college students’ demographics and time spent on TV viewing and sleeping. Previous studies have demonstrated that TV viewing and sleeping are important activities that may influence the relationship between Internet use and offline socializing. Since the two activities take up considerable time in people’s everyday life, the time spent on those activities significantly affects the possible time that people can spend on socializing with others (Nie et al., 2005). Therefore, the first research question is:

RQ1: How is college students’ wireless use related to the amount of offline time spent with friends and acquaintances after controlling for demographics, TV viewing, and sleeping time?

In order to advance an understanding of the complex relationship between wireless Internet use and face-to-face interactions, this study considers the context of Internet use. Specifically, where and when an individual uses the Internet is as important as how much he or she uses it (Nie et al., 2002). Differentiating Internet use by location and time allows for elaboration of the results of the analysis and increases the validity of this study. For example, Nie et al. (2002) present that Internet use at home has a negative effect on time spent with family members. In particular, the spread of the wireless Internet facilitates use of the Internet at many places other than home or work (Sanusi & Palen, 2008). Therefore, this study identifies the independent effect of wireless Internet use by differentiating the places where users accessed the wireless Internet.

RQ2: How is college students’ wireless use at home versus school or other hotspots related to the amount of offline time spent with friends and acquaintances?

This study computes Internet use by calculating the number of hours spent on the wireless Internet during average weekdays and weekends. For most people, the weekend typically holds more recreational opportunities, so that individuals can choose how they wish to spend their time and with whom they wish to spend it (Nie & Hillygus, 2002). Nie and Hillygus suggest that the amount of Internet use strongly influences time spent with friends and acquaintances on weekends when people have more free time to choose what they wish to do. Therefore, this study asks:

RQ3: How are the amounts of college students’ wireless use on weekdays and on weekends related to the amount of offline time spent with friends and acquaintances?

Research methods

Sampling and Data Collection

A survey was conducted to predict the relationship between college students’ wireless Internet use and face-to-face relationships with friends and acquaintances. Data were collected from four large undergraduate communication courses in a large southwestern university in March 2008. Participants volunteered to answer an in-class survey and were assured of confidentiality. This research used a purposive sampling for gathering data rather than a random sample of students or classes. Purposively chosen students from the four large classes ensured a sample that is heterogeneous in its demography. Demographic analysis revealed that the sample is highly similar to the college population. Although the courses from which students were selected do not represent a wide range of study areas and course levels, Internet use and daily life are not items influenced by participants’ major or educational level. This study invited 405 students to participate, and 354 (87%) answered the questionnaire. In this study, data from the 339 participants are reported. Respondents of the sample who did not complete the questionnaire were excluded from data analysis as well as those questions that had inaccurate data.

Measures of Variables

Independent Variables

Time spent with the wireless Internet. Wireless Internet use was measured by questions regarding time spent on the Internet for social network sites, e-mail, chatting, and instant messaging. Eight items in the original survey questionnaire measured the wireless Internet use. In the survey, students were asked questions, “How many hours on an average weekday/weekends do you spend on social network sites/e-mail/chatting/instant messaging via the wireless Internet?” One method to measure Internet use is to rely on respondents’ estimates of daily or weekly Internet use. In the survey designed by Shklovski, Kraut and Rainie (2004), respondents were asked to remember the amount of time that they used the Internet. Respondents’ time estimates may be problematic, because individuals do not count total minutes or hours spent on particular activities precisely (Franzen, 2000). However, the respondents’ self-report could overcome criticism of the existing research to simply divide the population into users and non-users by directly measuring time and Internet use (Nie et al., 2002).

Location of wireless Internet use. The location of wireless Internet use was measured by asking respondents to report where they mainly used the wireless Internet with four response choices, including home, school, work, and other hotspots. Hotspots refer to public places that have installed Wi-Fi access—for example, libraries or coffee shops. All categories of location of wireless Internet use are nominal variables, so that they were recoded as dummy variables for analyses.

Time spent on TV viewing. Respondents were asked to report how many hours they watch TV on an average weekday and weekend.

Time spent on sleeping. Respondents were asked to report how many hours they sleep on an average weekday and weekend.

Dependent Variable

Time spent with friends and acquaintances. This study examined face-to-face relationships with college students’ friends, and acquaintances. Respondents filled out the open-ended question, “How many hours do you spend communicating face to face with your friends, and acquaintances on an average weekend/weekday?” In Nie et al.’s time diary study (2002), social relationships are measured as the number of minutes spent communicating via telephone and actively engaging or participating in an activity with friends, family, or acquaintances. Particularly, measuring time spent on interpersonal, face-to-face relationships is to consider the quality of sociability that people are actively engaging in activities with significant social ties (Nie et al., 2002).

Demographic Variables

This study controlled for various demographic background factors, such as gender, age, year in education, and ethnicity, and other activities such as TV viewing and sleeping that might affect the relationship between time online and time with people. Age was assessed by the item, “What is your age?” with six response categories, “17 to 19,” “20 to 22,” “23 to 25,” “26 to 28,” “29 to 31,” and “older than 31.” The ethnicity measure was created by identifying whether or not respondents were Latino or Hispanic. The people who answered “no” were asked what their ethnicity was with four choices: “White,” “Black,” “Asian/Pacific Islander,” or “Other.” Respondents were asked to report their level of formal education with five choices: “Freshmen,” “Sophomore,” “Junior,” “Senior,” or “Other.”

Data Analysis

Besides the main independent and dependent variables, other variables such as students’ TV viewing or sleeping, as well as demographic variables were measured in order to effectively control for extraneous factors that may influence the relationships between wireless Internet use and interaction with other people. All of the nominal variables in this study were recoded as dummy variables. Hierarchical linear regression was used to estimate how the main independent variables as well as other controlling variables predict the amount of time interacting with others. Data were coded and analyzed with the SPSS statistical analysis package.

Results

Descriptive Statistics of the Participants

Of the 339 respondents, 52% were female and 48% were male. In addition, 71.7% were white, followed by Hispanic (17.7%), Asian (7.1%) and black (3.5%). The age of the participants was mainly distributed between 17 and 22 (94.4%), with a range of 17 to 31 years. The mean time that the participants spent with wireless Internet was 2.8 hours (see Table 1). The respondents use the wireless Internet for 3.2 hours (SD = 3.2) on an average weekday and 3.4 hours (SD = 3.2) on an average weekend. 44.4% of the respondents spend their time on the wireless Internet at home, 25.9% at school, and 28.8% at hotspots. On an average weekday, college students spent time face to face with friends for 4.8 hours (SD = 4.0) and with acquaintances for 3.4 hours (SD = 3.5). The respondents spent time face to face with friends for 8.7 hours (5.0) and with acquaintances for 2.6 (3.1) hours during weekends. On an average, the subjects had spent 7.5 hours sleeping (SD = 2.1) and 3.1 hours watching TV (SD = 3.6). Table 1 presents the descriptions of the sample used in this study.

Table 1. Descriptions of Participants

Wireless Internet Use and Relationships with Friends and Acquaintances

RQ1 asked about the overall relationship between the amount of wireless Internet use and time spent with friends and family. The models shown in Table 2 explained more than 20% of the variance in the dependent variables. Entered on Step 1, demographic variables had little explanatory power. Entering time spent on TV viewing and sleeping on Step 2, the explanatory power of time spent on TV viewing was less than 10% for face-to-face time spent with friends and acquaintances (ΔR² = .08, p < .05; ΔR² = .09, p < .01, respectively). Time spent on TV viewing was significantly related to decreased time with friends and acquaintances. The variance in both forms of relationship explained by the block of time spent on wireless Internet was substantial as well. Total time of wireless Internet use was positively associated with offline time spent with friends and family. Specifically, time spent with friends and acquaintances increased 14 and 28 percentage points, respectively, when wireless Internet use changed from its lowest amount of time to its highest amount of time, holding all other variables constant.

Table 2. Wireless Internet use at home, school, and hotspots and Social relationships with friends and acquaintances

Wireless Internet Use at Home, School and Hotspots and Social Relationships

RQ2 asked how wireless Internet use in multiple places is related to time spent with friends and acquaintances. As shown in Table 2, in the regression models, wireless Internet use at school, and hotspots accounted for 14% of face-to-face time spent with friends (ΔR² = .14, p < .001) and 28% with acquaintances (ΔR² = .28, p < .001). Specifically, wireless Internet use at school and hotspots were significant positive predictors of face-to-face time spent with friends and family. In addition, home wireless use is significantly related to increased time spent with acquaintances, while it has no significant relationship with face-to-face meeting with friends. Demographic variables in Step 1 were not significant predictors of face-to-face time spent with friends and acquaintances. Time spent on TV viewing entered in Step 2 accounted for 8% of the variance in interactions with friends (ΔR² = .08, p < .01) and 9% of the variance with acquaintances (ΔR² = .09, p <.05).

Wireless Internet Use in Weekday versus Weekend and Social Relationships

RQ3 asked how wireless Internet use at different times (weekday versus weekend) is related to offline social relationships with friends and acquaintances. For wireless Internet use during weekdays, the hierarchical multiple regression equation accounted for 21.9% of the explained variance of time spent with friends (ΔR² = .219, p < .05) and 15.5% with acquaintances (ΔR² = .155, p < .01; see Table 3). Demographic variables entered in Step 1 were not significant predictors of face-to-face time spent with friends and acquaintances. Entering TV viewing and sleeping on Step 2 accounted for 3.8% of the variance (ΔR² = .038, p < .05). Specifically, while, time spent on sleeping had no statistically significant relationship with offline socializing, TV viewing was a negative predictor of face-to-face relationships with friends and acquaintances. Final results of the hierarchical regression analyses are summarized in Table 3.

Meanwhile, for the models of wireless Internet use during weekends, the hierarchical multiple regression equation with all variables entered accounted for 24.5% and 16.4% of the variance in time spent with friends and acquaintances, respectively. Variables entered on Step 1 (gender, age, year of school, and ethnicity) had no explanatory power in time spent with friends and acquaintances. The explanatory power of entering TV viewing and sleeping on Step 2 was less than 10%. Specifically, time spent on TV viewing explained 8% of the variance in time spent with friends (ΔR² = .08, p <.05), but the explanatory power for time spent with acquaintances was negligible (ΔR² = .016, p < .05). The amount of sleeping had no significant relationship with time spent with friends and acquaintances. In addition, entering the amount of wireless Internet use on Step 3 explained additional 15.9% of the variance in the amount of time spent with friends (ΔR² = .159, p <.05). On Step 3, wireless Internet use during weekends accounted for 17.7% of the variance in time spent with acquaintances (ΔR² = .177, p < .05). Table 4 summarizes final results of the hierarchical regression analyses.

Table 3. Wireless Internet Use during Weekdays and Face to Face Relationships

Table 4. Wireless Internet Use during Weekends and Face to Face Relationships

Discussion

The regression analyses show a positive relationship between wireless Internet use and face-to-face time spent with friends and acquaintances. Considering multiple locations and the time that college students use the wireless Internet, this study shows that wireless Internet use is related to offline socializing in different contexts. Specifically, while wireless Internet use at home is not significantly related to time spent with friends and acquaintances, school and hotspots uses are positively and significantly related to the time spent with friends and acquaintances. In addition, during weekdays and weekends, wireless Internet use has a positive association with offline time spent with friends and acquaintances. TV viewing is negatively related to time spent with friends and acquaintances, while sleeping time has no significant relationship.

The results of this investigation contradict the expectations of the time displacement hypothesis, first suggested by Putnam (2000) for the effects of television on social capital and then expanded to the Internet. In the 1990s, critics held the diffusion of the Internet as evidence of individuals’ increasing isolation from society and public life (Kraut et al., 1998; Nie, 2002). This argument is based on a zero-sum assumption of time use. That is, people have limited time, thus time spent in one activity interferes with time spent in another activity. While not all activities are displaced by media use, time displacement studies empirically found that social interaction is one valuable activity that is displaced by media use.

However, the findings of the present study may ease the concerns raised by the early Internet researchers. As the Internet becomes an effective medium for maintaining social ties, the wireless Internet also plays an important tool to mediate face-to-face social interactions. Ubiquitous networks supported by wireless connection make people reachable anywhere at any time. Most people are able to keep in touch through wireless connections in public spaces. These findings reflect “networked individualism” (Wellman et al., 2003). According to Wellman et al., ubiquitous connectivity and wireless portability facilitate networked individualism. They argue that wireless technology shifts the concept of social networks from “linking people-in-places” to “linking people at any place,” since the basis of connections is people and not on places. The findings of the present study, identifying the positive relationships between wireless use at hotspots and school and offline social interaction, suggest that the ubiquitous availability of wireless Internet access could reinforce existing close ties and further afford networked individualism.

Particularly, a strong association of wireless Internet use with face-to-face relationships indicates a likelihood that college students invest a considerable amount of their time on the wireless Internet in socializing. Although the way people use the Internet and a computer may be different, the positive relationship between wireless Internet use and face-to-face relationships suggests that the wireless Internet may benefit social interactions with peers. Lately, SNS research explores how online social networks are interrelated within different dimensions of social capital. Young people are motivated to join SNSs to keep strong ties with friends and to strengthen ties with new acquaintances (Ellison et al., 2007). Although the present study did not focus on SNS use, the findings reflect the trend of young adults’ online activities. Nearly 72% of young adult Internet users use SNSs and they overwhelmingly view the social aspects of the Internet as very important to them (Lenhart et al., 2010). The survey conducted by Lenhart et al. showed that wireless Internet use rates are especially high among young adults and that the laptop has replaced the desktop as the computer of choice among those under 30. That means the pattern of online activities on the wired network of the Internet could be replicated in the wireless Internet because wireless connection tends to replace the fixed network. For young adults, socializing is a significant reason why wireless connection helps (Horrigan, 2009).

The present study also found a negative association between TV viewing and face-to-face time spent with friends and family. The time displacement hypothesis proposes that an increase in time spent in one activity leads to a decrease of time spent in another activity. In fact, TV viewing and sleeping take significant amounts of time (Nie et al., 2002). While computer communication through wireless connections could benefit peer interaction, TV viewing tends to provide no way to mediate social interactions with others. The primary purpose of TV viewing is entertainment, and TV viewers are unlikely to engage in socializing. In addition, time spent on wireless Internet use could be distracted or replaced by TV viewing. Therefore, the negative relationship between TV viewing and offline socializing supports confirms the time displacement hypothesis.

Overall, this study found significant connections between the wireless Internet and offline socializing. However, some limitations should be addressed in future research. Given the cross-sectional nature of this study conducted in a large southwestern university, we cannot generalize the findings to the U.S. college student population. In addition, the purposive and convenient sample does not represent the whole university population, even if it is heterogeneous in its demography and the demographic analysis of the sample is highly similar to the college population. Even so, the findings do suggest that wireless Internet use integrated into the regional community can influence students’ interaction with others. This research could be a case study of wireless Internet use and social interactions. Future research can explore wireless use in other contexts and more diverse communities.

Another limitation of this study is that it disregards factors that can moderate the effects of Internet use on social relationships. Existing differences among individuals such as extraversion personality can account for differences in the dependent variable. For example, for extraverted people who already have strong ties with others, Internet use may be counterproductive activity maintaining social relationships. Therefore, Internet effects moderated by respondents’ social context or personality could be detected if the study includes the variable.

This study does not consider the quality of social relationships. Indeed, whether Internet use will have positive or negative relationships with social interaction depends on the quality of people’s online relationships (Kraut et al., 2002). If the online relationships have much stronger ties than the offline relationships, Internet use could be negatively related to the offline social interaction. In contrast, if people have closer relationships with others offline than online, their Internet use might be less influential on their offline social interaction. Therefore, differentiating social effects by online relationships would help a researcher to elaborate and advance the effects within different relationships.

In addition, the present study does not show a causal relationship between wireless Internet use and time spent with friends and acquaintances. It may well be that students who are socially outgoing and invest more time in having relationships with friends and acquaintances are more likely to use wireless Internet access. This limitation could be better addressed by a longitudinal study, which would track changes in wireless Internet usage with changes in offline socializing. Such observation could separate “before” social interaction from “after” social interaction when the study ends. The longitudinal design would allow for entangling the causal links between use of the wireless Internet and face-to-face interactions with friends and acquaintances.

The wireless Internet has the potential to influence civic engagement as well as offline social relationships. It advances accessibility and availability of Internet services and expands public access to disadvantaged groups who are unprivileged from Internet accessibility. The efforts of Wi-Fi community networks to assure connectivity to the Internet have focused on making Internet services affordable and bringing them to people who live in rural areas and low-income families. Wireless Internet access mobilizes significant efforts and resources to increase disadvantaged citizens’ Internet access through public access services, such as freenets or community networks. Therefore, promoting public wireless Internet connectivity can positively influences civic involvement.

In conclusion, this study has implications for examining social interaction patterns related to other mobile devices. As mobile technologies, such as smartphones, become woven into the fabric of everyday life, they have also involved the contexts of social interaction. The proliferation of mobile devices provides a site for the renegotiation of the boundaries between the public and private spaces and the ways of communicating with each other. Alongside studies exploring the overall uses of such new technologies, we also need studies concerned with the ways in which technologies get communicative functions and affect existing patterns of social interaction. Furthermore, a consideration of communication through mobile technologies must take into account both the reorganization of the means as social interactions and the meanings they carry in different cultural contexts.

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Correspondence to:
Namsu Park
82-10-2695-7535
Dondaemun-gu Yongdu-dong, Doosan Bears Tower #819
Seoul, South Korea
Email: park.namsu(at)gmail.com