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Information, Communication & Society
ISSN: 1369-118X (Print) 1468-4462 (Online) Journal homepage:
Digital skills and social media use: how Internet
skills are related to different types of Facebook
use among ‘digital natives’
Teresa Correa
To cite this article: Teresa Correa (2016) Digital skills and social media use: how Internet skills are
related to different types of Facebook use among ‘digital natives’, Information, Communication &
Society, 19:8, 1095-1107, DOI: 10.1080/1369118X.2015.1084023
To link to this article:
Published online: 14 Sep 2015.
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VOL. 19, NO. 8, 1095–1107
Digital skills and social media use: how Internet skills are
related to different types of Facebook use among ‘digital
Teresa Correa
College of Communication and Literature, Universidad Diego Portales, Vergara 240, Santiago, Chile
Based on the idea that Internet use can be conceptualized in terms
of depth (frequency) and width (differentiated) uses of the Web, this
study explored how socio-demographic factors and digital skills are
related to frequency and types of Facebook use among young
adults. It used a face-to-face representative survey conducted in
the three main urban areas of Chile among a sample of 18-to 29year olds. The results found that men and more educated young
people had higher levels of skills, con?rming that the so-called
‘digital natives’ are not a monolithic group. They also revealed
that digital skills did not predict frequency of Facebook use.
Furthermore, lower educated young people tended to use
Facebook more frequently. Although these results go against the
long-established digital divide research, traditional digital gaps
emerged when types of use were analyzed. While more educated
and skillful individuals tended to use Facebook for informational
and mobilizing purposes, socio-demographic factors and skills did
not make a difference in Facebook use for social purposes.
Received 15 January 2015
Accepted 11 August 2015
Digital skills; social media;
Facebook; digital inequality;
digital divide; young people;
survey; digital natives
Social media such as Facebook are pervading all sectors of society, particularly among
young people (Duggan & Smith, 2013). Furthermore, it has become a port of entry to
the Internet for those who are accessing the Web for the ?rst time. For example, in developed countries such as the United States, 84% of online young adults (18–29 years old) use
Facebook (Duggan & Smith, 2013). In developing countries like Chile, the ?gures are
similar: 94% of young adults (18–29) are registered on Facebook and more than threefourths of them visit Facebook at least once a day (School of Journalism UDP-Feedback,
On surface, these ?gures con?rm the myth that millenials are almost universally connected. Indeed, they have grown up with a greater familiarity with new technologies to the
point that they have been called ‘digital natives’ (Prensky, 2001) or the ‘net generation’
(Tapscott, 1998). They even become technology brokers in their families and help
include their parents in the digital environment (e.g. Correa, 2014; Correa, Straubhaar,
Chen, & Spence, 2015; Katz, 2010). However, research is consistently ?nding that they
CONTACT Teresa Correa
© 2015 Taylor & Francis
are not a monolithic group with universal talent to use digital media. In fact, their engagement with digital technology is varied (Selwyn, 2009) and there are differences by gender
and socioeconomic status on more skillful Internet activities (Correa, 2010; Correa &
Jeong, 2011; Hargittai, 2010).
As the Internet matures, research on the digital divide has moved from differences
between connected and disconnected people to pay attention to different aspects of the
digital inclusion process, including skills and differentiated usage of the Web. This line
of research has been called the ‘second level digital divide’ (Hargittai, 2002) or the
‘usage gap’ (van Dijk, 2005). Research has found socioeconomic differences in frequency
and breadth of actions that require greater involvement and technological skills, such as
content creation and educational, economic, or political Internet activities, even among
young people. Those with lower levels of education and income tend to engage in less
skillful activities (Correa, 2010; Hargittai & Hinnant, 2008; Hargittai & Walejko, 2008;
Livingstone & Helsper, 2007).
Furthermore, current studies have found that in developed and highly connected
nations such as the Netherlands, people with lower levels of education are using the
Internet more frequently than middle-upper sectors of society, but they focus on social
interaction and gaming, both very time-consuming but less capital-enhancing activities
(van Deursen & van Dijk, 2014). In the same vein, the Pew Research Internet Project’s
?gures on social media use revealed that people with lower level of education and
income – who typically have lower levels of digital skills – are using Facebook to a
greater extent than people with higher education and income (Duggan & Smith, 2013).
However, it is relevant to explore whether the relationship among socioeconomic
status, digital skills, and Facebook use depends upon types of Facebook use.
Therefore, drawing from the literature on digital inclusion and skills, this study has
three purposes: (1) to explore the different levels of skills among the so-called ‘digital
natives’, (2) to investigate how digital skills relate to social media use, and (3) to
examine to what extent the relationship among socio-demographic factors, skills, and
social media use differs by types of social media use.
Literature review
From digital access to skills and usage
As the Internet diffuses into all sectors of society, scholars, and policy-makers have moved
Internet research from basic adoption and access to a multifaceted concept that involves
different aspects of the digital inclusion process, including attitudes, skills as well as depth
and width of Internet use (e.g. van Dijk, 2005; de Haan, 2004; Hargittai, 2002; Shih &
Venkatesh, 2004). Depth is de?ned as the amount or frequency of use and width as the
number of different uses (Gatignon & Roberston, 1991). The argument suggests that, as
the technology spreads to the population, digital inequalities evolve, but do not disappear
because having basic access is different from taking full advantage of the opportunities and
content provided by the Web. The emergence of this second phase of research on digital
inequality has been called ‘usage gap’ (van Dijk, 2004) and ‘second-level digital divide’
(Hargittai, 2002). Although this approach considers many factors as important contributors of the digital inclusion process such as motivation, self-ef?cacy, experience, and
autonomy of use (Correa, 2010; Eastin & LaRose, 2000; de Haan, 2004; Hassani, 2006), two
aspects have gained key attention by most research on the topic: digital skills (for a review
see Litt, 2013) and differentiated uses of the Web (e.g. Cho, Gil de Zúñiga, Rojas, & Shah,
2003; van Deursen & van Dijk, 2014; Hargittai & Hinnant, 2008).
Digital skills: They have been broadly de?ned as the ‘capacity to respond pragmatically
and intuitively to challenges and opportunities in a manner that exploits the internet’s
potential’ (DiMaggio et al., 2004, p. 378). More speci?cally, Hargittai (2005) de?ned
them as ‘user’s ability to locate content on the web effectively and ef?ciently’ (p. 372).
van Deursen and van Dijk (2010) categorized four types of skills: operational, which is
the ability to operate hardware and software; information, which refers to the capacity to
search, select and process information in a computer; strategic, which is the ability to use
the computer and the Internet to attain particular goals; and formal skills which refer to
the capacity to navigate in a hypermedia context.
A recent review of the literature about skills (Litt, 2013) revealed that most of the
research has focused on self-reported levels of operational and information skills (van
Dijk, 2006), in which the respondent evaluates his/her level of skill. For example, using
a four-point scale from ‘beginner’ to ‘expert’, Livingstone and Helsper (2007) revealed
that skills have the greatest impact on number of activities performed in the web. The
in?uence was more important than age. Other instruments such the General Social
Survey use similar self-rated abilities that go from ‘excellent’ to ‘poor’ (Litt, 2013).
Despite these ?ndings, self-reported skills suffer validity problems (van Dijk, 2006). To
overcome these shortcomings, Hargittai (2002, 2005) developed performance tests to rate
information skills in a controlled setting. Based on these controlled tests, Hargittai created
questions to measure people’s knowledge of Internet terms in surveys (e.g. advanced
search, jpg, pdf, spyware, malware). These terms highly correlated with people’s ability
to ?nd various types of content on the Web. Thus, they become better proxies of actual
users’ skills than self-perceived abilities (Hargittai, 2005).
Results from studies that have explored online skills reveal that although access gaps are
closing in many developed countries, skills gaps are opening (van Dijk, 2006). There are
signi?cant differences in effectiveness and time needed to complete a task. For example,
Hargittai (2002) has found that age is negatively associated with people’s level of online
skill, while van Deursen and van Dijk (2010) found that age was negatively related only
to operational and formal skills. The evidence about gender is mixed. While a few
studies have found that gender is not related to web skills (Bunz, 2009; van Deursen &
van Dijk, 2010), other investigations have revealed a more complex scenario, in which
men and women do not differ greatly in their skills, although females have lower perceived
competences, which may affect their online behavior (Hargittai & Shafer, 2006). There is
also evidence that suggests signi?cant gender differences, in which males have greater
Internet skills than women (Wasserman & Richmond-Abbott, 2005). Finally, the skills
differences by socioeconomic status are consistent: groups with higher levels of education
and/or income are more digitally skillful than those with lower levels of education and/or
income (Bonfadelli, 2002; van Deursen & van Dijk, 2009, 2010). Furthermore, van
Deursen and van Dijk (2010) found educational differences for all types of digital skills.
Although young people are almost universally connected and show greater levels of
skills to the point that they have been named ‘digital natives’ (Prensky, 2001) or ‘net generation’ (Tapscott, 1998), research has found that they are not a monolithic group with
innate talent to use new technologies (e.g. Correa, 2010; Correa & Jeong, 2011; Gui &
Argentin, 2011; Hargittai, 2010; Selwyn, 2009). Because digital inequalities mirror structural social inequalities (Helsper, 2012), young people also show differences by gender
and education in digital media mastery (Correa, 2010; Gui & Argentin, 2011; Hargittai,
2010). Thus, I hypothesize that:
H1: Men and more educated young adults will show greater levels of digital skills.
Differentiated uses of the Web: Theoretically, the Web is an instrument that helps in
advancing access to information and services, socialization, economic and educational
opportunities as well as political and civic participation (Castells, 2000; Chen &
Wellman, 2003; Norris, 2001; Warschauer, 2003). In line with this premise lies the
assumption that some Internet activities are more helpful than others because they
provide greater opportunities to improve people’s education, work, civic engagement,
and political participation (e.g. Cho et al., 2003; van Deursen & van Dijk, 2010; Hargittai
& Hinnant, 2008; Zillien & Hargittai, 2009).
Based on the uses and grati?cations approach – which asserts that people’s motivations
to use media are related to speci?c outcomes (Rubin, 1994) – current research has found,
for example, that expressive, informational, and mobilizing uses of social media are associated with more meaningful outcomes, including increased social capital and political and
civic participation, than consumptive and entertaining uses (Gil de Zúñiga, Jung, & Valenzuela, 2012; Valenzuela, 2013).
The investigations have also suggested that the digital inclusion process occurs in a continuum that goes from consumption activities to active and creative uses (Livingstone &
Helsper, 2007). In this line, the authors found that digital skills have the greatest impact on
number and complexity of activities performed on the web (Livingstone & Helsper, 2007).
In the same vein, Hargittai and Hinnant (2008) found that people with greater skills are
more likely to visit websites that enhance their political, cultural, and knowledge capital
such as governmental, ?nancial, and health web pages.
Generally, studies have demonstrated that people from higher socioeconomic status use
more advanced applications of the web for informational, educational, communicational,
or service-oriented purposes while users from lower classes use simpler applications for
communication and entertainment (Bonfadelli, 2002; van Dijk, 2005; Howard, Rainie,
& Jones, 2001; Peter & Valkenburg, 2006). Similarly, Cho and colleagues (2003) found
that users high in socioeconomic status are more effective to attain grati?cations they
seek, such as connection, learning, and acquisition, while people from lower status take
a more indirect route to achieve a simpler goal, which is engaging in consumptive activities
to get connected with others. Researchers have also demonstrated that college students
who are better off (measured by parental schooling) are more likely to engage in creative
activities than those who are less well off (Correa, 2010; Hargittai & Walejko, 2008).
Furthermore, studies in countries with wide Internet access have recently found usage
patterns that go against the traditional digital divide. For instance, van Deursen and van
Dijk (2014) found that in the Netherlands, people with lower levels of education are using
the Internet more frequently than middle-upper sectors of society. However, they also
found a usage gap in which lower educated people focus on social interaction and
gaming, activities that are very time consuming but do not take advantage of the economic, cultural, and political opportunities provided by the Web. Similarly, in the
United States, the patterns of social media use revealed that people with lower level socioeconomic status – who typically have lower levels of digital skills – are using Facebook
more frequently than people with higher education and income (Duggan & Smith,
2013). However, it is relevant to explore whether the relationship among socioeconomic
status, digital skills, and Facebook use depends upon types of Facebook uses. Based on
these ?ndings, it is hypothesized that:
H2: Digital skills will not be associated with frequency of Facebook use among young adults.
H3: The association between digital skills and Facebook use will differ by types of social
media use. Particularly, digital skills will be positively associated with more capital-enhancing
activities – such as informational and mobilizing Facebook uses – while they will not be
associated with activities that involve social interactions.
Survey description
To test the hypotheses, I relied on the face-to-face probabilistic survey of individuals aged
18–29 conducted in October 2013 in Chile’s three main urban areas: greater Santiago, Valparaíso-Viña del Mar, and Concepción-Talcahuano. These three areas comprise 43.2% of
the country’s total population. The School of Journalism at Universidad Diego Portales
and Feedback, a professional polling ?rm, collaborated in a multistage probability
sample that selected respondents according to the following phases: In each urban area,
the sample was distributed proportionally by districts and, then, by blocks. In each randomly selected block, ?ve households were randomly chosen. In each household, one
18- to 29-year-old resident was randomly drawn to be interviewed. The ?nal sample of
1,000 individuals represented an 80% response rate.
Chilean context
Chile is an appropriate setting to study digital inclusion processes because it is relatively
well connected but has varied degrees of adoption. In this 17 million-people country, computer and Internet penetration rates are among the highest in Latin America. While twothirds (66%) of the entire population uses the Internet (Subtel, 2014), the ?gure escalates
to 90% among young adults (World Internet Project [WIP] Chile, 2014). Eighty percent of
the population uses the Internet through broadband access, 32% of people through smartphones, and 19% through mobile broadband (Subtel, 2014). However, there are important
gaps by socioeconomic status and gender. While more than 70% of higher socioeconomic
status people use the Web, only 35% of lower SES do so (WIP Chile 2014). Regarding
gender, for example, while 55% of male heads of household have used the Internet,
45% of female heads of household have been online (Agostini & Willington, 2012).
Socio-demographics: To examine socio-demographic factors, standard questions were
used. Respondents were asked about their gender, which was recoded as a dummy variable
(male = 0; female = 1). Age was measured as a continuous variable and socioeconomic
status was measured by the highest level of formal education completed by the respondent.
The response categories varied from 1 (less than primary education) to 7 (graduate
Digital skills: This variable was measured by a scale developed for surveys by Hargittai
and Hsieh (2012). This scale aggregates responses to nine questions about people’s knowledge of computer- and Internet-related terms. Respondents were asked: ‘How familiar are
you with the following computer and Internet-related items? Please choose a number
between 1 and 5, where 1 represents no understanding and 5 represents full understanding
of the item’. The items were the following: Advanced search, PDF, Spyware, Wiki, JPG,
Blog, Malware, Tag, Firewall. Because these items have high correlation with people’s
actual skills, they are better proxies of actual users’ skills than perceived abilities (Hargittai,
2005). This approach of measuring skills has been used several times with adequate
levels of internal consistency and predictive value (e.g. Correa, 2010; Hargittai &
Hinnant, 2008; Hargittai & Hsieh, 2012; Hargittai & Walejko, 2008). The Cronbach’s
alpha was .92 (M = 2.99; Mdn = 3.0; SD = 1.31).
Facebook use: Current Internet research focuses on depth (frequency) and width
(differentiated uses) of the Internet. Thus, Facebook use was measured as frequency of
Facebook use and types of Facebook use.
Frequency of use was measured with the following open-ended question: How many
hours per day you are connected to Facebook? This question was measured as a continuous variable (M = 3.4, Mdn = 2.0; SD = 3.8).
Types of Facebook use were measured by three different indexes. The inde …
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