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Synchronicity matters: defining the characteristics of digital generations

ABSTRACT This paper investigates whether or not the proposition that the second digital generation (or so-called digital natives) is more engaged in social use of the Internet than older generations is tenable. By analysing nationally representative questionnaire-based survey data collected from Finland in 2011 (N = 612), the study shows that rather than social use of the Internet in general, it is the synchronicity of online communication that distinguishes user generations. Results show that, in contrast to asynchronous modes of online communication (e.g. social networking sites, blogs and online discussion forums), synchronous modes (e.g. instant messaging and Internet calls) are clearly generationally differentiated practices. They are more frequently used by the second digital generation than the first digital generation and digital immigrants. Furthermore, the study shows that asynchronous uses of the Internet are clearly gendered in nature. Women are more typically users of social networking sites and blogs than men, whereas men are more often engaged with discussion forums than women. These results are discussed in light of two concepts: privacy and communicative efficacy. The studied forms of synchronous online communication provide more privacy as well as an instant and abundant channel for effective communication, which are all features especially appreciated by the youngest user generation.


Introduction
Many efforts have already been made to identify social generations that would differ from the preceding ones with regard to the use of digital media (Dingli & Seychell, 2015;Montgomery, 2007;Prensky, 2001a;Tapscott, 1998). In most cases the distinguishing factor has been higher engagement in the most recent information and communication technology (ICT). Nevertheless, the youngest generations, born into and grown up in a world that is thoroughly mediated by technology, are often far too easily considered as innately technology savvy and active users of digital media. From Prensky's initiative (2001aPrensky's initiative ( , 2001b, these generations have been widely called 'digital natives' to differentiate them from 'digital immigrants' (DI), who were born earlier (before the 1980s) and only adopted digital technologies at a later age. Such stark juxtapositions of the two generations have been subsequently questioned by more detailed empirical investigations (e.g., Davies, Coleman, & Livingstone, 2014;Hargittai, 2010;Helsper, 2010;Helsper & Eynon, 2010;Lee, 2008). The notion of digital natives is said to reflect the distorted view of parents and others, who tend to mystify the mundane sides of digital media. Like any other skill, digital media skills must be learnt and socialized into, and hence some scholars would like to put aside the generation terminology (e.g. boyd, 2014;Hargittai, 2010). Later, Prensky (2009) himself noticed that his original distinction had become less relevant as digital technologies evolved so rapidly. He suggests that more and more attention should be paid to prudent use of the new technology and to the wisdom arising from the use of digital technologies.
In fact, empirical studies have also provided support for these critics, showing that digital natives and immigrants do not comprise coherent and clearly defined social groups as regards ICT use. For example, Hargittai (2010) shows how race/ethnicity, the number of years of using the Internet and the weekly hours of web use affect online skills, and how these skills, along with the time spent on the web each week, increase the diversity of Internet use, contributing to stratification among the networked (young) people. Similarly, Lee (2008) has shown that Internet access and usage have remained by and large concentrated in wealthier households in the UK, contradicting the idea of young people as techno-enthusiasts and experts regardless of their background. Helsper (2010), in turn, presents that life stage could be a more powerful predictor in this respect than generation. The natives vs.
immigrants division makes us overrate the difference between generations and overlook the diversity within them. Herring (2008) has argued that these so-called natives are actually a kind of 'transitional generation', as they are still using both analogue and digital media. As such, they can also work as intermediaries between the digital immigrants and the new digital generations who are increasingly unfamiliar with both the old analogue media and the older forms of digital media.
More recently, Helsper and Eynon (2010) jointly suggested that the social functionalities of the Internet (e.g. Facebook, MySpace) may have created a second generation of digital natives. Helsper and Eynon maintain that the second generation would differ from the first generations of natives, born in the 1980s, in its greater familiarity and immersion in Web 2.0, which refers to the developmental phase that makes the Internet more social and participatory in nature (Fuchs, 2010, for more detailed analysis and criticism). In 2015, Dingli and Seychell put forward an idea that people born towards the end of the first decade of the twenty-first century could be called 'the new digital natives'. This new generation is able to deal with wireless technologies and touch screen at once when infant and toddler, while the previous generation of digital natives came in contact with digital technologies relatively late, only when they learnt to control a mouse and to read. All in all, these many parallel and at least partially competing attempts to define the new generations of digital technology users imply how vigorous, yet also elusive, a sociological category the generation is when trying to unpack the social diversities of digital societies.
In this study, the terms the first and the second digital generation (1DG and 2DG respectively) are used to simplify this tangle of concepts and conceptualizations (see also, Fortunati, Taipale, & de Luca, forthcoming). 1DG refers to people born in the 1980s who were exposed to and gained hands-on experience of the first digital technologies at a relatively early stage of their life. 2DG is considered as a generation that was born in the 1990s or later and who, following the suggestion of Helsper and Eynon (2010), should be more engaged with the social functions of the Internet. Digital immigrants (DI) will also be tackled in the analysis. They will serve as a point of reference in order to understand the particularities of the two digital generations.
Based on these definitions and considerations, the aim of this article is defined as being to empirically test if 2DG is really different from 1DG in Finland, in terms of its closer engagement with the social functions of the Internet. In their study, Helsper and Eynon (2010, p. 510) used bivariate methods to show that there are statistically significant differences in Internet uses between various age groups in general. However, their analysis does not reveal if the difference between the first and second digital generations (or natives) in particular is statistically significant. While using multivariate methods, Helsper and Eynon (2010, pp. 512-514) applied respondents' age as a continuous variable in their models. In so doing, their study is not able to reveal whether or not there are differences between specific age groups/cohorts, or so-called societal generations (Pilcher, 1994), and if any possible differences are statistically significant.
To overcome these limitations, this study will exploit both bivariate methods and a logistic regression analysis. The social uses of the Internet will be measured with five dependent variables, which are used disjointedly to paint a more nuanced picture of the studied phenomenon. The separate use of these five measures allows detection of whether the social uses of the Internet are differently related to generations. On the other hand, the strength of logistic regression analysis in this connection is that it makes possible the testing of whether the differences between specific generations, with relation to the social uses of the Internet, are statistically significant. The analysis will be carried out with a nationally representative questionnaire data (N = 612) collected from Finland during May-June 2011.
The rest of the paper is structured in the following way. The paper begins with a discussion of the development of the Internet from an information sharing network to a platform of social interaction and cooperation, as well as how this development is related to the rise of new user generations. At the same time, previous empirical literature and statistics are reviewed to lay a solid basis for research hypotheses. The data, measurement instruments and statistical procedures are described before moving on to a results section. The paper will end with discussion and concluding remarks.

Co-evolution of the Internet and user generations
Living through and learning to use similar functions of the Internet is a binding factor amongst people who belong to the same societal generation of Internet users. Fuchs (2008, pp. 125-136) presents that the first phase of Internet development, the so-called Web 1.0, was a tool for thought. Internet usage was chiefly characterized by the idea that everybody is able to publish information online and engage him/herself in the global web. 1DG was born before the world where Web 1.0 was taking its first steps, while digital immigrants had grown up for many decades without any digital technologies and encountered them only at a later phase of their lives. With the rise of new interactive and social platforms, such as MySpace, YouTube, Twitter and Facebook, the Internet became a channel of communication and was labelled Web 2.0. According to Fuchs (2008, p. 126), this change truly took place around 2005. Web 3.0 is seen to come about along with new platforms such as Wikipedia and GoogleDocs, which require cooperative and real-time efforts from users. It is increasingly based on synchronous forms of communication, such as instant messaging, chatting and video conferencing, which complement the older social functions of the Internet that were more intermittent by nature. It is especially these social functionalities of Web 2.0, and the cooperative and relative communicative uses of the Web 3.0, that can be seen as peculiar to the 2DG born in the 1990s or later. can be divided into synchronous and asynchronous activities. Synchronous activities necessitate that at least two people are simultaneously involved in an activity. By contrast, asynchronous use does not require simultaneous availability of both parties. At that time, Wellman et al. could not find demographic characteristics that would be strongly related to any synchronous online activity, only that respondents with a university degree were more likely to be users of synchronous Internet activities in their study, analysis of which was based on a sample of US and Canadian citizens. The authors assumed that the reason for weak and no associations was the wide penetration and use of the Internet in the given countries. It is worth noting that at that time the 2DG was still very young, and hence was not included in their sample.
Considering this parallel development of Internet technology (from asynchronous to increasingly synchronous) and user generations (from late age adopters to infants and toddlers embedded in the digital world), it makes sense to approach the social uses of the Internet by dividing them into synchronous and asynchronous modes of communication.
Given the limited number of relevant measurements in the used data, the following five modalities of the social use of the Internet will be analysed more carefully in this paper. Synchronous modes of communication include instant messaging (IM) that, according to Baron (2008), became a widespread phenomenon in the US in the late 1990s.
Baron maintains that it was at the turn of twenty-first century that 'America's teenagers and college students shifted their computer allegiances (if they had any yet) from email to IM' (Baron, 2008, p. 45). This means that the growth of IM took place at a time when 2DGs were only at the age where they began to use digital communication technologies. Baron also shows the gendered nature of IM: women are more "talkative" than men. Unsurprisingly, the use of IM services is much more popular among younger generations than older ones.
Statistics Finland (2014), which collects information only about the use of IM services via a mobile phone (e.g. WhatsApp), reports that 88 per cent of 16-24 year-olds had used these services within the last three months, and 75 per cent of them on a daily basis in 2014. The rates of IM service use decline rapidly towards older age cohorts. Of 55-64 year-olds, only 13 per cent have used these services with the last three months. The other synchronous mode of communication investigated here is the use of Internet telephony. As a mode of communication, it is even more novel than IM; yet, as a medium of oral communication, it supplements the mobile phone and the fixed telephone. Previous results show that cost effectiveness is one of the main motivators for the adoption and use of Internet telephony (Constantiou & Kautz, 2008;Park, 2010). Research work from Denmark and the UK indicates that the youngest users are perhaps not the most active users of Internet telephony, which accounts, at least partially, for the common and more regular use of Internet telephone calls for professional purposes (Cecere & Corrocher, 2011;Constantiou & Kautz, 2008).
Besides employees, studies show that housewives could be more active users of Internet telephony than other social groups (Cecere & Corrocher, 2011, p. 528). In 2013 in Finland, males (23 per cent) used slightly more often Internet telephony and video conferencing than females (19 per cent). The usage is also clearly more uncommon among 45 year-olds and older than among younger people (Statistics Finland, 2013). Also high level of education, young age and students are connected to use of Internet telephony and video calls in Finland (Statistics Finland, 2012, p. 32).
Three other measures are used to investigate asynchronous modes of communication.
Social network sites (SNSs), such as Facebook and Twitter, have been defined as web-based services that allow people to build a public or semi-public profile within an enclosed system, to manage whom they share a connection with, and to view and crisscross their connections as well as those made by others (boyd & Ellison, 2007). In Baron's study (2008, p. 88) targeted at college students, women outpace men in being more frequent Facebook users and spending more time per day on the Internet. Hargittai's study (2007, pp. 286-289), which surveys American college students, and the study by Vasalou, Joinson and Courvoisier (2010, p. 722), which is based on data collected from Facebook users from five countries, both reveal the higher likelihood of women being SNS users when compared with men. In Finland, women were more frequent users than men of SNSs in all age brackets in 2012.
Women also considered themselves as more active agents on social networking sites than men (Statistics Finland, 2012, pp. 19-20).
The second asynchronous form of Internet use investigated here is blogs. The term blog emerged from 'web logs' as the blogging gained more visibility. Blogs are regularly modified web pages, which include various types of data entry in reverse chronological sequences (Herring, Scheidt, Wright, & Bonus, 2005). In 2003, at the time when blogs were only just gaining popularity, Herring et al. (2005, p. 150) found that a slight majority of blog authors were young adult males. According to Statistics Finland (2012, p. 33), women read blog postings (42 per cent) more typically than men (34 per cent) in Finland. It seems that with the rise of fashion, beauty, decoration and mummy blogs, the sphere of blogs has become feminized. Furthermore, official statistics from Finland show that reading activity also decreases with age, and most active blog readers live in the capital region. Students and highly educated people are amongst the most active blog readers in Finland (Statistics Finland, 2012).
The third asynchronous form of Internet use considered in this study is online discussion forums (ODFs). These forums are based on asynchronous text-based communication (blogs include also pictures, videos, etc.), which make possible records of written messages without loss of data (Yang, Li, Tan, & Teo, 2007, p. 572). ODFs represent the oldest form of social functionalities of the web analysed in this study. Yang et al. (2007) write that there were already many research projects on the use of ODFs, especially within student populations, carried out in the 1990s. Herring's (2003) study also documents that women-focused groups, where women were able to share experiences, began to proliferate as early as at the turn of the 1990s. Burr and Smith (2003), in their study of the users of a university's ODF in Australia, indicate smaller gender and age differences. Women students were actually better represented in online discussion forums than men, and the use of online discussion forums increased rather than decreased with the age of the student. While there is no solid up-to-date statistical evidence on the popularity of ODFs in Finland, the most relevant data in this respect considers messages written and posted on the Internet (excluding emails). These figures, produced by Statistics Finland (2012, p. 32), reveals virtually no gender or educational differences. However, under 35 year-olds, students and people living in a capital region are more active message composers than others in Finland.
Lastly, it is in place to stress the vividness of the relationship between generations and digital social media. In today's technology intensive world, the adoption and ways of using new technologies determine increasingly our generational consciousness. We become members of a generation by using technologies and media that are typical for it (Buckingham, 2006). However, digital technologies regenerate themselves at an accelerating pace, and younger generations especially easily change to newer technologies and applications. This is not only because of their technological progressiveness, but also because of their social need to find places of interaction that are beyond the reach of parental monitoring. The Internet provides for contemporary children and adolescents an arena where they can perform socially and nurture peer relations. In the past, these activities were practised in the public spaces of a town or city, which nowadays are often considered too unsafe for young people by their parents (boyd, 2014) In contrast, some other studies suggest that young people also share more and more new technology and digital content with their parents and grandparents (Baron, 2008, p. 233). Hence, it is clear that new digital and social technologies provide tools to enhance intrafamily communication and intergenerational solidarity (e.g. Dolničar, Hrast, Vehovar, & Petrovčič, 2013;Lam, 2013;Wajkman, Bittman, & Brown, 2008), and in this process a transitional 1DG may play a key role as they are more familiar with both old and new media than the 2DG, which is increasingly digital-only.
Having said all this, it is obvious that generations are in a constant process of 'doing a generation' rather than in a passive state of 'being a generation' (cf. 'doing a gender' on Butler, 1990;also Fortunati et al., forthcoming). In this process, a generation specific new technology may lose its determining role surprisingly quickly, and become replaced with a new technology, application or practice of use. In terms of analytical strategies, this implies that it is essential to study various social uses of the Internet separately, yet side by side.
Bunching all these uses together and treating them as 'one social media' would prevent mode detailed understanding of generational differences in the social uses of the Internet.

Hypotheses
Based on the above reviewed literate and considerations, the following hypotheses are defined for the study next. The survey was pre-tested with ten persons. The response rate of the survey was 24. The characteristics of the unweighted data are presented in Table 1. In all analyses, weighted data are used to correct skewed gender and age distributions which result from the higher nonresponse rate of 25-34 year old men and 35-44 year old women when compared with other groups.
The design of the questionnaire benefitted from two earlier survey studies. A majority of questions was adopted from the 'Telecommunication and Society in Europe' telephone survey that was carried out in Italy, Spain, Germany, France and the United Kingdom in 2009. This survey is a partial replica of another survey conducted in the same countries in 1996 (Fortunati & Manganelli, 1998) Table 1 about here --

Dependent variables
Regarding the social use of the Internet, the following item from the questionnaire was employed: 'When using the Internet from home, which of the following activities do you practise at least sometimes?' The question was followed by a list of 25 activities, of which the following five are analysed in the present study: 'Use Messenger or other instant messaging service'; 'Make/receive calls with Skype or similar application'; ' Visit social networking sites (such as Facebook or MySpace)'; Visit blog sites'; and 'Take part in online discussion forums'. The supplied answering choices were 'Yes' and 'No'.

Independent variables
Generations were defined by asking for the year of birth, which was then recoded into full years (M = 44.45,SD = 15.07, and further into three categories guided by previous research: digital immigrants (DI) (born before 1980); the first digital generation (1DG) (born between 1980 and 1989); and the second digital generation (2DG) (born 1990 or later). To measure gender, fixed answering categories, 'Male' and 'Female', were supplied.

Education level was measured as the highest completed level of education in accordance with
The International Standard Classification of Education (ISCED 97). The ISCED scale was recoded in three new categories to ensure the sufficient number of cases in each category: 'Low education' (ISCED levels 1 and 2), 'Medium education' (ISCED levels 3, 4 and 5b), and 'High education' (ISCED levels 5a and 6). The indicator for main activity was recoded from the question 'What describes your current situation best?' with the answers 'Employee', 'Housewife/-husband', 'Unemployed', 'Pensioner', 'Student' or 'Other'. Measurement for children was developed from a question with ten fixed answering categories measuring the type of household. With recoding categories, a dummy variable with 'No children' and 'Children (one or more)' categories was produced. It is worth noting that children are not inevitably the respondent's own, but belong to the same household. Household income was measured by asking 'What is the total annual income of your household? That is, the approximate total of all salaries, pensions and other revenues.' Answering categories ranging from 'Less than 20,000 Euros' to 'More than 80,000 Euros' were supplied (M = 4.32, SD = 2.32, Range = 1-8). Lastly, the degree of urbanization of a respondent's place of abode was ascertained by asking 'How many inhabitants has your city/town/village?' and by providing eight answering categories. The answering categories were reduced to three, as outlined by the OECD: essentially rural (less than 5000 inhabitants), relatively rural (5001-100,000 inhabitants) and essentially urban (more than 100,000 inhabitants).

Statistical methods
The data was analysed by using both bivariate and multivariate statistical tools.
Distributions of dependent variables were analysed and presented by using contingency tables, chi-squared tests and standardized residuals. Logistic regression analyses (LRA) were conducted with an entered model, where the five social functionalities of the Internet worked as dependent variables. The Hosmer-Lemeshow test was used to indicate the goodness-of-fit of the LRA model. To identify the overall proportion of the variance explained by the model, Nagelkerke statistics were referred to (Tabachnick & Fidell, 2007, pp. 459-461).
Furthermore, the total percentages of correctly predicted cases were analysed to assess the predicting capacity of the model.

Results
This section starts by looking at how common it is for different generations to use the social functionalities of the Internet. Table 2 presents distributions of five uses by generations without controlling any other factors. It shows that 2DG is the most engaged in all the studied activities, with the exception of visiting blogs. Blog reading is the most common practice among 1DG. With regard to instant messaging, social networking sites and online discussion forums, 1DG holds the second place. DIs really seem to be the least involved in social uses of the Internet, yet regarding Internet calls, the differences between three generations are not statistically significant. Table 2 about here -

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The main results of this study are presented in Table 3, which summarises the outputs of five logistic regression models. Four out of five regression models explain between 17.9 and 29.0 per cent of the total variance. Only the model for Internet calls obtained a lower Nagelkerke's pseudo R 2 , which was 9.9. As a response to H1, which maintained that 2DG is more likely to use the social functionalities of the Internet than 1DG, the models reveal that it is only the synchronous forms of communication that make this difference. The youngest Internet users are more active using instant messages and Internet calls, both of which require simultaneous availability of the people engaged in the communication act. Instead, the analysis does not reveal statistically significant differences between 1DG and 2DG regarding the asynchronous forms of online communication. Both digital generations are actually relatively active on social networking sites, blogging and using online discussion forums.
Given these results, H1 must be rejected. Table 3 about here --The second hypothesis, H2, presents that 2DG is more likely to use the social functionalities of the Internet than digital immigrants. The results of this study do not provide solid support for this hypothesis either. From Table 3, it appears that DIs are not perhaps so categorically different from 2DG than is commonly believed when a range of other sociodemographic factors is controlled. It is true that DIs are less often engaged with the synchronous modes of communication and social networking sites than the newest generation of digital natives. Nonetheless, concerning the use of blogs and online discussion forums, the regression models are not able to confirm the statistical significance of generational differences (although the coefficients are relatively low). Table 3 also provides many noteworthy results in respect to H3, which assumed that with the exception of high educational level, socio-demographic variables are not strongly associated with the social uses of the Internet. First of all, it can be noticed that the level of education is only related to the higher levels of Internet calls and discussion forum usage.

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These practices of Internet use, especially among older users, serve professional and more functional purposes (e.g. Cecere & Corrocher, 2011;Constantiou & Kautz, 2008) while the rest of the studied practices of Internet use-instant messaging, social networking sites, blog use-are more utilized for non-professional purposes, and for this reason are not related to educational achievements either.