BRICs & clicks: Insights into the sociomateriality of consuming social networking sites

Lichy, Jessica; Khvatova, Tatiana; de Oliveira, Mauro

doi:https://doi.org/10.59876/a-g6kv-zvn6

This study compares the sociomateriality of consuming social networking sites (SNS) in four emerging economies – Brazil, Russia, India, China – to further the understanding of SNS user behaviour and digital interactivity in BRIC markets. The terms “SNS user behaviour” and “SNS usage” describe the routine activities associated with consuming SNS—i.e., sharing digital content (photos, disclosing personal information, participating in discussions), preferred platforms and user interactivity (Bhatt, De Roock and Adams, 2015).

Scholars examine users’ routine activities to further our understanding of SNS user behaviour (Bhatt et al., 2015). Studies show that user behaviour is socially constructed, shaped by communication and information practices that link the actors and technology (Koga and Yanagihara, 2017). SNS usage is influenced by the content consumed (Li, 2013; Lin and Utz, 2017; Omar and Dequan, 2020), by other users including digital influencers (Djafarova and Trofimenko, 2019; Silva et al., 2020) and by the cultural context (Lichy and Merle, 2020; Lichy and Racat, 2021). However, these studies overlook the sociomateriality perspective, which examines SNS usage as an enactment between human and material agency. A core interest of this study, therefore, is to use sociomateriality to explain SNS user behaviour, and connect it to theories of culture with reference to communication and information practices. We hold that theories of culture have focused on broad communication and information practices, without adequately considering material factors, such as emerging and local SNS user behaviour. We address this gap by adopting sociomateriality as a theoretical frame with which to approach the study of culture-specific SNS user behaviour, to develop digital “hacks” (i.e., advice) in the form of “general digital hacks” and “context-specific hacks.”

Acknowledging that sociomateriality is multifaceted and context specific (Parmiggiani and Mikalsen, 2013), we develop a framework of digital culture to show the effects of BRIC cultural contexts and sociomaterial context, and how these factors can be used to explain SNS user behaviour. Digital culture describes the interdependence of the “material” (the roles played by technology) and human agency (what humans can achieve) (Orlikowski and Scott, 2008). Guy (2019: 56) defines digital culture as “social forms” (noticeable patterns of communication emerging in a crowd of individuals) and “cultural mindset” to emphasise “how current digital technologies are tailored to a human (individual) scale.” This definition embraces the social process of using information and communication technologies, shaped by the surrounding environment (i.e., cultural context) in which individuals make sense and engage with technology (i.e., sociomaterial context) (Leonardi and Barley, 2010a; Bhatt et al., 2015).

SNS accentuate the inherently sociomaterial character (Orlikowski, 2007) of the discursive practices that take place on and through digital technologies. Leonardi (2010) argues that when materiality is understood to represent the practical instantiation and the significance of an artefact, digital artefacts (such as “like,” “follow” and “comment and share”) can clearly be seen to have materiality, as they continuously provide both opportunities and constraints for action. The materiality of SNS enables a user to edit and re-edit comments and digital content before actually clicking “post” or “share” (Leonardi, 2012). In the flux of the activity itself, actors create the opportunities for their own actions; however, for Leonardi (2012), materiality is a context and even a condition for action, while for Orlikowski (2007), materiality is more the consequence of an action.

Boyd and Ellison (2008) define SNS as online services that allow users to create a personal profile, connect with other users, and navigate through networks of contacts, creating and sharing content. The popularity of SNS can be attributed to the widespread availability of mobile technologies, which connect the virtual space to the physical space, and move users between them in a way that enhances both, bound by the cultural context (Lichy and Merle, 2020). Businesses use digital content to influence and stimulate the development of consumer engagement, trust and relationships (Hollebeek and Macky, 2019), yet managers may be overlooking cultural factors that influence sharing information online, which can affect relationship building (Payne et al., 2008). The use of SNS has become a global phenomenon, warranting a better understanding of user behaviour in different national contexts (Arora and Scheiber, 2017) to extend “the scope of questioning and theorizing about the Internet beyond traditional national and cultural boundaries” (Kluver and Yang, 2005: 307).

With the exception of Wang and Choi (2019) and Biryukova and Matiukhina (2019), few scholarly studies have compared SNS user behaviour in BRICs, though various scholars have explored the Chinese context per se, which “can be attributed to China’s ring-fenced internet economy” (Tamilmani et al., 2018: 125). There is a lack of cross-disciplinary research on sociomateriality, digital interactivity and culture (Meske, Kissmer and Stieglitz, 2020), as an enactment between human and material agency (Fenwick, 2016). Furthermore, Schlagwein and Prasarnphanich (2014: 123) suggest that the cultural impact on SNS “might be even stronger compared to more traditional technologies because of the openness, transparency, and equality embedded in social technologies.”

This study takes theoretical perspectives from different national contexts, as advocated by Bell and Willmott (2015) and Santello (2015). The intention is to remove the bias that suppresses sociomaterial differences in our understanding of SNS usage in different settings (Steenkamp, 2019) and address “the need for further research into ICT usage in non-Anglo-centric markets” (Lichy and Merle, 2020: 155). Acknowledging that technology does not occur in a vacuum but instead encompasses social and cultural phenomena (Davies, 1988), our interest focuses on how individuals in BRICs use SNS within their respective cultural context (Leonardi and Barley, 2010a).

Against this background, our objective is to, firstly, examine differences in SNS user behaviour across BRIC countries, paying attention to context (cultural and sociomaterial) which may influence user behaviour, and secondly to contribute to the sociomateriality literature on SNS usage in BRIC contexts. While the cultural dimensions of Hofstede (2001) act as structural inspiration for this paper, we take an interpretive approach and empirically develop his framework by integrating digital materiality (Leonardi, 2010b; Morizio, 2014) into the cultural dimensions, to illustrate the sociomateriality of SNS user behaviour in the BRIC context. Thus, we develop the following research question: What differences exist in the sociomateriality of SNS user behaviour in the BRIC cultural context?

We use a two-step approach (survey and interviews) to gather information on SNS user behaviour, in line with Lichy and Racat (2021) in order to understand, interpret and explain SNS usage. Our analyses identify a number of characteristics of culture-specific SNS user behaviour that can inform businesses for leveraging digital interactivity, from which we develop management implications.

There now follows a review of literature, presentation of methodology, results and discussion, management implications, followed by concluding comments.

Literature review

The following paragraphs discuss relevant literature to address the research question—highlighting the relevance of sociomaterial considerations in different-yet-comparable contexts.

Sociomateriality and digital interactivity

Researchers use the term “sociomaterial assemblage” (Orlikowski and Scott, 2008; Cecez-Kecmanovic et al., 2014; Fenwick, 2016) to visualise digital interactivity as constitutive entanglements of social and material agencies. This view holds that there are no independently existing entities; they materialise and attain different qualities through their particular relations and configurations, assembled by user practices (Bhatt et al., 2015). Sociomateriality asserts social practices are intrinsically conjoined with the technologies in use, mutually and emergently productive of one another (Orlikowski and Scott, 2008)—thus, “what technologies achieve in practice can only be understood by focusing on their material performances, which are always enacted by humans” (Jarrahi and Sawyer, 2013: 112). The material features of technology influence how users make sense and engage with technology (Jarzabkowski and Pinch, 2013).

In Information Systems research on user participation in online communication, Harris and Abedin (2015) show that social and technological aspects of online participation overlap and function interdependently to become sociomaterial. Online communities reflect how technical and social elements are embedded into one identity (Faraj et al., 2016), forming “instances of sociomaterial systems” (Picazo-Vela, Fernandez-Haddad and Luna-Reyes, 2016: 693). Businesses encourage user participation in online communities, in an effort to build relationships with users (Hollebeek and Macky, 2019). Priharsari and Abedin (2021) highlight the influence of cultural values, arguing that users of online communities in different countries and cultures behave differently.

“Digital materiality” is a relatively new concept in Information Systems research, denoting the “materiality” of digital artefacts in SNS such as “like,” “follow,” “comment and share” (Morizio, 2014; Luo and Hancock, 2020). Digital artefacts are understood as “assemblages” generated from sophisticated interactions between technological, social and cultural factors (Lupton, 2014; Caplan, 2013), subject to human interpretation and contextual influences (Leonardi and Barley, 2010a). Exploring digital artefacts in Chinese SNS, Zhao and John (2020) found that the English concept of “sharing” (i.e., digital participation) cannot “be unproblematically transferred into the Chinese context, reinforcing the need to continue to de-westernize communication research” (p.14); however, this view does not present a comprehensive picture of users in the other BRIC contexts. The existing literature on SNS user behaviour does not fully explain the influence of cultural context and the ways in which users have appropriated SNS. Our study sets out to fill this gap, and make a relevant contribution to international management by explaining the sociomateriality of SNS user behaviour in BRICs that may lead to a shift in current practices.

BRIC cultural context

Culture is a group-specific, collective phenomenon of commonly shared values: “[Culture] is the collective programming of the mind which distinguishes the members of one group or category of people from another” (Hofstede, 1991/1994, p.5). In each country, commonly shared values form society. Summarised in Tables 1a&b, these values describe the socio-cultural context that influences the perception of a brand or product/service in each context. This approach is used as a tool to generalise country-specific habits (or cultural context) for gathering potential business opportunities; it is relevant to explore the extent to which this notion can be applied to the sociomateriality of consuming SNS.

Table 1a

**BRIC comparison of Hofstede’s dimensions (0 lowest-100 highest)**

Since the official establishment of BRIC (Brazil, Russia, India and China) in 2009, this group of countries has showcased their industrial power in global economic developments (BRICS, 2018; Meyer and Meyer, 2019). Representing around 40% of the world’s population, the BRICs have received heightened academic interest owing to their rapid growth and economic resilience during the global financial crisis (Delcoure and Singh, 2016; Beeson and Zeng, 2018). Ranked among the most promising emerging economies and covering more than 25% of global GDP, the BRICs have strong trade connections inside and outside the group and are growing faster than overall world trade (Galloppo and Paimanova, 2017). Lingenfelter (2006) estimates that by 2040, the BRIC economies will be greater in absolute size than that of G6 (US, Japan, UK, Germany, France and Italy) countries.

Table 1b

**Definitions & relevance of Hofstede dimensions to SNS usage**

As regards digital development, studies confirm the steady growth of technology adoption and usage in BRICs (Cruz-Jesus, Oliveira and Bacao, 2018), and the preference for local SNS that cater to local tastes and languages (Singh, Lehnert and Bostick, 2012; Tamilmani et al., 2018). The BRICs are collectivist cultures, thus it is easier to connect and communicate with people if they are part of an “in-group” (Hofstede, 2001); time and trust is needed for “out-group” members to be accepted into the network of the group. Fuchs (2015) and Distefano et al. (2016) note the positive impact of network relations and interactivity for driving socio-economic growth.

BRIC technology usage

While the BRICs are often portrayed as lagging behind developed countries regarding digital infrastructure, they have been able to leverage digital technology (Avdasheva and Korneeva, 2019) and integrate SNS into routine behaviour (Cheung et al., 2020). In each of the BRICs, there are peculiarities in using SNS that may challenge businesses wishing to enter these markets (Singh et al., 2012). For example, there is a high diversity of cultures within each country (Schwartz et al., 2010) and uneven Internet speeds, yet Russia holds third place (behind USA and Japan) in the world for the percentage of Internet users: 79.7% in 2020 (Statista, 2020). While scholars have explored the use of information and communication technologies in BRICs (Chan and Daim, 2012; Ying, Miao and Yibo, 2014; Jabalameli and Rasoulinezhad, 2019), less is known about how users per se interact and share content, or how this can be used by businesses for leveraging digital interactivity. Understanding how individuals consume SNS is complex, as the online environment is continually fragmenting into new segments that transcend geographic borders, cultures and languages (Lichy and Racat, 2021).

The growth of local SNS (such as VK in Russia and Tencent QQ in China) reflects national efforts to challenge global platforms, namely Google, Apple, Facebook, Amazon and Microsoft, by exploiting cultural identity (Dey et al., 2018) and digital culture (Makri et al., 2019; Guy, 2019). For example, LinkedIn is banned in Russia (Lichy, Kachour and Khvatova, 2017) and many Western SNS are blocked in China (Lee, 2016). Internet users who wish to access the Internet beyond national borders can use a Virtual Private Network (VPN), which will mask the user’s Internet address, however, it is illegal for Chinese citizen to use a VPN to access content from outside China. The following table gives estimates of population, Internet penetration and regulation in BRIC countries.

Table 2

**Population, Internet penetration & censorship**

SNS — a user perspective

Since the inception of SNS, users have progressively discovered the many different things that they can do online. Simultaneously, users have had to teach themselves how to consume SNS, given that SNS can be used in numerous ways, thus “Out of this dual experimentation emerged our current digital culture not as the natural expression or extension of these technologies, but as a social selection with consequences for the same technologies” (Guy, 2019: 56).

Comparisons of SNS user behaviour are difficult, partly because the statistics available rarely provide equivalent figures for equivalent periods. Furthermore, in China and Russia, many well-known global brands are either refused legal entry or eclipsed by their national competitors (Sparks, 2014; Steenkamp, 2019). While these studies highlight the need to protect consumer rights (Ostanina and Titova, 2020) and to fight crime (Nikitin and Marius, 2020), they overlook how individual users engage with SNS and how businesses can leverage digital interactivity from these users.

SNS enable a user to build a digital identity that carries symbolic meanings (Heimbach and Hinz, 2018), portraying an idealised representation of the offline self. Kimmel (2010) suggests that our behaviour is more than simply “just human nature”; we actively create our identities from the materials we find around us in our culture such as other people, ideas and objects (Makri, Papadas and Schlegelmilch, 2019) and in our digital culture (Guy, 2019). The consumption of SNS offers a fertile ground for understanding user behaviour (van Dijck, 2013; Baluch, 2016), by providing a statement about who the user is (Coyne, Padilla-Walker and Howard, 2013) and what makes them interact and share content in a particular context (Li, 2013).

SNS have opened the floodgates to users’ self-disclosure of thoughts, feelings and experiences online, triggering research interest among academics and practitioners in what people share, why they do it, and how it may affect the user’s life and the lives of other users. The widespread use of smartphones for accessing SNS has facilitated self-disclosure (Chen et al., 2019; Melumad and Meyer, 2020). SNS make publicly visible other users’ feedback through #hashtag comments and digital artefacts (Morizio, 2014; Luo and Hancock, 2020). Self-disclosure has resonance for digital interactivity—since users are influenced by the content they consume and generate (Li, 2013; Lin and Utz, 2017; Omar and Dequan, 2020), and by the user’s view of him/herself that originates from other online users (Ray, Kim & Morris, 2014). Users share digital “hacks” (i.e., advice) for enhancing their self-image and interactivity (Djafarova and Trofimenko, 2019), including the use of fictitious content (Zannettou et al., 2019). Businesses seek to work with users who generate persuasive messages and emotional reactions, in an effort to create content and build brand awareness (Djafarova and Trofimenko, 2019). However, studies tend to overlook the impact of local culture on the consumption of SNS and the different ways in which users create and share content in BRICs (cf., Lichy et al., 2017; Beeson and Zeng, 2018; Slusarciuc, 2019; Priharsari and Abedin, 2021). This information would be useful for international businesses. The following section explains the methodology for collecting data on SNS user behaviour in BRICs.

Methodology

A two-step approach was used to gather information on SNS user behaviour (survey and interviews), in line with empirical studies that are more often used to explore and elaborate new theoretical objects than to test them (Snow and Thomas, 1994); our focus is on “how and why” instead of “how much/many” (Silverman, 2013).

Owing to the lack of reliable information on SNS user behaviour in BRIC countries, we designed our own survey instrument (developed from the literature), as advocated by Lichy and Racat (2021). Following Singh et al. (2012), the survey questions collected information on routine SNS usage, focusing on interactivity for sharing content (Djafarova & Trofimenko, 2019). We designed 10 questions to address different types of information shared via SNS (i.e., personal, professional and corporate), preferred platforms, routine SNS usage, and socio-demographic data (see Appendices).

Following a pilot-test, two questions were modified to improve clarity. Question 1 was rephrased “What is your nationality and residence?”, so that Chinese nationals who reside in China (for example), would answer “Chinese.” Secondly, question 6 was amended to “What do you know about Big Data analytics?” as a proxy for gauging users’ concerns about their data privacy while using SNS, in line with Lichy et al. (2017) who found this approach would reveal respondents’ perceptions of data privacy and surveillance.

Distribution of survey

First, the survey was posted on the website of an organisation (https://www.figs-education.com France International Graduate Schools, FIGS) that employs career advisors in BRIC countries (and elsewhere), and on LinkedIn given that such platforms are widely used for interpersonal communication, information and career development (Garcia and Al Nima, 2016). The post invited respondents residing in Brazil, Russia, India and China to participate in a study on SNS usage. Next, by means of snowballing (i.e., relying on informal social networks), as advocated by Milroy and Milroy (1992), the FIGS career advisors in each BRIC country were invited by email to nominate further contacts from their social and professional networks to take part in the survey. Thus, the respondents form a relatively homogeneous group that can be described as young adults, career-seeking, digitally-literate BRIC nationals. Survey data were collected over 6 months then analysed using SPSS. The responses gathered are indicators of SNS user behaviour.

Second, in-depth personal semi-structured interviews were undertaken in collaboration with the FIGS career advisors. Eight career advisors were invited to identify prospective respondents. A prerequisite for participating in the study was that respondents must regularly use SNS (i.e., over 1 hour/day) and be a resident and citizen of a BRIC country. Twenty-two individuals were identified and invited to participate in one-to-one interviews (see Table 3b). Anonymity was guaranteed. Copies of the interview questions were made available prior to the interviews. Each interview lasted approximately 1hour. The interviews were transcribed, then manually analysed thematically using Template Analysis to generate major themes and sub-themes (King, Horrocks and Brooks, 2018). Equal attention was given to each recorded data item; highlighters were used to annotate each transcript, and to indicate potential patterns or themes in the data that characterise SNS user behaviour, paying attention to surrounding data in order to avoid downplaying context (Bryman, 2016).

The survey yielded quantitative data from a wide public yet it lacked depth; the interviews generated qualitative data that allowed us to go deeper into SNS user behaviour, given that behaviour reveals psychological aspects (e.g., physical, mental and social activity) of SNS usage that are commonly found amongst SNS users. The use of both methodologies allows us to perfect the subject.

Data analysis

The results are divided into sections to show: demographics of the sample, cross-tabulation, dependencies between variables with Chi-square criterion, and analysis of interview data.

Demographics of the sample

The survey yielded 765 returns, with 42.7% from individuals aged 18–30 years and 57.3% aged 30+ years (see Table 3a).

To begin, let us analyse the whole sample. In response to the question “What kind of personal information do you share via SNS?”, 69.8% of SNS users share photos, 52% share their personal opinions and ideas, 42% share their interests and hobbies. For the question “What type of professional information do you share?”, 51.8% of respondents share their work-related interests, 40.8% of respondents share photos connected with their professional activities, 37.3% share professional opinions and ideas. Concerning sharing corporate content, over half of the respondents post corporate photos on SNS, 28.2% of respondents respond to corporate posts, and 7.1% of the respondents have discussions with external stakeholders.

Regarding sites used regularly, the most popular response given by participants in Brazil, Russian and India is Facebook (85.9%), Instagram (51%) and Skype (40.8%), consistent with Jarzabkowski and Pinch (2013). The Chinese participants admitted using a VPN for engaging with non-Chinese SNS, alongside the abundance of superior local SNS; they cite using WeChat (micro-messaging), Sina Weibo (microblogging), Tencent QQ (instant messaging app and web portal)—confirming the findings of Tamilmani et al. (2018).

On the issue of data privacy, over a third of respondents claim to have “no idea” about Big Data analytics (36.1%). However, 32.9% believe that it generates “more accurate information about consumer profiles” and a “better match of supply and demand”; 30.6% think it creates business opportunities.

Cross-tabulation

Contingency (cross-tabulation) tables were constructed to explore dependencies between pairs of the sample characteristics—that is, (a) gender and SNS user behaviour, (b) nationality and SNS user behaviour, and (c) age and SNS user behaviour. Note that “gender is a co-shaped, changing part of human-identity tied into the sociomateriality of gendered relations often treated as a binary dichotomy” (Fosch-Villaronga et al., 2021: in press)—hence the inclusion of gender.

Cross-tabulations of survey answers with the variable “gender”

Men are more active than women in sharing personal information. The difference is especially noticeable in responding to information posted on SNS; whereas 45.9% of men respond to posts, only 28.3% of women do. However, women and men equally enjoy sharing photos via SNS.

For sharing professional information, men are (again) much more active. Women only exceed men in sharing professional photos (46.7% against 35.6%). The difference is especially visible in sharing professional opinions via SNS; while 45.2% of men share professional opinions, only 28.3% of women do. Men and women are almost equal in sharing work-related interests.

A similar result is noticed in sharing corporate information: men are more active than women in sharing information relating to their employer. Although women share corporate photos more often, men like to respond to posts (32.8% against 20.8%); men share corporate opinions twice as often as women do.

Concerning platforms, mainly men used Twitter and WhatsApp, whereas women preferred Pinterest (28.3% against 7.4%). More men use WhatsApp, Skype and Facebook than women. Moreover, while Twitter and Facebook have global appeal, Instagram is very popular in Brazil; whereas in China, WeChat, Sina Weibo (“Twitter of China”) and Tencent QQ (Instant Messaging) are better positioned to cater to local user preferences.

On the issue of data privacy, almost half of the women are unfamiliar with the term Big Data analytics (49.2% against 24.4%); men see it as a business opportunity (37% against 23.3%); 45.2% of men think that it is about generating more accurate customer profiles and matching supply and demand.

Regarding additional activities performed via SNS, women play games more often than men, while men chat more often than women (via WeChat and Twitter). These results reveal a gender split in SNS user behaviour that was not previously reported in the literature.

Cross-tabulations of survey answers with the variable “nationality-residence”

Overall, sharing personal photos (74.7% of Brazilians, 77.1% of Russians, 57.6% of Indians, 71.2% of Chinese) and sharing personal opinions are the two most popular responses. Brazilians and Russians are leaders in sharing photos. Brazilians are far ahead of others in their desire to share personal opinions via SNS (62.7% against only 39.7% in Russia, for example). Although “expressing personal opinions and ideas” is not found to be a very popular activity among Russians (only 39.7% chose this answer), Russians like to read and react to other people’s posts, more than the other nationalities. In addition, the Russian respondents indicated “discussions with friends” as an important activity (more than other nationalities). Indians share personal photos much less frequently than others do (57.6%, compared to over 70% for other nations). Russians share the most photos (77.1%). Brazilians enjoy sharing personal opinions (62.7%), while only 39.6% of Russians share personal opinions and 47.0% of Chinese. Regarding commenting and sharing, Brazilians respond the least to posts (only 24.0% of participants mentioned this activity), and Indians respond the most to posts (45.5%)—see Fig. 1.

Figure 1

**Comparing responses: “type of personal information shared” vs. “nationality”**

Figure 2

**Comparing responses to “type of professional information shared” vs “nationality”**

Brazilians share more professional photos (46.7%) and express their professional opinions (46.7%). Russians express their work-related interests much more than the other nationalities in the sample (58.3%); Russians are most cautious about expressing their professional opinions (a modest 22.9%). Brazilians demonstrate the highest variety of communication activities while Russians seem to be the least active, especially in expressing their opinions via SNS. The enthusiasm of Russians to share their opinions is less than half of Brazilians—see Fig. 2.

These results contribute to SNS user behaviour by identifying the different types of professional information shared by BRIC users, which were not previously reported in the literature.

Figure 3

**Comparing responses to “type of corporate information shared” vs “nationality”**

Regarding sharing corporate information (Fig. 3), once again, we see that sharing photos is a very popular activity. Indians and Brazilians like discussing corporate issues with colleagues via SNS, while for Russians this activity is much less commonplace. Russians prefer to share company photos and respond to posts instead, rather than discuss.

Concerning the sites used regularly, the participants in each setting claim to use Facebook, WhatsApp, Skype, Twitter, Instagram to varying extents—which would infer that the participants are using a VPN to access SNS that are currently blocked in their country. The Chinese use WeChat more than any other SNS, and fewer Russians use LinkedIn—some 60% of Russians use VK, in preference to Facebook. The wide range of activities undertaken via SNS in China reflects the “fully mobile lifestyle” (see table 8) generated by the “transversal” relationship between technology, society and culture. This detail was not reported in the literature, yet it resonates with sociomaterial assemblages generated from interactions between technological, social and cultural factors (Lupton, 2014; Caplan, 2013).

When asked about data privacy (using the proxy “Big Data analytics”), over a third of participants in each country answered that they had no idea: 41.3% of Brazilians, 33.3% of Russians, 33.3% of Indians and 34.8% of Chinese. A popular interpretation among the participants is that it gives “a more accurate consumer profile/ better match of supply and demand”: 29.3% of Brazilians, 31.3% Russians, 36.4% of Indians and 34.8% of Chinese. Roughly one third of participants in each country think it provides new business opportunities but Russians perceive it as a risk, with 25% of people mentioning their fear. Brazilians seemed least aware (41.3%)—which may explain why people are so active on SNS in this country.

Concerning other activities performed via SNS, the participants responded similarly—namely, sharing photos (64% of Brazilians, 52.1% of Russians, 69.7% of Indians, 62.5% of Chinese); and also chatting, emailing and finding/meeting friends. Russians surpassed the others in chatting (77%) and joining online groups (60%).

It can be deduced that nationality (i.e., national/cultural context) has an effect on the consumption of SNS, in the sense that it shapes the interactions between technological, social and cultural factors (Lupton, 2014; Caplan, 2013). These nuances found in the data were not reported in the literature.

Breakdown per age group

Younger participants share most photos (90% of people aged 18–20, against only 30% of people aged over 30), and discuss hobbies with friends and family. People aged over 30 are significantly less active, although many share photos and personal opinions; however, they are noticeably more active in sharing professional information, especially work-related interests. This finding can be explained by the fact that these people are already active on the labour market, whereas younger people may still be looking for their first job. A similar situation is observed for sharing corporate information.

Despite state control of SNS in China, Facebook comes out as the absolute leader in SNS usage for each age group; Skype, Instagram and Twitter are most popular for 18-20-year olds; people aged over 30 prefer WhatsApp more than Facebook.

People aged 24–26 and 21–23 grasp the meaning and implications of Big Data analytics. For example, the participants recognise the benefit for surveillance (over 37% of people aged 21–26) for generating business opportunities and more accurate customer profiles (40–43% of people aged 21–26), though the notion of “risk” and “fear” is voiced by 25% of the participants. The data reflect the extent to which age determines SNS user behaviour.

After the preliminary data analysis, the following hypotheses are developed:

H1: SNS user behaviour is related to gender

H2: SNS user behaviour is related to nationality-residence (i.e., national/cultural context)

H3: SNS user behaviour is related to age group

H4: attitude towards data privacy is related to nationality-residence

H5: attitude towards data privacy is related to gender

H6: attitude towards data privacy is related to age group

Checking dependencies between variables with Chi-square criterion

The survey generated a substantial sample of data; processing the data is a task of checking pairwise independence (or dependency) of multi-level characteristics. To begin, redundant data were eliminated; then, the dichotomy “design” matrix 765 by 44 consisting of 1 and 0 (765 people sorted according to their nationality) was formed. A Burt matrix (44 by 44) was obtained in which the stacked categories are tabulated against each other.

Nine variables are analyzed (see Appendices). Q8 was excluded from the analysis (“Other activities undertaken via SNS”), as the responses to this question reiterated previous responses.

The Burt matrix can be used to check the H₀-hypothesis regarding pairwise independence (or dependency) of multilevel qualitative characteristics.

Hypothesis H₀: there is no relation between characteristics; i.e., they are independent;

Hypothesis H₁: there is a certain relation among characteristics, they are not independent.

To check these hypotheses, it is imperative to compare the observed value and the critical value for statistics in the Burt matrix. For this, we need to define the expected frequencies in cells that would occur if the H₀ hypothesis were right, so the characteristics would be independent:

The statistics of the criteria should have the chi-square distribution (χ ²). The observed value of the statistics is calculated as follows:

To check the hypothesis H₀, the critical value of the statistics is defined:

where α is the significance level (α=0,05), f=(r —1)(c —1) is the number of the degrees of freedom (r the number of rows in the Burt matrix, c is the number of columns). The were taken from the standard Chi-square distribution table.

After comparing the observed value and the critical value, it can be deduced that at the significance level 5%, the hypothesis H₀ (regarding independency of characteristics) can be accepted (if the observed value is smaller than the critical value) or rejected. Processing the data as described above allowed us to define relations between the categories—see Fig. 4. The categories are the nodes of the graph while the edges are the relations between them.

This figure allows us to draw a number of conclusions. The central nodes of the graph which bring together the graph are Q10 (age) and C (nationality-residence). Thus, the responses provided by the participants regarding SNS usage are conditioned by their age (i.e., life experience) and their nationality-residence (i.e., national/cultural context), both of which are shaped by sociomaterial assemblages.

Let us now consider the structure of the chains and loops of the considered characteristics. The biggest loop contains five categories: Q4 (types of shared corporate information) — Q10 (age) — Q7 (time spent on updating personal information) — Q5 (which site you are using) — C (nationality-residence) — Q4 (types of shared corporate information). These five categories form a connected area of the graph with which the hanging nodes are connected: Q3, Q6, Q2, G. The category Q3 (types of shared professional information) correlates with Q4 (types of shared corporate information), which is logical and automatically confirms the correctness of the obtained results. The category Q6 (data privacy) correlates with Q10 (age), which is a slightly unexpected result. Category Q2 (types of personal information shared in social networks) correlates with Q7 (how much time do you spend on updating personal information), which is reasonable and confirms our results. Category G (gender) correlates only with C (nationality), which reveals the gender composition in the countries studied. Clearly, gender bears little influence on SNS user behaviour, contrary to the literature (c.f., Fosch-Villaronga et al., 2021).

The core of the graph (consisting of the nodes Q4, Q10, Q7, Q5 and C) forms a tightly connected area where many nodes connect to each other and make additional cycles and loops: two loops of 4 and 3 loops of 3 categories. They overlap each other. There are no direct connections, only between: Q4 (types of corporate information shared) and Q5 (sites used) and Q7 (time spent on updating personal information); Q7 and Q4 and C (nationality-residence); Q5 and Q4; however, they are located in the same cycles which means they can sequentially influence one another.

It can be concluded that the hypothesis H1 “SNS user behaviour is related to gender” is not confirmed: the correspondence analysis proved that there is no significant connection between gender and other categories. Hypotheses H2 “SNS user behaviour is related to nationality-residence” and H3 “SNS user behaviour is related to people’s age group” are both confirmed: it is proven that these two categories influence all the characteristics of SNS user behaviour. As for attitudes towards data privacy, they do not seem to be connected to gender, thus H4 is rejected. Hypothesis H5 (attitude to data privacy is connected with nationality-residence) is also rejected—the correspondence analysis failed to find connections between Q6 and C. Rather surprisingly, the correspondence has been revealed between attitudes towards data privacy and age; therefore, H6 is accepted.

Analysis of interview data

By including a range of voices across BRIC settings, the research design highlights how creating and sharing information is linked to both national culture and digital culture. The interviewees articulated four transversal themes regarding SNS consumption: creating and engaging with content, distraction/entertainment, cautious engagement, and digital interactivity.

Figure 4

**Graphic representation of relations between SNS user characteristics**

Theme 1: creating and engaging with content

The interviewees discussed how SNS offer many opportunities to extend and enhance the pleasure of sharing information, expressing enjoyment for uploading UGC – especially photos, video clips and podcasts – that are viewed, shared and commented on across friendship networks. They attach great importance to posting content (personal and professional), which invariably leads to ongoing interaction, further comments, and storytelling on SNS, as the following excerpts show:

Excerpts from interviews “creating and engaging with content” — Table 4

**Excerpts from interviews “*creating and engaging with content*”**

Theme 2: distraction/entertainment

When discussing their routine activities undertaken via SNS, the interviewees mentioned using SNS as a source of distraction, highlighting the entertainment aspect of connecting/socialising with other users (worldwide) and admiring their UGC to encourage followers, as shown below:

Excerpts from interviews “distraction/entertainment” — Table 5

**Excerpts from interviews “*distraction/entertainment*”**

Theme 3: cautious engagement

Keeping up-to-date with other users and information (news and current affairs) was a common activity discussed by the interviewees; such activities are fundamental, as this interaction contributes to identity construction processes (especially digital identity) and building/maintaining friendships. However, they were aware of the impact of their interaction with other users and content. The excerpts below demonstrate the caution taken:

Theme 4: digital interactivity

The interviewees noted the influence of certain users who have a devoted social following on SNS and possess social influence over their followers (Djafarova & Trofimenko, 2019)—including vloggers and Internet celebrities.

The interview data show how SNS user behaviour is closely tied to identity (van Dijck, 2013), and how online content serves as an identity display, providing a statement about who the user is (Coyne et al., 2013), their cultural identity (Dey et al., 2018) and their social influence over their followers (Lou and Yuan, 2019).

Excerpts from interviews “cautious engagement” — Table 6

**Excerpts from interviews “*cautious engagement*”**

Excerpts from interviews “digital interactivity” — Table 7

**Excerpts from interviews “*digital interactivity*”**

Discussion

Addressing the research question, the sociomateriality of SNS user behaviour in the BRIC context can be explained by the transversal relationship between technology, society and culture. The findings lead us to draw a general conclusion, supporting the work of Hofstede (2001), that SNS usage is shaped by nationality—i.e., national/cultural context (Lichy et al., 2017; Beeson and Zeng, 2018; Slusarciuc, 2019). Furthermore, SNS user behaviour is shaped by the digital culture (Makri et al., 2019; Guy, 2019), evidenced by the consumption of local SNS that cater to user tastes and language preferences – e.g., VK pirated content in Russia and WeChat/Alipay digital wallet services in China – confirming the work of Tamilmani et al. (2018). While all the participants regularly consume SNS, alluding to the influence of other users (including prominent users cited in the interviews), their behaviour differs in the nature and extent of information created and shared, bound by the context (Lichy and Merle, 2020).

These observed differences symbolise the sociomateriality of SNS user behaviour in the BRIC context, capturing the assemblages generated from sophisticated interactions between technological, social and cultural factors (Lupton, 2014; Caplan, 2013). They confirm the literature underscoring the interdependence of the roles played by technology and what humans can achieve by using the technology (Orlikowski and Scott, 2008) in each national context. Framed by monitoring and censorship (Lee, 2016; Lichy et al., 2017), the routine behaviour of the participants represents the “materiality” of digital artefacts (Leonardi, 2010b; Morizio, 2014).

Our findings challenge the work of Singh et al. (2012) who found that BRICs do not distinguish between making friends, connecting with others, or reading content. In our study, the participants differentiated between other users (choosing how much to share and with whom) and were aware of their digital footprint (managing the content—i.e., personal, professional and corporate).

The cultural dimensions of Hofstede (2001) acted as structural inspiration for this paper, with which we developed a framework by integrating digital materiality (Leonardi, 2010b; Morizio, 2014) into the cultural dimensions (Hofstede, 2001) – see Table 8 – to illustrate the sociomateriality of SNS user behaviour in the BRIC context.

These observed characteristics can be used by individuals/businesses operating in the BRICs to identify and compare different types of user behaviour, with a view to leveraging digital interactivity, and to “nudge” consumers towards or against a particular consumption pattern.

Next, we take the findings with the literature on identity building (Makri et al., 2019) and digital culture (Guy, 2019) to develop a simplified framework of digital culture, which shows the variety of assemblages in BRIC contexts (Lupton, 2014; Caplan, 2013). The framework offers comparative insights into four types of SNS user behaviour, which can inform businesses operating in BRIC markets for leveraging digital interactivity.

Table 8

**Observed characteristics of culture-specific SNS user behaviour—in relation to Tables 1a&b**

Framework of digital culture

Demonstrative (Brazil, India) vs Reticent (Russia, China)—the extent to which a user will post/share graphic details (i.e., clips and images) via SNS, for example, visually disclosing the user’s values, attitudes, beliefs, lifestyle and interests.

Vociferous (Brazil, India) vs Taciturn (Russia, China)—the detail of lexical content (i.e., text) that a user will post/share via SNS, for example, verbally sharing the user’s values, attitudes, beliefs, lifestyle and interests.

High self-monitoring (Russia, China) vs Low self-monitoring (Brazil, India)—whether a user pays close attention to other users’ perceptions of them (high self-monitors), or if a user seems oblivious to how others see them (low self-monitors).

Unregulated usage (Brazil) vs Censorship mechanism (India, Russia, China)—the level of Internet governance in a country and the extent to which it constrains Internet freedom (e.g., use of VPN to circumnavigate) and free-speech.

In this framework, the sociomateriality of SNS consumption is multifaceted and context specific, in line with Parmiggiani and Mikalsen (2013). Furthermore, it is acknowledged that a user will modify their behaviour, depending on the nature of the information shared via SNS (i.e., personal, professional or corporate), and that this behaviour is shaped by digital materiality (Leonardi, 2010b; Morizio, 2014) and cultural dimensions (Hofstede, 2001).

Our findings confirm studies that underscore the importance of developing trusting relationships in collectivist cultures (Fuchs, 2015; Distefano et al., 2016). We show that SNS play a key role in nurturing and supporting trusting relationships, as well as in building new relationships with other users. To wield digital interactivity in the BRIC cultural context, individuals/businesses are advised to consider which SNS is best positioned for catering to the local tastes and language preferences of SNS users, as specified by Tamilmani et al. (2018). It is worth bearing in mind, however, that digital culture will change over time (Guy, 2019), in response to the co-evolution of technology, society and culture (Lichy and Racat, 2021).

Management implications

Based on the findings, we summarise a number of recommendations for individuals/businesses intending to implement or develop digital interactivity in BRIC markets. Borrowing from the vernacular of the participants, the recommendations are written in the form of digital “hacks” (i.e., advice), thus identifying hacks as a nascent feature of SNS user behaviour (Djafarova & Trofimenko, 2019). Table 9a addresses general hacks for managing content; Table 9b provides country-specific hacks.

The participants cited digital influencers as a source of interest/inspiration, yet acknowledged the notion of “fake it and make it—clickbait” (i.e., misleading online content that encourages users to click a link to an article, photo or clip). It suggests that users are aware of individuals who have fictitious followers and/or content that they use as “clickbait” (see Zannettou et al., 2019). This serves as a reminder to check the ratio of likes-to-followers as well as the number of likes per post of the influencer, as an indicator of credibility and authenticity.

Based on participant comments, Table 9b gives context-specific hacks for leveraging digital interactivity, which reflect how SNS user behaviour is shaped by both the local (collectivist) culture and digital culture (Makri et al., 2019; Guy, 2019) .

Individuals/managers must bear in mind that the notion of community is linked to the close-knit trusted relationships with family and friends (Pal, 2018), in which users interact and share information via SNS that cater to local tastes and language preferences (Tamilmani et al., 2018).

Limitations

The research acknowledges that BRICs are vast “mini continents” of diverse multicultural populations (Schwartz et al., 2010); the results of this study cannot be generalised to the whole population. Additional analysis and research in other collectivistic cultures (including Indonesia, Japan, Korea, Taiwan, Venezuela, Guatemala, Ecuador and Argentina) is needed for further exploring the sociomateriality of SNS usage. Also, there is scope for undertaking a longitudinal study to gain insights into the co-evolution of SNS user behaviour and emerging SNS, which may lead to a shift in current practices.

Conclusions

Echoing Jarzabkowski and Pinch (2013), there is a need to make sociomateriality an important and central agenda in management research specifically and social science research more generally, in order to understand how the assumptions and social obligations that surround them keep them working and, if need be, enable change. Our study contributes to the sociomateriality literature by examining how users harness SNS and mobile technologies, espoused by the BRIC collectivist cultural context in today’s digital environment. This is of paramount importance given that few scholarly studies have compared the sociomateriality of SNS usage in the BRIC context.

The findings provide a contemporary comparison of differences in the extent to which users interact and share information, how the cultural context and sociomaterial environment shape their consumption of SNS, and how they build digital identity within an “in-group” and with the wider online community. Beyond the ability and enthusiasm for using SNS, the users in our study show differences in the level of trust and engagement with other users, which can be explained by the context.

As local SNS are often used alongside global platforms (within the constraints of state control), individuals/businesses are advised to proceed with caution when entering BRIC markets, and to pay attention to identifying the country-specific characteristics of SNS user behaviour and digital interactivity.

BRICs & clicks: Insights into the sociomateriality of consuming social networking sitesBRICs & clics : un aperçu de la sociomatérialité de la consommation des réseaux sociauxBRICs & clicks: perspectivas sobre la sociomaterialidad del consumo de las redes sociales

Abstract

Résumé

Resumen

Literature review