Investigating culture and communication in digital spaces is challenging due to their dynamic, unbounded, and superdiverse nature (Solmaz, 2020). Of the 85 empirical studies we collected, 11 (13%) addressed this superdiversity directly, investigating diverse user populations in digital spaces. Studies of Western populations continued to dominate, with 20 (24%) focussing on Anglo-North American users (2 countries), and 31 (36) examining users from Europe (16 countries). However, we observe an increasing number of studies considering digital user populations beyond the West, including 5 (6%) from Latin America (five countries), 13 (15%) from East Asia (four countries), 7 (8%) from Southeast Asia (four countries), 4 (5%) from the Middle East (three countries), 3 (4%) from Africa, 2 (2%) from South Asia,  and 1 (1%) each from Central Asia and Australia. (Note that the total number of populations reported exceeds 85, because some studies explicitly examined or compared users from more than one global location.)

Studies of this kind therefore often make use of a wide range of methods and methodologies, reflecting the complex and dynamic nature of online interactions. We classified 85 (52%) of the works included in the current collection as ‘empirical’. Table 1 indicates the array of methods employed in these qualitative, quantitative, and mixed methods studies.

Table 1. Summary of research methods employed in this collection

 i.      Qualitative studies

Several papers in this collection offer reviews of literature in different areas of this field of study. Abdelnour-Nocera and Densmore (2017), Avgousti (2018), Banerjee and Firtell (2017a), Chun (2017), Heggernes (2021), Uzuner (2009), Shadiev and Sintawati (2020), Thorne et al. (2015), and Young and Asino (2020) variously summarize arrays of largely qualitative and descriptive studies that have been employed by others to investigate aspects of communication and culture in digital spaces. Such qualitative studies focus on in-depth understanding and typically involve non-numerical data.

Like these reviewers, we also found that a majority of studies in our corpus are qualitative in approach. Many have taken the form of case studies (Black, 2006; Cohen & Bekerman, 2022; Dubreil, 2012; Ersoy & Kumtepe, 2021; Han, 2017; Lam, 2009; Lynch, 2022; Misra, 2022; Prieto-Arranz et al., 2013; Rendell, 2021; Ribeiro, 2016; Shadiev & Sintawati, 2020; Shih, 2013; Stratton, 2019; Winschiers-Theophilus et al., 2022; Winschiers-Theophilus et al., 2019) and other kinds of observational study (Jiménez & Kressner, 2021; Koutsogiannis, 2015; Žuvela-Bušnja et al., 2008). Ethnographic studies are also common (Baker & Sangiamchit, 2019; Black, 2009; Domingo, 2012, 2014; Hepp et al., 2012; Kim, 2016; Koutsogiannis, 2015; Shrodes, 2021; Wagner, 2019). Many investigators employed interviews with users to gather insights (Ersoy & Kumtepe, 2021; Jurkova & Guo, 2021; Kim et al., 2009; Koutsogiannis, 2015; Kumi-Yeboah et al., 2022; Lim & Pham, 2016; Lynch, 2022; Pathak-Shelat & Bhatia, 2019; Sandel, 2014; Seto & Martin, 2019; Shadiev & Sintawati, 2020; Solmaz, 2020; Sung, 2014; Yau et al., 2019); focus groups or group interviews were also used (Cornillie et al., 2021; Ju et al., 2021; Lim & Pham, 2016; Park & Wen, 2016; Rohn, 2013)

Some investigators analyzed transcripts or associated discourses of user interactions in virtual spaces (often with the goal of analyzing communicative effectiveness or investigating sociocultural competence). Analytic methods employed include discourse analysis (Baker & Sangiamchit, 2019; Hepp et al., 2012; Koutsogiannis, 2015; Liebermann, 2021; Liu & You, 2019; Sandel et al., 2019) or content analysis (Brantner & Herczeg, 2013; Fabrício, 2014; Frost, 2013; Funes & Mackness, 2018; Halstead, 2021; Jeon, 2021; Kumi-Yeboah et al., 2022; Perumal et al., 2021; Rutten, 2014; Shadiev & Huang, 2016; Yadlin-Segal, 2017; Žuvela-Bušnja et al., 2008).

Other qualitative methods reported include action research (Glimäng, 2022; Koponen, 2020), design-based research (Eutsler & Perez, 2022; Hull & Stornaiuolo, 2014), analytical play (Blume, 2021), design research (Hull et al., 2013), mediagraphy (Schofield & Carvajal, 2022), narrative research (Mertala, 2020; Toscano, 2011), participatory research (Winschiers-Theophilus et al., 2021), phenomenology (Magro, 2019), use of vignettes (Aldridge et al., 2014), story exchanges (Sánchez & Ensor, 2021) and story-telling (Hull et al., 2021). Several studies deliberately employed several complementary qualitative methods (Brownell & Wargo, 2017; Kumi-Yeboah et al., 2022; Lindner & Méndez Garcia, 2014)

ii.      Quantitative studies

These involve numerical data and statistical analysis, and are much less common, both in our own corpus and in reviews completed by others. Avgousti (2018) uncovered only a single quantitative study, for example. Similarly, we only identified one true experimental study in our corpus (Zhong & Newhagen, 2009) and one quasi-experimental study (Roche & Todorova, 2010).

In our collection, some studies did make use of surveys as data collection instruments (Godler & Reich, 2017; Grieve et al., 2022; Hepp et al., 2012; Hu et al., 2017; Koutsogiannis, 2015; Lai, 2019; Ochs, 2017; Rudnev et al., 2018). A few studies made use of questionnaires (Ju et al., 2021; Roche & Todorova, 2010; Shadiev & Huang, 2016). Two studies report on statistical analysis of large sets of survey data (Godler & Reich, 2017; Rudnev et al., 2018). A final quantitative study (Goodfellow & Hewling, 2005) also offered some early cross-over with the field of learning analytics, offering some simple comparative analysis of participation patterns in two different online courses.

iii.      Mixed methods studies

These combine both qualitative and quantitative approaches for data collection and analysis. Several authors of literature reviews included in our corpus note that a significant number of studies they reviewed had adopted mixed methods, often incorporating qualitative data collection like interviews or questionnaires (Avgousti, 2018; Shadiev & Sintawati, 2020; Uzuner, 2009).

In our collection, only eight studies (5%) appear to deliberately take a mixed methods approach. Of these, only two make use of comprehensively designed mixed methods: Hauck (2019) combined task design with questionnaire data. Hull and Stornaiuolo (2014) combined online participation analytics with ethnography. The ‘principled mixed methodological design’ employed by Sydorenko et al. (2021)is described as a discourse analysis approach whose output is then analyzed quantitatively. Roche and Todorova (2010) include quantitative data in their study in the form of learner grades (and analysis of these). The remaining four studies include survey data as the quantitative element of their work, combined with a selection of qualitative approaches. We might be wise, however, to heed Uzuner’s 2009 caution that while a number of studies employ a survey methodology, some fail to follow rigorous survey research design; data drawn from survey-informed studies might best be approached with care.

Overall, methods employed in the studies included in our collection lean heavily towards qualitative, descriptive, and interpretive approaches, often grounded in sociolinguistic and sociocultural theories, to explore the complex interplay of culture, identity, and communication in diverse digital environments. How we theorize and measure digital culture determines what we can see, compare, and legitimately claim–so studies should make those choices explicit and align methods to them.