Research Article

Research Methodologies in Sport Management

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1. Introduction

All papers considered in this section of the SMD are from published issues of the pre-selected journals. Table 1 provides a summary of the methodological approaches used across each journal for this time period.

Table 1: Summary of the Methodological Approaches

Journals Mixed Qualitative Quantitative Total
Communication & Sport 1 16 3 20
Communication & Sport - Invited Article 1 2   3
European Sport Management Quarterly 2 6 7 15
International Journal of Sport Finance     8 8
International Journal of Sport Marketing and Sponsorship 1 9 12 22
International Journal of Sport Communication   4 8 12
International Journal of Sport Communication (1 Critical Commentary and 3 Case Studies)       4
International Journal of Sport Policy and Politics 1 12 4 17
International Journal of Sport Policy and Politics – 2 Critical Commentary       2
Journal of Global Sport Management   6 3 9
Journal of Sport Economics     25 25
Journal of Sport Management 2 8 10 20
Sport Management Review   17 8 25
Overall Total 8 80 88 182

Over this period numerous research designs, data collection, and analysis techniques have been employed successfully to provide new insights into areas of research. Table 2 captures the variety of research designs and analytic approaches used.

Table 2: Quantitative and Qualitative Designs and Approaches Employed

Quantitative Approaches Qualitative Approaches
Simultaneous Equation Approach Interviews
Regression Analysis (various forms) Case Study
Independent t-test Conceptual Review
Conjoint Analysis Field Work
Chi-Square Test Thematic Analysis
Quantitative Content Analysis Focus Groups
Experimental Design Observations
Linear Modelling Ethnography
Factor Analysis Qualitative Content Analysis
Structural Equation Modelling Discourse Analysis
Survey Narrative
Panel Modelling Conceptual Framing

From these journals, three papers have been selected for a more detailed review. The papers selected were chosen as they used social media as a research platform. The decision to focus on social media papers was made as never before has such a rich vein of potential data been available to sport management researchers. Social media presents researchers with a tool to provide deeper insights into the influence and impact that sport can provide, however, it does present challenges. Therefore to begin, a short critique of social media as a research method will be presented.

2. Social Media as a Research Method Critique

There is no doubt that for sport management scholars the research potential within social media is commensurate with its volume, cultural status and popularity. It has been described as ‘natural’ (Bail, 2017) in that it records not only the time-relevant and event-specific posts by individual users or sport organisations, but also their interactions with fans and brands. Such data provide a rich and textured repository of narratives, which are typically unavailable, or difficult to access via traditional research methods. In addition, researchers can take advantage of how users can communicate asynchronously (uploading a video of a past sport experience) or synchronously (live streaming of a sport experience) (Baym, 2015) to comment on sporting events. Social media data does not suffer from poor memory or reflective filtering of respondents after the event has occurred, which may arise in some methods. Rather, social media captures opinions, emotions and attitudes at the very moment of impact, providing a digital footprint and data set for researchers to utilise. Moreover, by reviewing a longitudinal series of social media content, it is possible to create an understanding of how ideas and views have formed, transmitted, and vanished over time (Robards, & Lincoln, 2017).

The term ‘social media’ has been employed to capture the presence of multiple social internet platforms incorporating blogs, social networking sites, and user generated content sharing sites (Fuchs, 2017). This means that communication is conversational in nature involving not just the expression of views, but their exchange through interaction. It is also worth keeping in mind that although most users are individuals, groups and organisations can post content too, as representatives of larger entities.

The unprecedented success and growth of social media emanates from its remarkable and unique ability to connect people in ways that would never be possible through conventional, analogue communication (Boyd, 2010). Unlike almost every other social contact, which tend to pass by unrecorded, social media leaves a trace, with conversations often labelled according to audience and content (Hoskins, 2009; Robards, & Lincoln, 2017). Studying and identifying a population online can be challenging. Ensuring validity and reliability can be demanding. Social media users themselves present an obstacle to validity and reliability because from a sampling viewpoint they tend not to be representative of populations.

Making generalisations from the sample to the population can therefore be problematic, due to bias. Data volume and volatility makes social media validity and reliability trickier due to the sheer volume and the swift changeability of the content. User content authenticity can prove troublesome to validity and reliability because it cannot be assumed that user behaviour on social media mirrors their behaviour in the material world. Emotive and deliberately controversial language and images are commonplace in social media, a side-effect of users trying to cut through the volume of posts and attract attention. Exaggeration and over-statement can therefore bias results and a researcher cannot necessarily be confident that a user’s report of their opinions and intentions are authentic. Social media content private ownership can influence validity and reliability, as some social media content is not shared publicly, again meaning that what is available will reflect a bias towards those users who want their opinions heard. Another problem is that some social media companies do not transparently release information about their platforms content, as they make decisions about their rules, functionality and policies based on commercial imperatives, such as the presence of advertisements and click-throughs.

Issues of privacy and ethics have also not been as fully reconciled for social media methods as they have for its traditional, analogue counterpart. Hall et al. (2016) pointed out from a legal standpoint that while developing, the issue is complicated by international legal boundaries. Sport management researchers face the problem of securing informed consent from participants. This may be impossible given the number of social media users and the challenges of contacting all of them. It may be argued that users are theoretically aware when they create social media content that it may be made public and used for other purposes. Page et al., (2014) warned that social media research may harm participants in forms that are not immediately tangible but are nonetheless significant (Corbett & Edwards, 2018). While this list is not exhaustive it does provide some initial insight into the challenges of social media research.

There is also an urgent need for critical reflection within sport management on the epistemological implications of social media research, which despite attracting the attention of scholars intrigued by its potential, currently lacks veracity as a research domain. Such consideration is relevant given that social media is transforming research methods through the availability of a detailed and vast suite of largely uncensored, accessible data generated through a public social process (Quinton, & Reynolds, 2018). In the sport management research context, Abeza, O’Reilly, Seguin and Nzindukiyimana (2015), and Filo, Lock and Karg (2015), undertook reviews examining social media scholarship. Although they utilised different approaches, both concluded that around 50% of the articles reviewed did not outline or apply a theoretical or conceptual framework, whilst the remaining work heavily utilised uses and gratifications theory (Ruggiero, 2000) and relationship marketing theory (Möller, & Halinen, 2000). However, if social media is to receive acknowledgement as a viable data domain, researchers need to provide transparent epistemological justifications.

Reflecting on the emergence, perception and employment of the new social media paradigm in sport management, it is instructive to review the nature of its ontological underpinnings. To begin with, the application of different paradigms suggests that there is no single, accepted way of carrying out research (Skinner, Edwards & Smith, 2020). How researchers proceed depends upon numerous factors, including how one sees the world and the nature of one’s reality (ontology), the relationship between the inquirer and knowledge (epistemology), and what techniques can be used to measure the perceived reality (methodology). Further, a paradigm is a set of propositions that explain how the world is perceived, and a way of breaking down the complexity of the real world, telling researchers what is important, what is legitimate, and what is reasonable (Sarantakos, 2002). Yet, the fluid and chaotic nature of the social media world encourages a continually shifting definition of ‘what is important?’. Guba (1990) suggested:

there are many paradigms that we use in guiding our actions: the adversarial paradigm that guides the legal system, the judgmental paradigm that guides the selection of Olympic winners, the religious paradigms that guide spiritual and moral life [and] those that guide disciplined inquiry.(p.18)

Yet, how the social media paradigm guides our understanding of the sport management world has not been fully explored.

Quinton and Reynolds (2018) proposed that digital research should not be restricted to specific ontological or epistemological perspectives, whilst others have advocated for specific approaches like Wittgenstein’s ordinary language philosophy (Brooker, Dutton, & Greiffenahgen, 2017), or a critical digital and social media perspective drawing from the work of Marx (Fuchs, 2017). Social media data cannot be examined in isolation, as it has been shaped and influenced by broader, social, cultural and political contexts that need to be considered (a point noted in the review paper 3 of this section). For social media research to be considered and accepted as a sport management research domain there needs to be greater clarity, consideration and justification by sport management researchers using social media data surrounding the epistemological stance guiding their research.

One argument maintains that critical epistemologies are particularly well suited to underpinning social media analysis because it “is based on real world phenomena and linked with societal ideology” (Scotland, 2012, p.13). For example, the ‘digital divide’ and the social inequalities that arise from internet access and technological infrastructures have proved to be popular domains for critical lenses (Wessels, 2013). Social media’s ubiquity has also raised concerns around the way its discourse produces and disseminates inequalities, and unequal representation of certain populations that do not align with societal norms or cultures (Boyd, 2010); all salient questions to sport and its management, especially given the complexity of the digital divide (Radovanovic, 2011).

Fuchs (2008) observed that the internet, and in turn related social media platforms, are techno-social systems that are produced, utilised, adapted and shared through the activities and networks of human actors. In this sense an actor’s discursive knowledge regarding social reality has a construction effect on the outcomes of social media interrelations. As such they are both enabled and inhibited by technological infrastructure, which means that “social media [platforms] are tools for exerting power, domination, and counter-power” (Allmer, 2014, p.40). Social media research therefore allows for the investigation of deeper, underlying structures and beliefs critical to the construction, interaction and engagement of and with the data (either text, images, networks, interactions) produced on social media platforms (Marwick, 2013).

The remainder of this article will focus on three papers that utilised social media as a research tool. The papers have been chosen as the above commentary is captured in their methodological design.

3. Social Media Papers

Paper 1 by Andrea Geurin and Erin McNary was published in the European Sport Management Quarterly 21(1). The paper entitled ‘An examination of Rule 40 and athletes’ social media use during the 2016 Rio Olympic Games’. Ambush marketing was used as a framework to examine athletes’ adherence to Rule 40. Under Rule 40 athletes are restricted from posting any content on social media featuring a non-official Olympic sponsor from a time period of nine days before the Opening Ceremony until three days after the Closing Ceremony. Therefore, athletes who have personal sponsors that are not official sponsors of the Olympic Games cannot use social media as a platform by which to promote or thank their personal sponsors during the so-called ‘blackout period’. Methodologically, the study used a quantitative content analytic method to examine the Instagram posts made by 100 randomly selected US Olympians one week prior to the blackout period, during the blackout period, and one week after the blackout period from the 2016 Rio Olympics. This represented a six- week time period of data collection.

Instagram was chosen as the social media platform for analysis due to its blend of visual content (photographs and videos) with written content (captions for photos or videos). It was argued that the use of visual content provided athletes with a greater platform by which to showcase their personal sponsors, as it did not require athletes to list sponsors by name, as is the case with solely written content. The use of this platform reflects the surge in platforms such as Instagram bringing a major research opportunity to access rich, visual data at the same time as instigating a methodological conundrum (Hutchinson, 2016). Instagram’s remarkable, exponential growth as a mobile application wherein users upload images and video footage taken on their phones, influenced these researchers to apply robust methods when drawing on visual and textual material to systematically categorized and record the data for analysis.

The research followed an accepted process for quantitative content analysis. To begin it selected the content that would be analysed. Based on the research questions the researchers choose the content to be analysed, defined the units and categories of analysis and developed a set of rules for coding – adding to the robustness of the design. They then coded the content according to the rules and quantitatively analysed the data through frequencies, chi square, and independent samples t-tests to draw conclusions.

The development of a validated codebook for quantitatively analysing Instagram photos is a particular methodological strength of this paper. The codebook was used to capture athletes’ self-presentation on Instagram allowing the captions of each photo to be analysed to determine whether any ‘prohibited’ words or phrases were used during the blackout period. The second strength the attention given to intercoder reliability. Two coders coded the sample. To begin each researcher coded 20% of the total sample independently of each other. Intercoder reliability was first calculated using percent agreement. Next, to test for chance agreement, kappa figures were calculated to determine if the threshold to continue with a content analysis study was met. Acceptable reliability figures were achieved and the researchers proceeded with the study by dividing the remaining 80 athletes’ Instagram accounts equally between the two coders and these were coded independently. This robustness of analysis is commendable as visual data can create complications for researchers as images are inevitably open to a level of subjective interpretation, so scholars, as in this case, need to be accountable and find a consistent way of coding.

Paper 2 was published in a Special Issue of European Sport Management Quarterly 21(3). The paper was authored by Daniel Weimar, Lisa Carola Holthoff and Rui Biscaia. It was entitled: ‘A bright spot for a small league: Social media performance in a football league without a COVID-19 lockdown’. The authors used daily follower statistics (Facebook, Twitter, Instagram, Youtube) three months before. during, and three months after the lockdown. By employing social media follower statistics of the Belarus clubs and well as those participating in 48 first divisions under shutdown, as a proxy for league interest from fans, Weimar et al estimated the effects of the COVID impact.

What is methodologically innovative about this paper is their use of cross-platform analysis (Facebook, Twitter, Instagram, Youtube). Sport management social media research is only just emerging in popularity as a productive method. As a result, researchers have not yet fully explored its methodological opportunities, particularly as new social media platforms and modalities are exploding into the mainstream more quickly than their research implications can be fully grasped. Amidst this inevitable clutter and learning on the job, one area of immense possibility for sport management researchers lies in conducting cross-platform studies; that is, research that collects data from numerous social media platforms at the same time. This research took up this challenge.

A first advantage of cross-platform analysis is that it can add tremendous richness and diversity to the data set. For example, different platforms attract different users, so the combination can immediate enhance the demographic and profile heterogeneity (dissimilarity) of samples. Added to this, a second advantage is that the same issue, topic or question can be addressed within different platforms, offering the researcher with different angles to investigate. Third, cross-platform analysis can also mean that different kinds and forms of data concerning the research question can be gathered, such as lengthy textual conversations, images, and short summaries. Fourth, cross-platform analysis exposes how the content and character of social media data can be platform specific, in line with the structures and modes each one allows and encourages (Burgess & Matamoros-Fernández, 2016). As such, sport management researchers can discover how each platform itself channels certain forms of responses.

A key implication is that researchers must remain mindful of the effects of each platform’s medium, including its architecture, displays, data types, policies, rules, hashtags and labels, advertising, and moderation or censorship (Pearce et al., 2018). Researchers should be naturally attuned to such contextual variables anyway, but social media tends to amplify the effect. Furthermore, researchers need to be aware of how each platform presents it data, including the prioritisation of content based on certain metrics such as likes, retweets, followers, friends, and upvotes (Rogers, 2017); all of which can potentially influence the perceptions and responses of subsequent users. The authors of this study have been mindful of these implications, and as such, their analysis of the Belarusian football fan experience has been enriched through a cross platform examination.

The third paper is taken from Communication and Sport, 9(1) It is authored by Grace Yan, Ann Pegoraro and Nicholas Watanabe and is entitled: “Examining Internet Research Agency (IRA) Bots in the NFL Anthem Protest: Political Agendas and Practices of Digital Gatekeeping’. The research examined the gatekeeping practices of IRA bots based on data released from the Social Media Listening Centre (SMLC) at Clemson University. In so doing, it aimed to enrich the discussions of digital gatekeeping in sport by illuminating new temporality, agents, and agenda on sport networks. The analysis approached bots’ gatekeeping activities from three perspectives: the overall behavioural patterns, the discourses and underpinning ideologies, and communicative tactics to sustain attention on Twitter.

This data set was composed of 2,973,371 tweets from 2,848 bot accounts, which were verified by Twitter as being associated with IRA. The data were first downloaded in the form of 11 CSV files and then imported into the R-3.6.0 statistical software package and merged to one complete file. In order to locate protest-related tweets within the data set, a search routine was developed in the R statistical software through the use of a series of keywords. Overall, 152 key words were developed to assist the search. In the next stage, the authors read through the 24,831 tweets to filter out those messages that were unrelated to the NFL anthem protest, resulting in the removal of 17,865 tweets and a final data set of 6,923 tweets. IRA bots were placed into five groups: right troll, left troll, newsfeed, hashtag gamer, and fearmonger. Using Linvill and Warren’s (2018) identification the authors verified the classification of bots in the context of NFL athlete protest.

Three interrelated analyses were conducted to comprehensively examine the IRA bots’ gatekeeping activities and agendas. To address the first research question concerned with the overall pattern of bots’ emergence, the time trend of bots’ activities in relation to political dynamics was examined. Considering the second research question, critical discourse analysis (CDA) was employed to examine the tweets produced by IRA bots. The analysis from research question 2 provided the basis for addressing the third question and understanding that social media users were increasingly exposed to information quantity and quick turnover. The authors therefore considered it critical to examine specific communicative strategies used by the bots to sustain the public attention on Twitter. This was done by examining the rhetorical style, the political context employed in composing tweets, as well as the utilization of networked connectivity surrounding the production of the tweets.

What is noteworthy methodologically in this paper is the use of CDA. This is because social media has converted the usually hidden opinions and interactions between individuals and groups into publicly available, searchable and downloadable data (Felt, 2016). Moreover, the data represents not only content from a networked sport community but also a barometer of current social discourses (Papacharissi, 2014). In this sense, this research was centred around questions concerning the nature and behaviour of people participating in social media sport networks (Sloan & Quan-Haase, 2017). This suggests sport management research can pertain to social media as a social instrument in its own right. For example, hundreds of millions of sports activists can congregate and communicate through social media, transgressing geography and background. Exactly what effect social media has had on influencing the sport agenda remains uncertain, and the investigation of social media as a cultural institution should sit at the top of the list of significant under-explored topics in sport management. This was a point noted by the authors who highlight an important characteristic of CDA is that all discourses can only be understood by reference to their cultural context. Moreover they note that the critical discourse analyst should consider the historical, sociocultural, spatial and institutional context within which the discourse was assembled, legitimized and disseminated.

At the contextual level, the researchers embraced a constructionist approach by seeking to link tweets’ content in relation to larger social contexts of power. To do so, they sought to critically disembed the ideological underpinnings of the tweets by considering the polarized beliefs and forces surrounding the wider political environment. This approach acknowledges that for the critical discourse analyst language is not viewed as powerful in and of itself, but is given power as a result of how it is used, who uses it and the context within which this usage takes place (Wodak, 2001). As shown in this paper, discourses do not merely reflect social practices, but are integral to the constitution of power through these practices in order to achieve certain ends (Jager 2001). Crucial to this research was an understanding that language is not analysed out of context, but is situated within the specific context of social practices of which it is a part (Fairclough, 2001).

4. Conclusion

While the breadth of methodological approaches used over this period is impressive this article has paid particular attention to three social media research designs that have advanced knowledge within the field of sport management. It has been noted that social media platforms can provide insights into controversial issues and provide valuable information about how sport can shape and influence opinions, attitudes, experiences, consumption behaviours, preferences, desires, and frustrations. Despite the new epistemological concerns surrounding social media research about the production of knowledge this article has shown how sport management researchers are embracing social media as a research tool. The following section provides an annotated bibliography of additional social media papers.

5. Annotated Bibliography

Utz, S., Otto, F., & Pawlowski, T. (2020). “Germany Crashes Out of World Cup”: A Mixed-Method Study on the Effects of Crisis Communication on Facebook. Journal of Sport Management, 35(1), 44-54.
The researchers at University of Tübingen investigated the effects of crisis communication on Facebook during the 2018 FIFA World Cup. In particular, the Facebook posts of the German team, captain Manuel Neuer and team member Thomas Müller, are examined based on the emoji reactions each received. In addition, the researchers used data from a two-wave panel study among a representative sample of adult German Internet users conducted before and after the FIFA World Cup to assess changes in evaluation and para-social relationships and perceived authenticity as potential mediators. Their findings suggest that the sender of a crisis communication matters: the posts by Neuer and Müller received fewer angry reactions than the posts from the team account and only the team was evaluated more negatively after the World Cup than before. The authors also demonstrate that para-social relationships mediate the effect of exposure to social media posts when using social media as a communication channel.

Gong, H., Watanabe, N. M., Soebbing, B. P., Brown, M. T., & Nagel, M. S. (2021). Do consumer perceptions of tanking impact attendance at National Basketball Association games? A sentiment analysis approach. Journal of Sport Management, 35(3), 254-265.
The authors, researchers at Rice University, University of South Carolina, University of Alberta, and the University of South Carolina used sentiment analysis to examine the impact of consumers’ sentiment regarding tanking on game attendance in the National Basketball Association. To examine the effect of consumer perception of tanking on NBA attendance the study analysed NBA game attendance between the 2013–2014 and 2017–2018 seasons. Based on the data, the authors created an algorithm to measure the volume and sentiment of consumer discussions related to tanking which demonstrated that the volume of discussions for the home team and sentiment toward tanking by the away team impacted on game attendance.

Weimar, D., Soebbing, B. P., & Wicker, P. (2021). Dealing with statistical significance in big data: The social media value of game outcomes in professional football. Journal of Sport Management, 35(3), 266-277.
The researchers, affiliated with University of Duisburg-Essen, University of Alberta, and Bielefeld University, examined the effect of game outcomes on the change rate of social media followers from three popular social media platforms: Facebook, Twitter, and Instagram. Using social media data, the authors assess ED the relative impact of determinants using dominance analysis. Data of 644 first division football clubs from Facebook (n = 297,042), Twitter (n = 292,186), and Instagram (n = 312,710) over a 19-month period were included in the research and the findings indicated that a victory yielded the highest increase in followers. The research also highlighted opportunities to develop fan engagement, increase the number of followers, and enter new markets

Eddy, T., Cork, B. C., Lebel, K., & Hickey, E. H. (2021). Examining Engagement with Sport Sponsor Activations on Twitter. International Journal of Sport Communication, 14(1), 79-108.
The authors, researchers at University of Windsor, Western Michigan University, Ryerson University, and the University of Arkansas investigated differences in follower engagement with regard to sponsored Twitter posts from North American professional sport organisations. The research is centred around the focus, scope, and activation type of the sponsored messages. The research consists of two related studies: Study 1 employed a deductive content analysis, followed by negative binomial regression modelling in order to examine differences in engagement between message structures defined by focus and scope. Study 2 applied an inductive content analysis approach to investigate differences in engagement between different types of activations. The authors found that in general, more passive forms of sponsor integration in social media messages drive engagement among followers.

Schäfer, M., & Vögele, C. (2021). Content Analysis as a Research Method: A Content Analysis of Content Analyses in Sport Communication. International Journal of Sport Communication, 14(2), 195-211.
The researchers, affiliated with Johannes Gutenberg University and University of Hohenheim, conducted a quantitative content analysis of scholarly journal articles, focusing on three major international sport communication journals between 2010 and 2019 (N = 267). The aim was to demonstrate to what extent and in which contexts content analysis as a research method is applied. Their findings indicate that qualitative and quantitative methods are used equally while combinations with other methods are comparatively rare. It was further concluded that the studies cover a broad portfolio of different topics and that social media as a communication channel have become an increasingly central issue of scientific exploration.

6. References

Abeza, G., O’Reilly, N., Séguin, B., & Nzindukiyimana, O. (2015). Social media scholarship in sport management research: A critical review. Journal of Sport Management, 29(6), 601-618. DOI: 10.1123/JSM.2014-0296

Allmer, T. (2014). (Dis) Like Facebook? Dialectical and Critical Perspectives on Social Media. Javnost - The Public, 21(2), 39-55. DOI: 10.1080/13183222.2014.11009144

Bail, C. A. (2017). Taming big data: Using app technology to study organizational behavior on social media. Sociological Methods & Research, 46(2), 189-217. DOI: 10.1177/0049124115587825

Baym, N. (2015). Personal Connections in the Digital Age (2nd Ed.) Cambridge, UK: Polity.

Boyd, D. (2010). Social Network Sites as Networked Publics: Affordances, Dynamics, and Implications. In Paparcharissi, Z., (Ed.) Networked Self: Identity, Community, and Culture on Social Network Sites, (pp. 39-58). New York: Routledge.

Brooker, P., Dutton, W., & Greiffenhagen, C. (2017). What would Wittgenstein say about social media? Qualitative Research, 17(6), 610-626. DOI: 10.1177/1468794117713058

Burgess, J., & Matamoros-Fernández, A. (2016). Mapping sociocultural controversies across digital media platforms: One week of #gamergate on Twitter, YouTube, and Tumblr. Communication Research and Practice, 2(1), 79–96.

Corbett, B., & Edwards, A. (2018) A case study of Twitter as a research tool, Sport in Society, 21(2), 394-412. DOI: 10.1080/17430437.2017.1342622

Fairclough N. 2001. Language and power. London: Longman.

Felt, M. (2016). Social media and the social sciences: How researchers employ Big Data analytics. Big Data & Society, 3(1), 1-15. DOI: 10.1177/2167479515584045

Filo, K., Lock, D., & Karg, A. (2015). Sport and social media research: A review. Sport management review, 18(2), 166-181. DOI: 10.1016/j.smr.2014.11.001

Fuchs, C. (2008) Internet and Society: Social Theory in the Information Age. New York: Routledge.

Fuchs, C. (2017). From digital positivism and administrative big data analytics towards critical digital and social media research! European Journal of Communication, 32(1), 37-49. DOI: 10.1177/0267323116682804

Guba, E. G. (Ed.) (1990). The paradigm dialog. Newbury Park, CA: Sage Publications.

Hall, M., Mazarakis, A., Peters, I., Chorley, M., Caton, S., Mai, J. E., & Strohmaier, M. (2016). Following user pathways: Cross platform and mixed methods analysis in social media studies. In Proceedings of the 2016 CHI conference extended abstracts on human factors in computing systems (pp. 3400-3407). ACM.

Hoskins A. (2009). The Mediatisation of Memory. In: Garde-Hansen, J., Hoskins, A., & Reading, A. (Eds.) Save As … Digital Memories (pp. 27-43). Palgrave Macmillan: London.

(pp.1-23). London: Sage.

Hutchinson, J. (2016). An introduction to digital media research methods: how to research and the implications of new media data. Communication Research and Practice, 2(1), 1-6. DOI: 10.1080/22041451.2016.1155307

Jager, S. (2001). Discourse and knowledge: Theoretical and methodological aspects of a critical discourse and dispostitive analysis. In R. Wodak & M. Meyer (Eds), Methods of critical discourse action, pp. 32–62. London: Sage Publications.

Linvill, D., & Warren, P. (2018). Troll factories: The Internet Research Agency and state-

sponsored agenda building (Working paper). Retrieved from


Marwick, A. (2013b). Ethnographic and qualitative research on Twitter. In Weller, K., Bruns, A., Puschmann, C., Burgess, J. & Mahrt, M. (Eds.), Twitter and Society (pp.109-122). New York: Peter Lang.

Möller, K., & Halinen, A. (2000). Relationship marketing theory: its roots and direction. Journal of Marketing Management, 16(1-3), 29-54. DOI: 10.1362/026725700785100460

Page, R., Barton, D., Unger, J. W., & Zappavigna, M. (2014). Researching Language and Social Media: A Student Guide. New York, NY: Routledge.

Papacharissi, Z (2014). Affective publics: Sentiment, technology, and politics. In: Papacharissi, Z. (Ed.) Affective Publics: Sentiment, Technology, and Politics (pp. 64–94). Toronto, ON: Oxford University Press.

Pearce, W., Özkula, S. M., Greene, A. K., Teeling, L., Bansard, J. S., Omena, J. J., & Rabello, E. T. (2018). Visual cross-platform analysis: digital methods to research social media images. Information, Communication & Society, 1-20. DOI: 10.1080/1369118X.2018.1486871

Quinton, S., & Reynolds, N. (2018). Understanding research in the digital age. London: Sage.

Radovanovic, D. (2011, December 14). Digital divide and social media: Connectivity doesn't end the digital divide, skills do. Scientific American. Retrieved from:

Robards, B. & Lincoln, S. (2017). Uncovering longitudinal life narratives: scrolling back on Facebook. Qualitative Research, 17(6), 715-730. DOI: 10.1177/1468794117700707

Rogers, R. (2017). Digital methods for cross-platform analysis. In J. Burgess, A. Marwick, & T. Poell (Eds.), The SAGE Handbook of Social Media (pp. 91–110). London: Sage.

Ruggiero, T. E. (2000). Uses and gratifications theory in the 21st century. Mass Communication & Society, 3(1), 3-37. DOI: 10.1207/S15327825MCS0301_02

Sarantakos, S. (2002). Beyond domestic patriarchy: marital power in Australia. Nuance, 4, 12–34.

Scotland, J. (2012). Exploring the philosophical underpinnings of research: Relating ontology and epistemology to the methodology and methods of the scientific, interpretive, and critical research paradigms. English Language Teaching, 5(9), 9-16. DOI:10.5539/elt.v5n9p9

Skinner, J., Edwards, A, & Smith A.C.T (2020) Qualitative Research in Sport Management (2nd edition). Routledge; United Kingdom.

Sloan, L., & Quan-Haase, A. (Eds.). (2017). The handbook of social media research methods. London, England: Sage.

Wodak, R. (2001). The discourse-historical approach. In R. Wodak, & M. Meyer (Eds.), Methods of Critical Discourse Analysis, pp. 63–95. London: Sage Publications.

Wessels, B., (2013). The reproduction and reconfiguration of inequality: Differentiation and class, status and power in the dynamics of digital divides (pp. 37-48). In Ragnedda, M. & Muschert G. (Eds). The Digital Divide: The internet and social inequality in international perspective. New York: Routledge.