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To outline the current trajectories in digital social research and to highlight the roles of qualitative research in those trajectories.

A secondary analysis of the primary literature.

Qualitative research has shifted over time in relation to rapidly changing digital phenomena, but arguably finds itself in ‘crisis’ when faced with algorithms and ubiquitous digital data. However, there are many highly significant qualitative approaches that are being pursued and have the potential to contextualize, situate and critique narratives and practices of data.

To situate current debates around methods within longer trajectories of digital social research, recognizing their conceptual, disciplinary and empirical commitments.

This chapter critically evaluates the literature on digital consumer data and the ways in which it can be used in digital social research. The chapter illuminates how researchers have to conceptualise and negotiate digital data, focusing upon ethical and procedural challenges of employing digital methods.

The chapter draws upon and integrates a broad research literature from sociology, digital media studies, business and marketing, as these have opened up new directions for research design and method. It advocates interdisciplinary approaches to conceptualising what digital data is employing the concept of ‘marketing narratives’ to understand how the new visibilities of consumer data are shaped by related processes of branding and the interactivity of content.

The chapter shows how the capacities of digital technologies present significant challenges for researchers and organisations that have to be carefully negotiated if the potentials of digital consumer data are to be harnessed. In addition, researchers should pay attention to novel issues of ethical responsibility in the context of the longer-term presence of data records.

The chapter offers a set of guidelines for digital social researchers in negotiating the meanings of visible digital consumer data, the ethical and proprietary issues involved in utilising digital methods.

Digital humanities aim to use a digital-based revolutionary new way to carry out enhanced forms of humanities research more effectively and efficiently. This study develops a character social network relationship map tool (CSNRMT) that can semi-automatically assist digital humanists through human-computer interaction to more efficiently and accurately explore the character social network relationships from Chinese ancient texts for useful research findings.

With a counterbalanced design, semi-structured in-depth interview, and lag sequential analysis, a total of 21 research subjects participated in an experiment to examine the system effectiveness and technology acceptance of adopting the ancient book digital humanities research platform with and without the CSNRMT to interpret the characters and character social network relationships.

The experimental results reveal that the experimental group with the CSNRMT support appears higher system effectiveness on the interpretation of characters and character social network relationships than the control group without the CSNRMT, but does not achieve a statistically significant difference. Encouragingly, the experimental group with the CSNRMT support presents remarkably higher technology acceptance than the control group without the CSNRMT. Furthermore, use behaviors analyzed by lag sequential analysis reveal that the CSNRMT could assist digital humanists in the interpretation of character social network relationships. The results of the interview present positive opinions on the integration of system interface, smoothness of operation, and external search function.

Currently, the system effectiveness of exploring the character social network relationships from texts for useful research findings by using the CSNRMT developed in this study will be significantly affected by the accuracy of recognizing character names and character social network relationships from Chinese ancient texts. The developed CSNRMT will be more practical when the offered information about character names and character social network relationships is more accurate and broad.

This study develops an ancient book digital humanities research platform with an emerging CSNRMT that provides an easy-to-use real-time interaction interface to semi-automatically support digital humanists to perform digital humanities research with the need of exploring character social network relationships.

At present, a real-time social network analysis tool to provide a friendly interaction interface and effectively assist digital humanists in the digital humanities research with character social networks analysis is still lacked. This study thus presents the CSNRMT that can semi-automatically identify character names from Chinese ancient texts and provide an easy-to-use real-time interaction interface for supporting digital humanities research so that digital humanists could more efficiently and accurately establish character social network relationships from the analyzed texts to explore complicated character social networks relationship and find out useful research findings.

The purpose of this chapter is to situate how the digitalized research environment is changing the roles of researchers and participants, and how these changes lead to more complex and less discrete ethics challenges. Incorporating contemporary examples from the social sciences, we outline the core challenges of the changing research landscape that embrace both research actors (researcher, participant, and research users) and data issues. The ethical implications related to research actors’ roles are discussed by considering how data is accessed, how people can now participate in research, and issues related to accessing participants. Digital data and associated ethical issues are explored through examining authorship and ownership, how digital data is produced, and how research transparency can be achieved. Following on from this consideration of research actors and data issues, we suggest which challenges have been re-contextualized by the digital environment, and which are novel to the digital research context, outlining six practical yet reflective questions for researchers to ask as a way to navigate ethics in the digital research territory.

The purpose of this research is to explore and define the digital maturity of events using the Industry 4.0 model (I4.0) to create a definition for Events 4.0 (E4.0) and to place various relevant technologies on a scale of digital maturity.

In a mixed methods approach, we carried out a qualitative social media analysis and a quantitative survey of tourism and events academics. These surveys and the thorough literature review that preceded them allowed us to map the digital technologies used in events to levels of a digital maturity model.

We found that engagement with technology at events and delegate knowledge satisfactorily coexists for and across a number of different experiential levels. However, relative to I4.0, event research and the events industry appear to be digitally immature. At the top of the digital maturity scale, E4.0 might be defined as an event that is digitally managed; frequently upgrades its digital technology; fully integrates its communication systems; and optimizes digital operations and communication for event delivery, marketing, and customer experience. We expect E4.0 to drive further engagement with digital technologies and develop further research.

This study has responded to calls from the academic literature to provide a greater understanding of the digital maturity of events and how events engage with digital technology. Furthermore, the research is the first to introduce the concept of E4.0 into the academic literature. This work also provides insights for events practitioners which include the better understanding of the digital maturity of events and the widespread use of digital technology in event delivery.

Digital markets are increasingly constructed by an interplay between (non)human market actors, i.e. through algorithms, but, simultaneously, fragmented through platformization. This study aims to explore how interactional dynamics between (non)human market actors co-codify markets through expressive and networked content across social media platforms.

This study applies digital methods as cross-platform analysis to analyze two data sets retrieved from YouTube and Instagram using the keywords “sustainable fashion” and #sustainablefashion, respectively.

The study shows how interactional dynamics between (non)human market actors, co-codify markets across two social media platforms, i.e. YouTube and Instagram. The authors introduce the notion of sticky market webs of connection, illustrating how these dynamics foster cross-platform market codification through relations of exteriority.

Research implications highlight the necessity to account for all involved entities, including digital infrastructure in digital markets and the methodological potential of cross-platform analyses.

Practical implications highlight considerations managers should take into account when designing market communication for digital markets composed of (non)human market actors.

Social implications highlight the possible effects of (non)human market co-codification on markets and consumer culture, and corresponding countermeasures.

This study contributes to an increased understanding of digital market dynamics by illuminating interdependent market co-codification dynamics between (non)human market actors, and how these dynamics (de)territorialize digital market assemblages through relations of exteriority across platforms.

This chapter critically discusses implications of working with ‘big data’ from the perspective of qualitative research and methodology. A critique is developed of the analytic troubles that come with integrating qualitative methodologies with ‘big data’ analyses and, moreover, the ways in which qualitative traditions themselves offer a challenge, as well as contributions, to computational social science.

The chapter draws on Interactionist understandings of social organisation as an ongoing production, tied to and accomplished in the actual practices of actual people. This is a matter of analytic priority but also points to a distinctiveness of sociological work which may be undermined in moving from the study of such actualities, suggesting an alternative coming crisis of empirical sociology.

A cautionary tale is offered regarding the contribution and character of sociological analysis within the ‘digital turn’. It is suggested that ‘big data’ analyses of traces abstracted from actual people and their practices not only miss and distort the relation of social practice to social product but, consequentially, can take on an ideological character.

The chapter offers an original contribution to current discussions and debates surrounding ‘big data’ by developing enduring critiques of sociological methodology and analysis. It concludes by pointing to contributions and interventions that such an empirical programme of qualitative research might make in the context of the ‘digital turn’ and is of value to those working at the interface of traditional and digital(ised) inquiries and methods.

As a result of the advancement of the online environment, several methodological proposals emerged to establish procedures for digital qualitative research. While the various online ethnography methods overlap, they are not equivalent in terms of their theoretical bases, procedures and goals. The purpose of this article is to add clarity to their main differences, depicting specificities, potentialities and limitations of each method.

This conceptual article results from an integrative literature review that brought together studies that proposed, debated or used qualitative research methods in the digital environment. The research focused on the primary indexed journals publishing cultural studies in the past 20 years.

The literature review highlights four methods – virtual ethnography, digital ethnography, netnography and the post-application programming interface ethnography. The integrative literature review adds clarity depicting the main premises and procedures of each method. The present analysis positions the different methods considering two dimensions: the focus on the boundaries of the group/culture investigated, and the focus on the platform agency, affordances and specific dynamics.

The article proposes a comparative framework outlining points of convergence and divergence to create a reference for researchers on topics of significance while designing and conducting a research study in a digital environment. This conceptual organization highlights and supports qualitative researchers on their methodological challenges.

This chapter explores the ethical complexities of researching location-aware social discovery Smartphone applications (apps) and how they mediate contemporary experiences of travel. We highlight the context-specific approach required to carrying out research on Tinder, a location-aware app that enables people to connect with others in close proximity to them. By journeying through the early stages of our research project, we demonstrate how ethical considerations and dilemmas began long before our project became a project. We discuss the pulls toward data extraction/mining of user-generated content (i.e., Tinder user profiles) within digital social research and the ethical challenges of using this data for research purposes. We focus particularly on issues of informed consent, privacy, and copyright, and the differences between manual and automated data mining/extraction techniques. Excerpts from our university ethics application are included to demonstrate how our research sits uneasily within standardized ethical protocols. Our moves away from a ‘big data’ approach to more ‘traditional’ and participatory methodologies are located within questions of epistemology and ontology including our commitment to practicing a feminist research ethic. Our chapter concludes with the lessons learned in the aim to push forward with research in challenging online spaces and with new data sources.