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In:Digital and Internet-Based Research Methods in Applied Linguistics
Edited by Matt Kessler
[Research Methods in Applied Linguistics 15] 2026
► pp. 58–80

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Chapter 4
Netnography and digital ethnographic approaches

 | Michigan State University
 | Michigan State University
 | Michigan State University
Published online: 5 January 2026
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https://doi.org/10.1075/rmal.15.04dec
Abstract
The notion of what constitutes the language classroom has developed over time, to the point where applied linguists have increasingly investigated the impact of out-of-class exposure on the traditional bricks-and-mortar classroom. Of particular interest is the digital classroom, and traditional classroom ethnographies have also made this digital migration. Building on these recent developments, in this chapter we discuss how ethnographic tools have to be modified across digital spaces to better understand the complexities surrounding evolving classroom cultures and other applied linguistics contexts. We draw on insights from one particular brand of ethnography, netnography. Specifically, we describe the netnography research process, provide examples of netnographies, and discuss ethical dilemmas that often emerge in netnographic research. The chapter closes with suggestions for the future, in light of the growing influence of generative artificial intelligence on language education and the need for research on underrepresented populations.
Article outline
  • 1.Introduction
  • 2.Frequently asked research questions
  • 3.Implementation
    • Data sources
      • Investigative data
      • Interactive data
      • Immersive data
    • Research process (step-by-step guide)
      • Step 1: Defining the research purpose and question
      • Step 2: Identifying the online community or platform
      • Step 3: Collecting data
      • Step 4: Analyzing data
      • Step 5: Presenting data
  • 4.Example studies
    • Janes and Chen (2024)
    • Yu and Xu (2024)
    • Nguyen and Pham (2023)
    • Chen et al. (2023)
    • Wang et al. (2024)
    • Discussion
  • 5.Ethics and research integrity considerations
    • Before the study
    • During the study
    • After the study
  • 6.Challenges and issues
    • Challenges in data collection
    • Challenges in data analysis
  • 7.Future research directions
    • AI integration
    • Emotional studies in digital contexts
    • Underrepresented languages and populations
  • References
References (33)
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