Advancing netnography – hybdrid ways of coding social media content

Purpose The aim of the research was to develop a methodological framework for coding data from social media. Design/methodology/approach The research is based on netnography, a qualitative research approach that combines online observation, digital traces, and elicitation techniques to study online phenomena. Findings Our study identified five key challenges in coding social media data (1) social media posts often function as coherent, multifaceted units of meaning, rather than discrete words or isolated sentences; (2)multi-Coding Necessity: Posts frequently convey multiple messages, necessitating simultaneous assignment of several codes to a single post unlike traditional coding practices that emphasize isolating individual meanings; (3) Iterative Codebook Development: Creating a reliable coding framework required up few rounds of refinement, highlighting the need for iterative development processes; (4) Lower Inter-Rater Agreement: Agreement levels among coders were lower than typically expected in conventional coding. Achieving a 75% agreement rate required extensive discussion and refinement; (5) Importance of Multiple Raters: Engaging more than two coders significantly improved the methodological rigor of the codebook development. Research limitations/implications The dataset was limited to firm–stakeholder interactions. Different dynamics might present other coding challenges. The exemplary dataset was relatively small and manageable. Larger datasets may require different sampling and coding strategies, limiting the direct transferability of our framework. Our framework was developed inductively from a single case. A synthesis of coding practices across multiple netnographic studies could further refine a literature-informed methodology. Existing studies rarely report coding procedures in detail, limiting opportunities for comparison or replication. Our framework focuses on textual data. However, visual and audiovisual elements in social media play an increasingly important role and warrant further methodological development. Practical implications We encourage researchers to treat entire posts as the basic unit of coding and allow for multiple codings to reflect the complexity of social media discourse. The actual process of developing a codebook should involve multiple coders and several rounds of iteration and discussion. A codebook can facilitate automated content analysis across larger data sets, increasing scalability while maintaining methodological rigor. Our recommendations provide a foundation for future guidance and best practices in digital qualitative research. Originality/value This study contributes a novel and structured framework for coding qualitative social media data – a methodological gap in the current netnographic literature. It offers practical strategies for addressing key challenges in coding complex digital content. By highlighting the limitations of traditional coding approaches to social media data, the study develops methodological guidelines useful to researchers and sets the stage for future research on the dataset.