Netnography is a "form of qualitative research that seeks to understand the cultural experiences that encompass and are reflected within the traces, practices, networks and systems of social media".
The term is a portmanteau combining "Internet" or "network" with "ethnography". Netnography was originally developed in 1995 by marketing professor Robert Kozinets (now USC Annenberg) as a tool to analyze online fan discussions about the Star Trek franchise. The use of the method spread from marketing research and consumer research to a range of other disciplines, including education, library and information sciences, hospitality, tourism, computer science, psychology, sociology, anthropology, geography, urban studies, leisure and game studies, and human sexuality and addiction research.
It is a specific set of research practices related to data collection, analysis, research ethics, and representation, rooted in participant observation that can be conceptualized into three key stages: investigation, interaction, and immersion. A significant amount of the data originates in and manifests through the digital traces of naturally occurring public conversations recorded by contemporary communications networks. Netnography uses these conversations as data. It is an interpretive research method that adapts the traditional, in-person participant observation techniques of anthropology to the study of interactions and experiences manifesting through digital communications . Netnography and ethnography Though netnography is developed from ethnography and applied in the online settings, it is more than the application of qualitative research in the form of traditional ethnographic techniques in an online context. There are several characters that differentiate netnography from ethnography.
Research focus. Netnographic research is more focused on reflections and data provided by online communities, whereas ethnography can focus on the entire human society. Communication focus. Ethnography comprises research into all forms of human communication, including body language and tone of voice. Netnography incorporates human online communication, which is textual communication, or some multimedia communication such as video, audio, pictures. Research method. Netnography offers a less intrusive research experience than ethnography, because netnography uses mainly observational data. Netnography is more naturalistic than personal interviews, focus groups, surveys, and experiments, whose data quality are largely influenced by the researcher. In addition, participants may alter their reactions/answers when involving in the interviews, focus group and surveys. The main advantage of netnography is that individuals reveal information, including sensitive details, unasked and voluntarily online naturally, and the netnographer could gain this organic information through observation. Data collection. Compared with traditional ethnography which requires researchers physically immerse into the samples to collect data, netnographic researchers are able to download communication data directly from an online community. Netnographic researchers do not become members of communities and cultures as in traditional ethnographic practice, but are instead engaged in various and flexible levels of committed and public online social interaction, thus immerse oneself in the community. Thus ethnography usually collects real-life observation and primary data, and netnography usually collects computer-based and secondary data Efficiency. Netnography tends to be less costly and timelier than many other methods because it leverages online archives and existing technologies to rapidly and efficiently gather and sort relevant data. Netnographic research is faster and cheaper in comparison with ethnographic research. Number of participants. Netnography enables the researcher to investigate a large number of people, even more than when using ethnography. Retroactivity. Netnography could trace back conversations several years ago so that allow researchers understand the history or the development of a topic/community, but ethnography can only study the current situation. Netnography is also similar to ethnography in these ways: It is naturalistic: it seeks to study online social interaction by participating within and observing it; It is immersive: it involves the researcher as the key element in data collection and creation; It is descriptive: it seeks rich contextual portrayals of the lived experience of online social life; It is multi-method: it can involve a range of other methods, such as interviews, semiotic visual analysis, and data science; and It is adaptable: it can be used to study many types of online sites and technology-related communications and interaction
Keys components
Key components of netnography include emotion/story, the researcher, key source person, and cultural fluency.
Emotion and story
Netnography combines rich samples of communicative and interactions flowing through the internet: textual, graphic, audio, photographic and audio-visual. The data then will be analysed using content analysis, semiotic visual analysis, interviews (online and in person), social network analysis and the use of big data analytic tools and techniques. These techniques are employed to find the emotional story behind a subject.
This what differentiate netnography to big-data analysis that often relies on machine (sentiment analysis, word cloud) and also to digital ethnography or digital anthropology. These terms (netnography, digital ethnography, and digital anthropology) are often used interchangeably, but they are very different.
The difference between netnography and digital ethnography could be seen in several ways, but the most obvious one is the research motivation and methodology determined by the purpose. Netnography focuses on internet users forming an online community which is highlighted from the substantial daily life, while digital ethnography only treat the digital world as a place to extend their offline data collection to complement the ethnographic research. The methodological framework between them are not typically different, since netnography mainly use online qualitative techniques and use online quantitative research as a supplement occasionally, while digital ethnography combines both quantitative (e.g., network and co-word analysis) and qualitative (e.g., sentiment and content analysis) techniques.
To find the emotional story, big data analysis is often used as a complementary technique, usually at the beginning of the research. However, instead of scooping a huge amount of data and relying on machine to analyse it, the strength of netnography is contextualized data, human-centered analysis, and resonant representation.
In the Journal of Marketing Management, Emma Reid and Katherine Duffy proposed a framework they termed "netnographic sensibility", using Pulsar as a case study platform to demonstrate how large-scale social media data can be gathered, segmented, and triangulated alongside qualitative netnographic analysis, extending what manual data collection can achieve while retaining the interpretive depth that distinguishes netnography from simple content analysis.
Researcher In netnography, to find the necessary emotion, the story behind the individuals, the researcher has to have a deep understanding of the culture that surrounds the data that she uses. They have to immerse themself in the community where they source their data. Humans are complex beings, and the human language has depth: nuance, symbolism, sarcasm, to name a few. Not to mention context. What is acceptable or positive in one culture might be the total opposite in others. Unearthing the layers is a complicate and delicate process no algorithm can currently perform.
If a researcher wished to understand the sentiment of a brand's customers or potential consumers towards a specific brand, the easiest thing to do is arguably analyzing the comments section of the brand's website. However, should there be a substantial number of comments that are using sarcastic language, solely using a machine-generated algorithm will give the wrong conclusion.
Key source person The key to understand the culture is to find rich data from a 'key source person'. To find the reason behind perception of a brand or the reason behind brand loyalty, a netnographer needs to comb through the comments sections to find consumers with a particularly strong attitude - either negative or positive - towards the brand in question.
Cultural fluency The goal of a netnographer is cultural literacy or "fluency", which means that at the end of the research, the researcher should be fluent in the symbolic language of the site's users that they have an almost biographical authority regarding them.
Cultural meaning(s) embedded in the Internet
Unlike the fetishization of big data and its attempt to portray a generic, characterization of markets in online communities (i.e., frequency of brand engagement), netnography enables researchers "to argue for a central tenet" (Kozinets, 2016, p. 2) that emerges from the collected data that represents a particular market. Netnography has an advantage over ethnography in that it focuses primarily on the context of textual communication and any affiliated multimedia elements, whereas ethnography focuses primarily on physical forms of human communication (e.g., body language) (Bartl et al., p. 168). Since Netnography uses spontaneous data and conducts observation without intruding online users, it is regarded as more naturalistic than other approaches such as interviews, focus groups, surveys and experiments (Kozinets, 2015). While online communication has a relatively shorter duration in efficiency when compared to human communication, the speed in collecting online communication is much faster and far less expensive than traditional in-person ethnography and other qualitative methodologies like focus groups or interviews . It is also a challenging approach involving work to tackle unpredictable and abundant data (Kozinets, 2015).
The need to understand the cultural meaning of online communities (e.g., Reddit; LinkedIn) has grown exponentially since the appraisal of Web 2.0 interfaces (i.e., user-generated content), along with other technological advances. One can no longer assume that people are isolating themselves from the physical world with technology, but rather view technology such as computer-mediated communication and digital information as a gateway that allows them to interact with familiar and, at times, anonymous users on a given occasion. Furthermore, cultural practices within the physical world are extended to, and enhanced by, these online communities, where people can choose a dating partner, learn about a religion and make brand choices, just to name a few examples. With ethnography's influence on netnography, this research method enables the researcher to link the communication patterns in order to understand the tacit and latent practices involved within and between these online communities of interest (Mariampolski, 2005). As Kozinets pointed out, "these social groups have a 'real' existence for their participants, and thus have consequential effects on many aspects of behaviour, including consumer behavior" (see also Muniz and O'Guinn, 2001).