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What is the image of cheese and wine on Instagram? 

This study is the result of a methodology developed in the context of the 2016-19 Alpine Space Interreg Project AlpFoodway (https://www.alpine-space.eu/projects/alpfoodway/), of which Kedge Business School was the partner responsible for the coordination of commercial valorization activities, and applied to study the social media image of specific products such as the Aosta Valley’s fontina cheese and Arnad Lard, and the Swiss cheese raclette du Valais (all products safeguarded by Protected Denominations of Origin). 

Selected research findings were presented in the context of 2019 exhibition Le Raclette (https://www.museedebagnes.ch/archives/11-musee-de-bagnes/130-exposition-le-raclette) organized by the Musée de Bagnes, which triggered the interest of a Swiss wine museum, which will host an exhibition on the image of wine in 2020 in asking the author to carry out a similar study. 

By presenting selected findings from these research activities the author – who admittedly is not an expert in wine research – seeks input from members of the Kedge Business School’s Wine, Food and Hospitality Centre of Excellence with the goal of improving the quality of the research, discussing its theoretical value and practical use for wine business and trade associations. 

Digital research methods use data spontaneously produced by social media users and/or subsequently aggregated by platforms (Rogers, 2013).

They are adapted to the characteristics the social media platform analysed, which shape user behaviour, the type of content that it is possible to upload and share, and patterns of user interactions. More specifically, the digital research methodology adopted in the research activities described above combined qualitative ethnographic analyses (Caliandro and Gandini, 2015; Kozinets, 2015) with quantitative data capture, analysis and visualisation procedures.

This mixed quali-quantitative methodology combines aspects of the two main approaches to social media analysis, namely ‘big data’ and ‘thick data’.

The big data approach permits to quantitatively analyse massive samples of user-generated social media data. Big data methodologies have generated new manners of capturing, analyzing and visualizing online consumer behaviour and interactions.

Figure 1 reports for example the hashtag network built around the hashtag #racletteduvalais in 2019. While the network is visually appealing, it is virtually impossible to make sense of in a way likely to result in theoretical or managerial insight.

Thick data approaches (Wang, 2013), which are qualitative in nature, work with much smaller samples with the goal of contextualizing and making sense of the use individual users make of social media.

References:
Kedge Business School and University of Innsbruck (2018), Digital Ethnography Research Report on Consumer Response to the Alpine Food Intangible Cultural Heritage, AlpFoodway Research Report. Available online: https://www.alpine-space.eu/projects/alpfoodway/project-results/wp2_d.t2.3.1_digital_ethnography_research_report_final.pdf  (6 December 2020).

Caliandro, A., and Gandini, A. (2015), Qualitative Research in Digital Environments. New York: Routledge.

Kozinets, R. V. (2015) Netnography: Redefined. Los Angeles: Sage.

D. Rinallo, G. Anselmi (2019), “#raclette: Le raclette du Valais sur Instagram”, in B. Seslarzes, M. Hugon-Duc (Eds.), Le Raclette, Edition Musée de Bagnes, Bruson, Svizzera, pp. 78-87.

Rogers, R. (2013), Digital Methods. Boston: The MIT Press. 

Wang, T. (2013), “Big data needs thick data”, Ethnography Matters, 13 May. Available online: http://ethnographymatters.net/blog/2013/05/13/big-data-needs-thick-data/  (6 December 2020).