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Digital social networks, such as Instagram, Facebook or Twitter are both repositories of cultural tendencies and common social interests, as well as devices to expand and extend such tendencies among the general population. A relevant number of such cultural tendencies do have an impact in public health. In this talk we will focus on one of the such common cultural tendencies: food consumption. People like to share recipes, new diets, pictures or what they are eating, and so on. Thanks to geolocalization, it is relatively easy to find out the geographical origins or such entries and posts, and see how a food consumption tendency is distributed around the world. Understanding how such digital entries are copied and distributed or “liked” by other users can help us to both see how a tendency generates and how it spreads, as well as its global and local acceptance by users. During the talk we will analyze how data obtained from such digital social networks, specially Twitter, Facebook and Instagram, are being used to analyze patterns of food consumption that can become public health problems, associated with obesity, anorexia, unhealthy diets, etc. We will focus on the epistemic innovations associated with these investigations, analyzing the strengths and weaknesses that have machine-based approaches versus more qualitative analyzes, and assess the epistemic reliability of those approaches.

Using social network analysis to analyze obesity and other public health issues related to food consumption