Exploring the interdependence between scientific and public opinion on nutrition through large-scale semantic analysis :
In the field of nutrition, scientific findings often have direct impact on public opinion, and thus on public behavior. Understanding this interdependency among the scientific vs. public opinion is thus of key importance, both from a global health perspective as well as from a communication and marketing perspective of enterprises active in this domain. In addition, the public discussion on nutrition is repeatedly polluted by false or unfounded claims (so called pseudo-science), which are often hard to distinguish from proper science, given the way they are presented in e.g. blogs of self-proclaimed “health advocates”.
This project intends to study the evolution dynamics and distortion of nutritional facts across media channels, through the use of Big Data technologies, social media analysis and machine learning methods, building upon several prior successful projects of the LSIR lab