Social network analysis has emerged in recent years as an important tool for examining social phenomena. In this review, Filipa M. Ribeiro, PhD researcher and science writer from University of Porto examines a recent dissertation on social network analysis that amongst else provides suggestions to how one can use social data and avoid the so-called echo-chamber effect.
At a first glance, the dissertation entitled “Emotions and Recommender Systems: A Social Network Approach”, by Carlos Figueiredo from the University of Austin, Texas, does not seem to relate to other fields than digital media. However, his research and considerations on the use of massive social data is useful for all fields, particularly education related fields as it deals with the current threats of using massive quantities of social data and social networks.
But first things first and let’s summarize the main strong points of this research work. First, the topic about the emotional implications of recommender system is of central importance to digital media and communication.