Dr. Jesús González Boticario, Universidad Nacional de Educación a Distancia (UNED).

Dr. Antonio Rodríguez Anaya, Universidad Nacional de Educación a Distancia (UNED).


There is a growing interest in analysing the affective aspects involved in social media and collaborative environments. Advancements come from accessing a larger spectrum of information sources, which cover cognitive, psychological and physiological features. Thus, the increasing amount of existing communications coming from both social and collaborative settings is paving the way for new research approaches that would take advantage of the interplay of those information sources in large data sets. To this end the field of affective computing has focused on detecting, modelling and providing feedback according to the user affective state. In turn, computer-supported collaborative learning (CSCL) has addressed the modelling issues involved in providing answers to the five Ws: What, Where, Who, When, and Why “effective collaboration” takes place. Finally, Social Network Analysis (SNA) has investigated social structures through the use of networks and graph theory.

However, we have noticed that there are many avenues to be explored in that interplay that require further attention. For instance, in sentiment mining within social media the users were mostly analysed individually, without taking into account that they were interacting with others. In other words they are playing roles in a given context where new tools and techniques can be applied. Further, the new observable features coming from the user’s emotion, cognition and behaviour expand the so many possible analysis that can be conducted to answer concrete issues that have been opened for decades, such as figuring out why, when and how the user is engaged in a given situation.

Bearing all the above in mind, the aim of this session is to provide a meeting point for IWINAC attendees and researchers who have a current or developing interest in the analysis of affective aspects in a social media environment but taking into account the social context of the participants and/or the new observable features coming from the user’s emotion, cognition and behaviour.

Topics areas are include (but not restricted to):

  • Affect in social media
  • Affective computing in social media
  • Affective computing in collaborative settings
  • Distance education, E-learning and affect
  • Data mining and sentiment analysis in social context
  • Social network analysis and affect
  • Social and emotional user modelling