In recent years we are witnessing a growing spread of social media footprints, as the consequence of the wide use of applications such as Facebook, Twitter or LinkedIn, which allow people to share content that might provide information about personal preferences and aptitudes. Among the traits that can be inferred, empathy is the ability to feel and share another person's emotions and we consider it as a relevant aspect for the proâ¬ling and recommendation tasks. We propose a method that predicts its level for the user by exploiting her social media data and using linear regression algorithms. The results show which are the most relevant correlations among the different groups of user's features and the empathy level predicted.
Scheda prodotto non validato
Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo
|Titolo:||Learning inclination to empathy from social media footprints|
|Data di pubblicazione:||2017|
|Appare nelle tipologie:||4.1 Contributo in Atti di convegno|