PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Coletto M., Lucchese C., Orlando S., Perego R., Chessa A., Puliga M. Twitter for election forecasts: a joint machine learning and complex network approach applied to an italian case study. Accepted for Poster Presentation at the International Conference on Computational Social Science 2015. Technical report, 2015.
 
 
Abstract
(English)
Several studies have shown how to approximately predict real-world phenomena, such as political elections, by ana- lyzing user activities in micro-blogging platforms. This ap- proach has proven to be interesting but with some limita- tions, such as the representativeness of the sample of users, and the hardness of understanding polarity in short mes- sages. We believe that predictions based on social network analysis can be significantly improved by exploiting machine learning and complex network tools, where the latter pro- vides valuable high-level features to support the former in learning an accurate prediction function.
Subject Online Social Networks
H.2.8 Database Applications Data mining


Icona documento 1) Download Document PDF


Icona documento Open access Icona documento Restricted Icona documento Private

 


Per ulteriori informazioni, contattare: Librarian http://puma.isti.cnr.it

Valid HTML 4.0 Transitional