SOCIAL MEDIA MANAGEMENT

Academic Year 2016/2017 - 3° Year - Curriculum A

Teaching Staff: Giovanni Maria FARINELLA
Credit Value: 6
Taught classes: 48 hours
Term / Semester: 1°

Learning Objectives

The course aims to present theories and techniques for the analysis of multimedia social data ( images , text, tags , metadata ).

Social Media, Computational Social Science e Marketing Digitale
Big Data, Sentiment Analysis e Visual Analytics
APIs and libraries for the exploration, visualization and analysis of social media data
Machine Learning e Pattern Recognition algorithms with applications in the context of Social Media
Computer Vision algorithms with applications in the context of Social Media
Deep Learning

R. Zafarani, M. A. Abbasi, H. Liu, Social Media Mining - An Introduction, Cambridge University Press, 2014
J. Leskovec, A. Rajaraman, J. D. Ullman, Mining of Massive Datasets, Cambridge Press, 2011
C. Bishop, Pattern Recognition and Machine Learning, Springer, 2006
E. Alpaydin, Introduction to Machine Learning, The MIT Press, 2009
Y. Bengio, I. J. Goodfellow, A.Courville, Deep Learning, Book in preparation for MIT Press, 2015
Duda, P. E. Hart, D. G. Stork, Pattern Classification (2nd ed.), Wiley, 2000
Murphy, Machine Learning – A Probabilistic Perspective, The MIT Press, 2012
R. C. Gonzales, R.E. Woods, Elaborazione delle Immagini Digitali, Pearson Italia 2008
R. Szeliski, Computer Vision: Algorithms and Application, Springer 2010
S. J.D. Prince, Computer Vision: Models, Learning, and Inference, Cambridge University Press, 2012