Publications

@article{terranaAnalysisFacebookUsers2014,

title = {Analysis of Facebook Users' Relationships Through Sentiment Classification: A Case Study of Italian Politicians},

author = { Diego Terrana and Agnese Augello and Giovanni Pilato},

doi = {10.1142/S1793351X14400108},

issn = {1793351X},

year  = {2014},

date = {2014-01-01},

journal = {International Journal of Semantic Computing},

volume = {8},

number = {3},

pages = {301--317},

abstract = {We illustrate a system that analyzes the homepage of a Facebook user or group in order to automatically detect who has discussed what and how it has been discussed. We have focused the analysis on three main actors of Italian politics. The goal is to find people who agree or disagree about given topics with the owner of the Facebook page under analysis. All public posts shared by a user are retrieved by an ad hoc built crawler. Information such as 'posts', 'comments', 'likes', are extracted from the Facebook page. Each post is classified as belonging to a set of predefined categories and its sentiment is also detected as being positive, negative or neutral. All the comments to that post are therefore analyzed and categorized together with its sentiment polarity. For each Facebook user under analysis a statistics of the topics dealt with is made, and for each category a graph is created where the concordance of sentiment is highlighted between the posts belonging to a given class and the related comments of the people interacting with the user or group under analysis. The graph can therefore be used to profile the user relationships according to sentiment classification. textcopyright 2014 World Scientific Publishing Company.},

keywords = {Facebook, Sentiment Analysis, User Profiling},

pubstate = {published},

tppubtype = {article}

}

@article{augelloSensorMiningUser2011,

title = {Sensor Mining for User Behavior Profiling in Intelligent Environments},

author = { Agnese Augello and Marco Ortolani and Giuseppe Lo Re and Salvatore Gaglio},

editor = { Soro A. Vargiu E. Pallotta V.},

doi = {10.1007/978-3-642-21384-7_10},

issn = {1860949X},

year  = {2011},

date = {2011-01-01},

journal = {Studies in Computational Intelligence},

volume = {361},

pages = {143--158},

abstract = {The proposed system exploits sensor mining methodologies to profile user behaviors patterns in an intelligent workplace. The work is based in the assumption that users' habit profiles are implicitly described by sensory data, which explicitly show the consequences of users' actions over the environment state. Sensor data are analyzed in order to infer relationships of interest between environmental variables and the user, detecting in this way behavior profiles. The system is designed for a workplace equipped in the context of Sensor9k, a project carried out at the Department of Computer Science of Palermo University. textcopyright 2011 Springer-Verlag Berlin Heidelberg.},

keywords = {Intelligent Environment, User Profiling},

pubstate = {published},

tppubtype = {article}

}