Social network data and practices: the case of friendfeed

Authors:
Fabio Celli;F. Marta L. Di Lascio;Matteo Magnani;Barbara Pacelli;Luca Rossi
Affiliations:
Language Inter. and Comp. Lab, Univ. of Trento;Dept. of Statistical Science, University of Bologna;Dept. of Computer Science, University of Bologna;Independent researcher;Dept. of Communication Studies, University of Urbino
Venue:
SBP'10 Proceedings of the Third international conference on Social Computing, Behavioral Modeling, and Prediction
Year:
2010

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Abstract

Due to their large worldwide adoption, Social Network Sites (SNSs) have been widely used in many global events as an important source to spread news and information. While the searchability and persistence of this information make it ideal for sociological research, a quantitative approach is still challenging because of the size and complexity of the data. In this paper we provide a first analysis of Friendfeed, a well-known and feature-rich SNS.