Moving Beyond the Twitter Follow Graph

Giambattista Amati, Simone Angelini, Marco Bianchi, Gianmarco Fusco, Giorgio Gambosi, Giancarlo Gaudino, Giuseppe Marcone, Gianluca Rossi, Paola Vocca

2015

Abstract

The study of the topological properties of graphs derived from social network platforms has a great importance both from the social and from the information point of view; furthermore, it has a big impact in designing new applications and in improving already existing services. Surprisingly, the research community seems to have mainly focused its efforts just in studying the most intuitive and explicit graphs, such as the follower graph of the Twitter platform, or the Facebook friends’ graph: consequently, a lot of valuable information is still hidden and it is waiting to be explored and exploited. In this paper we introduce a new type of graph modeling behavior of Twitter users: the mention graph. Then we show how to easily build instances of this graphs starting from the Twitter stream, and we report the results of an experimentation aimed to compare the proposed graph with other graphs already analyzed in the literature, by using some standard social network analysis metrics.

Paper Citation

in Harvard Style

Amati G., Angelini S., Bianchi M., Fusco G., Gambosi G., Gaudino G., Marcone G., Rossi G. and Vocca P. (2015). Moving Beyond the Twitter Follow Graph . In Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: DART, (IC3K 2015) ISBN 978-989-758-158-8, pages 612-619. DOI: 10.5220/0005616906120619

in Bibtex Style

@conference{dart15,
author={Giambattista Amati and Simone Angelini and Marco Bianchi and Gianmarco Fusco and Giorgio Gambosi and Giancarlo Gaudino and Giuseppe Marcone and Gianluca Rossi and Paola Vocca},
title={Moving Beyond the Twitter Follow Graph},
booktitle={Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: DART, (IC3K 2015)},
year={2015},
pages={612-619},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005616906120619},
isbn={978-989-758-158-8},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: DART, (IC3K 2015)
TI - Moving Beyond the Twitter Follow Graph
SN - 978-989-758-158-8
AU - Amati G.
AU - Angelini S.
AU - Bianchi M.
AU - Fusco G.
AU - Gambosi G.
AU - Gaudino G.
AU - Marcone G.
AU - Rossi G.
AU - Vocca P.
PY - 2015
SP - 612
EP - 619
DO - 10.5220/0005616906120619