Discovering Links Among Social Networks
Abstract
Distinct social networks are interconnected via bridge users, who play thus a key role when crossing information is investigated in the context of Social Internetworking analysis. Unfortunately, not always users make their role of bridge explicit by specifying the so-called me edge (i.e., the edge connecting the accounts of the same user in two distinct social networks), missing thus a potentially very useful information. As a consequence, discovering missing me edges is an important problem to face in this context yet not so far investigated. In this paper, we propose a common-neighbors approach to detecting missing me edges, which returns good results in real life settings. Indeed, an experimental campaign shows both that the state-of-the-art common-neighbors approaches cannot be effectively applied to our problem and, conversely, that our approach returns precise and complete results.
Cite
Text
Buccafurri et al. "Discovering Links Among Social Networks." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2012. doi:10.1007/978-3-642-33486-3_30Markdown
[Buccafurri et al. "Discovering Links Among Social Networks." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2012.](https://mlanthology.org/ecmlpkdd/2012/buccafurri2012ecmlpkdd-discovering/) doi:10.1007/978-3-642-33486-3_30BibTeX
@inproceedings{buccafurri2012ecmlpkdd-discovering,
title = {{Discovering Links Among Social Networks}},
author = {Buccafurri, Francesco and Lax, Gianluca and Nocera, Antonino and Ursino, Domenico},
booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
year = {2012},
pages = {467-482},
doi = {10.1007/978-3-642-33486-3_30},
url = {https://mlanthology.org/ecmlpkdd/2012/buccafurri2012ecmlpkdd-discovering/}
}