The 10th International ACM Web Science Conference was held from Sunday May 27 to Wednesday May 30 (2018) in Amsterdam, The Netherlands. The Alexandria project was present in this annual venue with the following contributions:
– Viewpoint Discovery and Understanding in Social Networks (by Mainul Quraishi, Pavlos Fafalios, and Eelco Herder) [PAPER]
– DistrustRank: Spotting False News Domains (by Vinicius Woloszyn and Wolfgang Nejdl) [PAPER]
The first paper proposes a graph partitioning method that exploits social interactions to enable the discovery of different communities (representing different viewpoints) discussing about a controversial topic in a social network like Twitter. To explain the discovered viewpoints, the paper describes a method, called Iterative Rank Difference (IRD), which allows detecting descriptive terms that characterize the different viewpoints as well as understanding
how a specific term is related to a viewpoint (by detecting other related descriptive terms). Such a method enables better understanding of ongoing political or societal debates, or analyzing and interpreting the course of historical events retrospectively.
The second paper proposes a semi-supervised learning strategy to automatically separate fake news from reliable news sources. The ouput is a trust (or distrust) rank that can be used in two ways: a) as a counter-bias to be applied when News about a specific subject is ranked (in order to discount possible boosts achieved by false claims), and b) to assist humans to identify sources that are likely to inclde fake news (or that are likely to be reputable), suggesting websites that should be examined more closely or to be avoided.
The work in this project is funded by the