Authors: Telmo Menezes; Camille Roth; Jean-Philippe Cointet
Addresses: CREA and ISCPIF, CNRS, ISC-57-59, rue Lhomond, F-75005 Paris, France. ' CAMS and ISCPIF, CNRS-EHESS, 54, bd Raspail, F-75006 Paris, France. ' INRA-SenS and ISCPIF, INRA-SenS, Université Paris-Est, Bois de l'Etang, 5, Bd Descartes, Champs sur Marne, F-77454 Marne-la-Vallée, France
Abstract: In this work, we study semantic-level precedence relationships between participants in a blog network. Our methodology has two steps: a process to identify units of discussion at the semantic level and a probabilistic framework to estimate temporal relationships between blogs, in terms of the order in which they arrive at those units of discussion. We propose dyadic precursor scores that can be used to construct semantic-level precedence networks. From these scores, we derive global precursor and laggard scores. Dyadic precursor scores are compared with URL linking to show that the semantic-level temporal relationships we estimate are an indicator of influence. Global scores are compared to traditional link degree and PageRank metrics, and we uncover relationships between semantic-level temporal behaviour and popularity. We show that our method reveals information about the network that could not be obtained from structural links alone.
Keywords: social networks; complex networks; blog networks; network analysis; network metrics; topic detection; temporal relationships; social computing; blogs; semantics; precedence relationships.
International Journal of Social Computing and Cyber-Physical Systems, 2011 Vol.1 No.2, pp.115 - 134
Available online: 11 Dec 2011 *Full-text access for editors Access for subscribers Purchase this article Comment on this article