Semantically interconnected social networks

Abstract

Social network analysis aims to identify collaborations and helps people organize themselves through community participation and information sharing. The primary sources for social network modelling are explicit relationships such as co-authoring, citations, friendship, etc. However, to enable the integration of on-line community information and to fully describe the content and structure of community sites, secondary sources of information, such as documents, e-mails, blogs and discussions, can be exploited. In this paper we describe a methodology and a battery of tools to automatically extract from documents the relevant topics shared among community members and to analyse the evolution of the network also in terms of emergence and decay of collaboration themes. Experiments are conducted on a scientific network funded by the European Community, the INTEROP network of excellence, and on the United Kingdom research community in medical image understanding and analysis.

Ideas with impact: How connectivity shapes idea diffusion

“…In this paper, we further extend this line of research with a network perspective. By using content networks to assess the connectivity of an idea relative to the other ideas in our dataset, we were able to uncover not only idea similarity (as we would have by using, for example, topic modeling), but also the underlying structure of ideas and how they bridge different knowledge domains (Cucchiarelli et al, 2012;Leydesdorff and Nerghes, 2015). Compared to other text-analytical methods, content networks are better able to reveal those ideas that bridge established knowledge domains by making use of the inherent meaning structures of ideas-in our case, publication titles.…”

“…Content networks have been defined as two-mode undirected and binary semantic networks in which publications are related when the words and concepts in the titles co-occur (Cucchiarelli et al, 2012;Leydesdorff, 1989;Rice and Danowski, 1993). Semantic networks project text (in our case publication titles) into networks of concepts and the ties between them, where a concept can be a word or a phrase (Popping, 2003), and a tie a shared affiliation or co-occurrence.…”

Interests diffusion in social networks

“…Merging the topological and semantic analysis of social networks represents a new and potentially fruitful research field which is providing promising results [17] [18] [19] [20] [21]. Our work shares the use of a semantic conceptual representation of a Domain of Interest [22] in the social network context with the formers.…”