PhD Position: temporal and semantic analysis of richly typed social networks 
from user-generated-content sites on the web


Topic:
There is now a strong interest in combining Social Network Analysis with 
Semantic Web frameworks in order to include inferences in the analysis of the 
social structure and exchanged data we capture through online social web sites.
But in many scenarios we not only need to understand the structure of an 
epistemic community and its resources, we also need to monitor the evolutions, 
trends, flows, signals, etc. of the dynamics of this complex networking.
In this Ph.D. proposal the candidate will consider how we can reconcile 
temporal reasoning, social network analysis, semantic web formalisms and graph 
dynamics to provide an innovative conceptual framework for temporal and 
semantic analysis of richly typed social networks from user-generated-content 
sites on the web.
The work plan includes:
(1) Study of the state of the art of models and algorithms to formalize and 
semantically analyze folksonomies, forum, discussions and social networks in 
the context of communities of interest on the open web.
(2) Exploit these representations to support the detection of possibly 
overlapping communities of interest, the roles and characteristics of users in 
the community, their profiles, and their interactions and relations.
(3) Revisit these semantic and structural models to integrate temporality in 
their formal definitions to go beyond the static analysis of a snapshot of the 
network and support the detection of emerging communities and dying ones, new 
topics, recurrent long term interests, etc.
An important aspect of this work will be the integration of the time dimension 
to semantic web frameworks for the representations of social web application 
data and the extension of semantic web operators (e.g. SPARQL), the social 
network metrics (e.g. betweenness centrality) and community analysis algorithms 
(e.g. labeled community detection) to exploit the temporal dimension and 
provide trends indicators.


About the Wimmics team:
Wimmics stands for Web-Instrumented Man-Machine Interactions, Communities, and 
Semantics. Wimmics research team conducts research in the domain of graph-based 
knowledge representation and inference systems applied in particular to 
semantic web and social web.  The research fields of this team are 
graph-oriented knowledge representation, reasoning and operationalization to 
model and support actors, actions and interactions in web-based epistemic 
communities. 
see: http://wimmics.inria.fr


Profile: The student should have a master degree in computer science and a 
strong knowledge of web and preferably semantic web standards.
Duration: 36 months
Place: Sophia Antipolis, France
Contact: [email protected]
Subject on-line: http://wimmics.inria.fr/node/40
-- 
fabien, inria, @fabien_gandon, http://fabien.info




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