Claudia Wagner

Claudia Wagner
Interests:
Computational Social Science, Data Mining, Text Mining, Network theory and dynamics, Web Science, Semantic Web
Email:
claudia dot wagner at gesis dot org OR clwagner at uni-koblenz dot de
Skype:
clauwag
Phone:
+49-0221-47694-224
Work address:
Computational Social Science Department,
GESIS - Leibniz Institute for Social Sciences
,
Unter Sachsenhausen 5-7,
Cologne, Germany
URI:
http://clauwa.info/me
Web:
Brief Bio:

Currently I am a Post Doctoral Researcher at the Computational Social Science Department at GESIS - Leibniz Institute for the Social Sciences and an Adjunct Lecturer at the University of Koblenz-Landau. My research interests include computational social science and network theories, data mining and natural language processing.

Previously, I did my master and my PhD in Computer Science at Graz University of Technology and worked as a research assistant at JOANNEUM RESEARCH in Graz, Austria. From February 2013 until April 2013 I was interning at HP labs where I was part of the Social Computation Research group. In summer 2011, I worked at the Augmented Social Cognition Group at Xerox PARC where I worked with Les Nelson and Peter Pirolli on creating topical expertise model of Twitter users. From October 2008 to February 2009 and in March and April 2011, I was an intern at the Knowledge Media Institute (KMi), Open University, where I worked with Enrico Motta, Matthew Rowe and Harith Alani on analyzing relations between different types of user activities and semantics.

Post-Doctoral Research:

Social Scientists are interested in how people think/feel/behave in social situations (social psychology), relate to each other (sociology), govern themselves (political science), handle wealth (socio-economics) and create culture (anthropology). In my post doctoral research I aim to investigate relevant social science questions by devloping and evaluating computational methods for analyzsing human's digital footprints.

Political Discourse in Twitter: In this project we investigate political discourse in Twitter. We are mainly interested in understanding to what extent the political ecosystem is reflected on Twitter and how social and semantic structures of politicians evolve over time -- i.e., how they change before, during and after elections.

Spatial and Temporal Dietary Patterns: In this project explore to what extent the information access behavior of users in online recipe platforms can be used to as a proxy for studying dietary patterns in Europa. We explore questions such as: In which regions do people eat especially healthy? Where and when do people consume most sugar or fat? Do these online observations which we obtain via unobtrusive research methods relate with offline observations (e.g., regional health statistics) which we obtain from reactive-research methods?

PhD Research:

Social streams are aggregations of data that are produced by a temporal sequence of users' activities conducted in an online social environment like Twitter or Facebook where others can perceive the manifestation of these activities. Although previous research shows that social streams are a useful source for many types of information, most existing approaches treat social streams as just another textual document and neglect the fact that social streams emerge through user activities. This thesis sets out to explore potential relations between the user activities which generate a stream (and therefore impact the emergent structure of a stream) and the semantics of a stream.

My thesis introduces a network-theoretic model of social streams which allows to formally describe social streams and the structures which emerge from them. Further, several structural stream measures which allow to compare different social streams and a novel measure for assessing the stability of emerging structures of social streams are presented in this work. In several empirical studies my thesis explores if a relation between semantics and user activities exists and if so to what extent this relation can be exploited for (1) the creation of semantic annotations of social streams and users and (2) the prediction of users' future activities in social streams.

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