Claudia Wagner

Claudia Wagner
Interests:
Semantic Web, Knowledge Acquisition, Social Web, Web Science, Web Mining
Email:
claudia.wagner@student.tugraz.at
Skype:
clauwag
Phone:
+43-316-876-2617
Fax:
+43-316-43-876-1403
Work address:
Institute of Information Systems, JOANNEUM RESEARCH, Steyrergasse 17, Graz, Austria
URI:
http://clauwa.info/me
Web:
Brief Bio:

I am a PhD student at Graz University of Technology where I am advised by Markus Strohmaier. My research interests broadly lie in the fields of social web science (i.e., exploring how people use the web and how they can be supported in accomplishing their goals) and semantic web research (i.e., investigating the construction of a meaningful layer on top of the web of documents). I am especially interested in the connection between those 2 fields, i.e. how people assign meaning to documents and other web entities simply by using them and interacting with them.

From February 2013 until April 2013 I will be interning at HP labs where I will be part of the Social Computation Research group. In summer 2011, I was interning 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.

I received my master degree in Computer Science from Graz University of Technology, Austria in 2009.

PhD Research:

On the social web, millions of users participate in the generation of content (upload pictures, post messages, comment on messages and so on) and thereby participate in establishing meaning in an uncontrolled and emergent manner. This phenomenon has been exploited in the past to develop algorithms and techniques that can harvest emergent semantics from user-generated data and metadata to, for example, improve search or to increase machine understanding of user-generated data. However, existing approaches mostly focus on textual analysis, neglecting behavioral and social factors that play a role in the establishment of meaning.

The aim of my PhD research is to enhance our understanding of how pragmatic metadata (i.e., data about the usage of data and users' behavior) may contribute to the automatic generation of semantic metadata (i.e., data about the meaning of data). The generation of semantic metadata is a time consuming task, while pragmatic metadata are generated as a byproduct of user activities on social media applications. Therefore, this research aims to develop new tools and methods which exploit pragmatic metadata to automatically annotate social media content and users with semantic metadata.

Program Committee Memberships and Reviewing:
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