Based upon findings and results from our recent research we propose a generic frame- work concept for researcher profiling with appliance to the areas of ”Science 2.0” and ”Research 2.0”. Intensive growth of users in social networks, such as Twitter generated a vast amount of information. It has been shown in many previous works that social networks users produce valuable content for profiling and recommendations. Our research focuses on identifying and locating experts for specific research area or topic. In our approach we apply semantic technologies like (RDF, SPARQL), common vocabularies (SIOC , FOAF, MOAT, Tag Ontology) and Linked Data (GeoNames , COLINDA).

1. ELIS – Multimedia Lab
Laurens De Vocht, Erik Mannens, Rik Van de Walle (Ghent University – iMinds)
Selver Softic, Martin Ebner (Graz University of Technology)
A Framework Concept for Profiling Researchers
on Twitter using the Web of Data

2. 2/18
ELIS – Multimedia Lab
A Framework Concept for Profiling Researchers on Twitter using the Web of Data
Laurens De Vocht
09-05-2013
1. Introduction
2. Use Case
3. Implementation
4. Evaluation
5. Aligning Multiple Resources
6. Conclusions & Future Work
Overview

3. 3/18
ELIS – Multimedia Lab
A Framework Concept for Profiling Researchers on Twitter using the Web of Data
Laurens De Vocht
09-05-2013
Introduction (1/3)
Who has scientific information
relevant for me?
Web users generate a huge
unstructured information flow
?

4. 4/18
ELIS – Multimedia Lab
A Framework Concept for Profiling Researchers on Twitter using the Web of Data
Laurens De Vocht
09-05-2013
Introduction: Research 2.0 (2/3)
Digital Libraries Google
Social Media
Online Events and
Announcements
?
Web of Data

5. 5/18
ELIS – Multimedia Lab
A Framework Concept for Profiling Researchers on Twitter using the Web of Data
Laurens De Vocht
09-05-2013
Introduction: Facilitate Research Collaboration (3/3)

6. 6/18
ELIS – Multimedia Lab
A Framework Concept for Profiling Researchers on Twitter using the Web of Data
Laurens De Vocht
09-05-2013
Use Case: Overview
Connecting researchers based on shared scientific events (conferences)

7. 7/18
ELIS – Multimedia Lab
A Framework Concept for Profiling Researchers on Twitter using the Web of Data
Laurens De Vocht
09-05-2013
Use Case: Example
Bob is giving an interesting presentation
at #ISEMANTICS2012 in Graz
Wondering how Graz people are
dealing with #semantics…
Linked
Data
Entities
Explicit
Connection
Implicit
Connection

8. 8/18
ELIS – Multimedia Lab
A Framework Concept for Profiling Researchers on Twitter using the Web of Data
Laurens De Vocht
09-05-2013
Implementation
Commonly used
Ontologies
e.g. FOAF, SIOC
Annotated Data from Social
Networks
Linked Open Data
Connect People and Resources
Conferences
Locations
Tags, Posts,
Mentions
General Concepts and Facts

9. 9/18
ELIS – Multimedia Lab
A Framework Concept for Profiling Researchers on Twitter using the Web of Data
Laurens De Vocht
09-05-2013
Implementation: Architecture

10. 10/18
ELIS – Multimedia Lab
A Framework Concept for Profiling Researchers on Twitter using the Web of Data
Laurens De Vocht
09-05-2013
Implementation: Match rating between two users

11. 11/18
ELIS – Multimedia Lab
A Framework Concept for Profiling Researchers on Twitter using the Web of Data
Laurens De Vocht
09-05-2013
Evaluation
‣ get User Profile
‣ find People or Events given a User Profile
‣ register a new User Profile
‣ get Event Details
Service for efficient discovery of people and events

12. 12/18
ELIS – Multimedia Lab
A Framework Concept for Profiling Researchers on Twitter using the Web of Data
Laurens De Vocht
09-05-2013
Evaluation: User Profile

13. 13/18
ELIS – Multimedia Lab
A Framework Concept for Profiling Researchers on Twitter using the Web of Data
Laurens De Vocht
09-05-2013
Evaluation: Find People

14. 14/18
ELIS – Multimedia Lab
A Framework Concept for Profiling Researchers on Twitter using the Web of Data
Laurens De Vocht
09-05-2013
Evaluation: Find Events

15. 15/18
ELIS – Multimedia Lab
A Framework Concept for Profiling Researchers on Twitter using the Web of Data
Laurens De Vocht
09-05-2013
How to combine information from multiple sources?
More connections from more sources would lead to more reliability
according to qualitative user evaluation. (De Vocht et al., 2011)

16. 16/18
ELIS – Multimedia Lab
A Framework Concept for Profiling Researchers on Twitter using the Web of Data
Laurens De Vocht
09-05-2013
Aligning Resources: Example
Linked
Data
Entities
More Connections!

17. 17/18
ELIS – Multimedia Lab
A Framework Concept for Profiling Researchers on Twitter using the Web of Data
Laurens De Vocht
09-05-2013
Conclusions & Future Work
Future Work
Measure precision and recall of presented results
Align more resources to obtain more reliability and information quality
Integrate user profile and context to improve matching and interlinking.
Conclusions
Enrichment of Social Media Data with Linked data:
Allows semantically motivated comparison between resources
Implemented framework with current state-of-the art technologies
Possible to discover connections between resources in big datasets

18. 18/18
ELIS – Multimedia Lab
A Framework Concept for Profiling Researchers on Twitter using the Web of Data
Laurens De Vocht
09-05-2013
Some References
De Vocht, L., Van Deursen, D., Mannens, E., & Van de Walle, R. (2012). A
Semantic Approach to Cross-Disciplinary Research Collaboration. International
Journal Of Emerging Technologies In Learning (IJET), 7(S2), pages 22 - 30.
Laurens De Vocht, Selver Softic, Martin Ebner, and Herbert Mühlburger. 2011.
Semantically driven social data aggregation interfaces for Research 2.0.
In Proceedings of the 11th International Conference on Knowledge Management
and Knowledge Technologies (i-KNOW '11), Article 43, 9 pages.
laurens.devocht@ugent.be
@laurens_d_v
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