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공공누리This item is licensed Korea Open Government License

Authority Data based Scientist Network Analysis and Modelling
Alternative Title
Authority Data based Scientist Network Analysis and Modelling
Jana Diesner
Alternative Author(s)
Jana Diesner
Korea Institute of Science and Technology Information
Publication Year
funder : 미래창조과학부
funder : KA
agency : 한국과학기술정보연구원
agency : Korea Institute of Science and Technology Information
I. Summary of the project
1. Main Study Goals
- Research on the methodologies for scientist network analysis
- Development of strategy for automated creation and analysis of network data
- Creation, analysis and interpretation of network of Korean scientist
2. Methodological Approach
We will develop and document a comprehensive, scalable and empirical strategy for mapping and studying the network for Korean scholars. This strategy entails the following steps:
- Automated creation of disambiguated social network data representing relationships between authors based on KISTI’s database. We plan to employ existing software tools for this process (Diesner, Mergel, & Carley, 2011).
- Analysis of these data to understand the structure, functioning and dynamics of these networks. This involves visualizations and network analytical techniques, including key player identification and clustering (Wasserman & Faust, 1994).
- Automated detection of salient themes and concepts for key authors and key clusters. This involves natural language processing techniques. This step goes beyond traditional social network analysis by allowing us to not only understand what individuals and groups drive network formation and dynamics, but also the content domains that these social agents are involved with (Diesner & Carley, 2010, 2011).

3. Study Team
Jana Diesner is an Assistant Professor at the iSchool (a.k.a. Graduate School of Library and Information Science) at the University of Illinois Urbana-Champaign (UIUC), and an affiliate at the Department of Computer Science (CS). She got her PhD from Carnegie Mellon University, School of Computer Science.
Jana’s work is at the nexus of social network analysis, natural language processing and machine learning.
With her team, Jana is developing and advancing computational methods and technologies that help people to measure and understand the interplay and co-evolution of information and socio-technical networks. She brings these computational solutions into various application context, currently mainly in the domains of medical informatics and media impact assessment. For more information about Jana’s work see

Jinseok Kim is a 2nd year Ph.D. student at Graduate School of Library and Information Science at University of Illinois at Urbana-Champaign. His main research area is to find out hidden social networks of people without asking them about their relationship. For this, he looks into the formation and evolution of people’s interpersonal relationships through advanced statistical techniques such as exponential random graph (p*) modeling.

He completed M.A. in communication (2012) at University of Illinois at Urbana-Champaign, and B.A. in English Language and Literature (2001) at Yonsei University. Prior to coming to M.A. program in 2010, he had worked as a South Korean government official for ten years in public administration and social security. Also, he was an assistant secretary to the President of Korea. He had helped the President to communicate with the public through social media from 2008 to 2009.

Shubhanshu Mishra is a 1st year PhD student at the iSchool of University of Illinois at Urbana-Champaign. He is currently working as a Research Assistant with Jana Diesner and Vetle Torvik. He is working on projects at the intersection of Text Network Analysis and Scholarly Data Mining. He is currently part of the team developing ConText, a Text Network Analysis software. He completed his integrated Bachelors and Masters in Mathematics and Computing from the Indian Institute of Technology, Kharagpur (IIT Kharagpur) in 2012. During his undergraduate he was a fellow of the Kishore Vaigyanik Protsahan Yojana, the most prestigious fellowship for science students in India. His master thesis was on "Analysis of Social Media Data to identify Positive and Negatively influential people". Shubhanshu has been an active developer for the last 8 years. He has worked with leading companies like Citrix and Barclays Capital as a Software Engineer. He also worked as a research intern at the Institute of Systems Science, National University of Singapore with Gloria Ng on Maps based mashup of Singapore tourism data.

4. Deliverables
- One international conference paper and one SSCI journal paper
- Final report
- Development Software

5. Duration
- March 1, 2014 – September 30, 2014 (7 months)
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7. KISTI 연구성과 > 연구보고서 > 2014
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