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Computational Scientometrics: Theory and Applications

The workshop will be held at iConference 2013

Location: Dallas Fort Worth, Texas
Date: Feb. 12-15, 2013

Organizing Committee:

Cornelia Caragea, University of North Texas, TX, USA
C. Lee Giles, Pennsylvania State University, PA, USA
Vetle I. Torvik, University of Illinois at Urbana-Champaign, IL, USA
Lior Rokach, Ben-Gurion University of the Negev, Israel

Important Dates:

January 10, 2013 - Submission deadline
January 25, 2013 - Notification of acceptance
January 30, 2013 - Camera-ready
February 12, 2013 - Workshop

Workshop Description:

The field of Scientometrics is concerned with the analysis of science and scientific research. As science advances, scientists around the world continue to produce large numbers of research articles, which provide the technological basis for worldwide collection, sharing, and dissemination of scientific discoveries. Research ideas are generally developed based on high quality citations. Understanding how research ideas emerge, evolve, or disappear as a topic, what is a good measure of quality of published works, what are the most promising areas of research, how authors connect and influence each other, who are the experts in a field, what works are similar, and who funds a particular research topic are some of the major foci of the rapidly emerging field of Scientometrics.

Digital libraries and other databases that store research articles have become a medium for answering such questions. Citation analysis is used to mine large publication graphs in order to extract patterns in the data (e.g., citations per article) that can help measure the quality of a journal. Scientometrics, on the other hand, is used to mine graphs that link together multiple types of entities: authors, publications, conference venues, journals, institutions, etc., in order to assess the quality of science and answer complex questions such as those listed above. Tools such as maps of science that are built from digital libraries, allow different categories of users to satisfy various needs, e.g., help researchers to easily access research results, identify relevant funding opportunities, and find collaborators. Moreover, the recent developments in data mining, machine learning, natural language processing, and information retrieval makes it possible to transform the way we analyze research publications, funded proposals, patents, etc., on a web-wide scale.

Call for Papers:

The workshop aims at bringing together researchers with diverse interdisciplinary backgrounds interested in mining large digital libraries and other relevant databases. Topics of interest include, but are not limited to:

• New approaches to measuring the impact of research publications as well as the impact of researchers in a particular field of study.
10. Identifying influential authors, experts, and collaborators within or across disciplines
11. Modeling the referencing behavior across disciplines
12. Automatic citation recommendation
• Mining large digital libraries of scientific publications and linking to other databases such as funded proposals and patents:
10. Identifying research trends and topics
11. Extracting relevant information from research articles
12. Scaling up machine learning algorithms to large datasets
13. Classification and clustering of scientific publications, funded proposal, patents, etc.
14. Linking together various entities, e.g., articles with articles by similarity, articles with the corresponding funded proposals.
• Presenting open-access, novel datasets (e.g., based on Wikipedia, DBpedia, United States Census Bureau data) that can be linked to entities in digital libraries, and can help researcher develop novel technologies for analyzing scientific publications.

Goals of the Workshop:

The primary goal of the workshop is to promote both theoretical results and practical applications to better answer questions and address challenges that are faced by today’s researchers as well as well-known technological companies such as Microsoft and Google and publishers such as Elsevier.

Expected Audience:

This workshop seeks to bring together researchers from applied disciplines such as libraries and sociology as well as from more theoretical disciplines such as mathematics and statistics, within our community of computer and information scientists. Several statistical and computational challenges arise when mining large collections of data such as citation graphs. As diverse communities of researchers use different ideas or perspectives to address these challenges, we seek to foster interdisciplinary collaborations and scholarly exchanges between researchers worldwide.

Submissions:

Submissions related to the above topics are invited. Papers must not exceed 4 pages, must be written in English, and must be formatted according to the iConference template available here. Please submit papers, in pdf format, by email to ccaragea [[at]] unt.edu. Each paper will be reviewed by three Program Committee members.

Program:

• 1:30 - 1:35 Introduction
• 1:35 - 2:00 Predicting Citation Counts Using Text and Graph Mining, by Avishay Livne, Eytan Adar, Jaime Teevan, Susan Dumais
• 2:00 - 2:25 Measuring Researcher Diversity and its Impact on Grant Money, by Tanu Malik, Andrey Rzhetsky, Ian Foster
• 2:25 - 2:50 Next Generation Indicators for Science Policy, by Richard Klavans, Henry Small, Kevin W. Boyack
• 2:50 - 3:50 Keynote talk, by Erik Saule
• 3:50 - 4:10 Break
• 4:10 - 4:35 Using title words to measure cognitive domains of disciplines, by Stasa Milojevic
• 4:35 - 5:00 Result Diversification in Automatic Citation Recommendation, by Onur Küçüktunç, Erik Saule, Kamer Kaya, Ümit V. Çatalyürek
• 5:00 - 5:25 Journal Strategy and Performance: An Empirical Study, by Aaron A. Sorensen, Kevin W. Boyack, Richard Klavans

Program Committee:

Simone Teufel, University of Cambridge
Stevan Harnad, University of Southampton
Caroline Wagner, Ohio State University
Xiaolin Shi, Microsoft Research
Liviu P. Dinu, University of Bucharest
Doina Caragea, Kansas State University
Stasa Milojevic, Indiana University
Ying Ding, Indiana University
Ümit V. Çatalyürek, Ohio State University
Hong Cui, The University of Arizona
Joseph Tennis, University of Washington