[Sigmetrics] CFP 2nd Workshop on Mining Scientific Papers: Computational Linguistics and Bibliometrics (CLBib-2017) @ISSI2017
Philipp.Mayr-Schlegel at gesis.org
Wed Aug 2 11:53:36 EDT 2017
== Call for Papers ==
You are invited to participate in the upcoming Second Workshop on Mining Scientific Papers: Computational Linguistics and Bibliometrics (CLBib-2017), to be held as part of the 16th International Society of Scientometrics and Informetrics Conference (ISSI-2017, October 16-20, Wuhan, China, http://www.issi2017.org/).
The call for papers is available at: https://easychair.org/cfp/CLBib2017
=== Important Dates ===
- Abstract registration deadline: September 3, 2017
- Submission deadline: September 10, 2017
- Notification of acceptance: September 30, 2017
- Camera-ready papers: October 6, 2017
- Workshop: October 16-20, 2017 (exact date to be confirmed), Wuhan, China
=== Scope and Aim of the Workshop ===
The open access movement in scientific publishing and search engines like Google Scholar have made scientific articles more broadly accessible. During the last decade, the availability of scientific papers in full text has become more and more widespread thanks to the growing number of publications on online platforms such as ArXiv and CiteSeer. The efforts to provide articles in machine-readable formats and the rise of Open Access publishing have resulted in a number of standardized formats for scientific papers (such as NLM-JATS, TEI, DocBook), full-text datasets for research experiments (PubMed, JSTOR, etc.) and corpora (iSearch, etc.). At the same time, research in the field of Natural Language Processing have provided a number of open source tools for versatile text processing (e.g. NLTK, Mallet, OpenNLP, CoreNLP, Gate, CiteSpace).
Scientific papers are highly structured texts and display specific properties related to their references but also argumentative and rhetorical structure. Recent research in this field has concentrated on the construction of ontologies for citations and scientific articles (e.g. CiTO, LinkedScience1) and studies of the distribution of references . However, up to now full-text mining efforts are rarely used to provide data for bibliometric analyses. While bibliometrics traditionally relies on the analysis of metadata of scientific papers (see e.g. a recent special issue on Combining Bibliometrics and Information Retrieval, Mayr & Scharnhorst, 2015), we will explore the ways full-text processing of scientific papers and linguistic analyses can play. With this workshop we like to discuss novel approaches and provide insights into scientific writing that can bring new perspectives to understand both the nature of citations and the nature of scientific articles. The possibility to enrich metadata by the full-text processing of papers offers new fields of application to bibliometrics studies.
Working with full text allows us to go beyond metadata used in bibliometrics. Full text offers a new field of investigation, where the major problems arise around the organization and structure of text, the extraction of information and its representation on the level of metadata. Furthermore, the study of contexts around in-text citations offers new perspectives related to the semantic dimension of citations. The analyses of citation contexts and the semantic categorization of publications will allow us to rethink co-citation networks, bibliographic coupling and other bibliometric techniques.
The workshop aims to bring together researchers in bibliometrics and computational linguistics in order to study the ways bibliometrics can benefit from large-scale text analytics and sense mining of scientific papers, thus exploring the interdisciplinarity of Bibliometrics and Natural Language Processing. How can we enhance author network analysis and bibliometrics using data obtained by text analytics? What insights can NLP provide on the structure of scientific writing, on citation networks, and on in-text citation analysis?
=== Goals of the workshop ===
The workshop aims to bring together researchers in bibliometrics and computational linguistics in order to study the ways bibliometrics can benefit from large-scale text analytics and sense mining of scientific papers, thus exploring the interdisciplinarity of Bibliometrics and Natural Language Processing.
The first edition of this workshop, co-located with ISSI 2015, attracted more than 70 participants and six full paper contributions, showing a large interest in these topics in the community. The goal of this second edition of the workshop is to continue to encourage the collaboration between these two domains and to answer questions like: How can we enhance author network analysis and Bibliometrics using data obtained by text analytics? What insights can NLP provide on the structure of scientific writing, on citation networks, and on in-text citation analysis?
See the proceedings of the first edition of the workshop: http://ceur-ws.org/Vol-1384/.
=== Submission Guidelines ===
All papers must be original and not simultaneously submitted to another journal or conference.
All submissions must be written in English up to 6 pages and following the ISSI 2017 Template for full papers.
Submissions require registration as a user in the EasyChair system. Please go to <https://easychair.org/conferences/?conf=clbib2017> to register.
All submissions will be reviewed by at least two independent reviewers. Please be aware of the fact that at least one author per paper needs to register for the workshop and attend the workshop to present the work.
The accepted papers will be invited for a publication in a special issue of the Journal Frontiers in Research Metrics and Analytics <http://journal.frontiersin.org/journal/research-metrics-and-analytics>.
=== Workshop Topics ===
Topics include (but are not limited to) the following:
- Linguistic modeling and discourse analysis for scientific texts
- User interfaces, text representations and visualizations
- Structure of scientific articles (discourse / argumentative / rhetorical / social)
- Scientific corpora and paper standards
- Act of citations, in-text citations and Content Citation Analysis
- Co-citation and bibliographic coupling
- Text enhanced bibliographic coupling
- Terminology extraction
- Text mining and information extraction
- Scientific information retrieval
- Ontological descriptions of scientific content
- Knowledge extraction
The workshop will involve research project reports, system demonstrations and a panel discussion on the perspectives for the development of new text analytics approaches for bibliometrics.
=== Organizing committee ===
Iana Atanassova, Centre Tesnière - CRIT, Université de Bourgogne Franche-Comté, France
Marc Bertin, ELICO, Université Claude Bernard Lyon 1, France
Philipp Mayr, GESIS - Leibniz Institute for the Social Sciences, Germany
=== Programme Committee (to be confirmed) ===
Lee Giles (College of Information Sciences and Technology, Pennsylvania State University, USA)
Yves Gingras (CIRST, Université du Québec à Montréal, Canada)
Vincent Lariviere (EBSI, Université de Montréal, Canada)
Stefanie Haustein (EBSI, Université de Montréal, Canada)
Timothy Bowman (EBSI, Université de Montréal, Canada)
Cassidy R. Sugimoto (School of Informatics and Computing, Indiana University, USA)
Sylviane Cardey (Centre Tesniere - CRIT, Université de Bourgogne Franche-Comte, France)
Sherifa Boukacem (Elico, Université Claude Bernard Lyon 1, France)
Guillaume Cabanac (IRIT, Université de Toulouse, France)
Beatrice Milard (Université de Toulouse 2, France)
Ruslan Mitkov (University of Wolverhampton, England)
Constantin Orasan (University of Wolverhampton, England)
Tomi Kauppinen (Aalto University, Finland)
Roman Kern (Know-Center, Austria)
Angelo Di Iorio (Department of Computer Science and Engineering, University of Bologna, Italy)
=== Contact ===
All questions about submissions should be emailed to iana.atanassova (at) univ-fcomte.fr.
Dr. Philipp Mayr
GESIS - Leibniz Institute for the Social Sciences
Unter Sachsenhausen 6-8, D-50667 Köln, Germany
Tel: + 49 (0) 221 / 476 94 -533
Email: philipp.mayr at gesis.org<mailto:philipp.mayr at gesis.org>
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