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Petersohn S.,Leibniz Institute for the Social science
Education for Information | Year: 2016

Quantitative metrics in research assessment are proliferating all over the world. The demand has led to an increase in bibliometric practitioners and service providers. Their professional roles and competencies have not yet been subject to systematic study. This paper focuses on one important service provider in evaluative bibliometrics-academic librarians-and analyzes their professional competencies from a sociology of professions perspective. To this end, expert interviews with 25 British and German information professionals and several documents have been analyzed qualitatively. Academic librarians compete with other occupations for professional jurisdiction in quantitative research assessment. The main currency in this competition is their expert knowledge. Our results show that academic librarians rely strongly on the know-how gained in their academic Library and Information Science (LIS) training and develop a specific jurisdictional claim towards research assessment, consisting primarily in training, informing and empowering users to proficiently manage the task of evaluating scientific quality themselves. Based on these findings, and informed by the theoretical framework of Andrew Abbott, our conceptual proposal is to adapt formal training in bibliometrics to the various specific professional approaches prevalent in the jurisdictional competition surrounding quantitative research assessment. © 2016 IOS Press and the authors. All rights reserved.

Bosch T.,Leibniz Institute for the Social science
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2012

Designing domain ontologies from scratch is a time-consuming endeavor requiring a lot of close collaboration with domain experts. However, domain descriptions such as XML Schemas are often available in early stages of the ontology development process. For my dissertation, I propose a method to convert XML Schemas to OWL ontologies in an automatic way. The approach addresses the transformation of any XML Schema documents by using the XML Schema metamodel, which is completely represented by the XML Schema Metamodel Ontology. Automatically, all Schema declarations and definitions are converted to class axioms, which are intended to be enriched with additional domain-specific semantic information in form of domain ontologies. © 2012 Springer-Verlag Berlin Heidelberg.

Schaer P.,Leibniz Institute for the Social science
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2012

During the last three years we conducted several information retrieval evaluation series with more than 180 LIS students who made relevance assessments on the outcomes of three specific retrieval services. In this study we do not focus on the retrieval performance of our system but on the relevance assessments and the inter-assessor reliability. To quantify the agreement we apply Fleiss' Kappa and Krippendorff's Alpha. When we compare these two statistical measures on average Kappa values were 0.37 and Alpha values 0.15. We use the two agreement measures to drop too unreliable assessments from our data set. When computing the differences between the unfiltered and the filtered data set we see a root mean square error between 0.02 and 0.12. We see this as a clear indicator that disagreement affects the reliability of retrieval evaluations. We suggest not to work with unfiltered results or to clearly document the disagreement rates. © 2012 Springer-Verlag.

Mayr P.,Leibniz Institute for the Social science
CEUR Workshop Proceedings | Year: 2016

In this paper we describe a case study where researchers in the social sciences (n=19) assess topical relevance for controlled search terms, journal names and author names which have been compiled by recommender services. We call these services Search Term Recommender (STR), Journal Name Recommender (JNR) and Author Name Recommender (ANR) in this paper. The researchers in our study (practitioners, PhD students and postdocs) were asked to assess the top n preprocessed recommendations from each recommender for specific research topics which have been named by them in an interview before the experiment. Our results show clearly that the presented search term, journal name and author name recommendations are highly relevant to the researchers topic and can easily be integrated for search in Digital Libraries. The average precision for top ranked recommendations is 0.749 for author names, 0.743 for search terms and 0.728 for journal names. The relevance distribution differs largely across topics and researcher types. Practitioners seem to favor author name recommendations while postdocs have rated author name recommendations the lowest. In the experiment the small postdoc group favors journal name recommendations.

Stier S.,Leibniz Institute for the Social science
WebSci 2016 - Proceedings of the 2016 ACM Web Science Conference | Year: 2016

This article analyzes political communication by partisan elites on Twitter. Based on framing theory, it investigates whether tweets on U.S. political debates by Democratic and Republican party actors diverge with regard to their semantics. Applying computational text analysis to the most discussed political topics in 2015, the paper identifies topically varying degrees of partisan framing. © 2016 Copyright held by the owner/author(s).

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