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Abstract

Characteristics of the Journal of the American Society for Information Science and Technology and 76 other journals listed in the InformationSystems category of the Journal Citation Reports-Science edition 2009 were analyzed. Besides reporting usual bibliographic indicators, we investigated the human cornerstone of any peer-reviewed journal: its editorial board. Demographic data about the 2,846 gatekeepers serving in information systems (IS) editorial boards were collected. We discuss various scientometric indicators supported by descriptive statistics. Our findings reflect the great variety of IS journals in terms of research output, author communities, editorial boards, and gatekeeper demographics (e.g., diversity in gender and location), seniority, authority, and degree of involvement in editorial boards. We believe that these results may help the general public and scholars (e.g., readers, authors, journal gatekeepers, policy makers) to revise and increase their knowledge of scholarly communication in the IS field. The EB_IS_2009 dataset supporting this scientometric study is released as online supplementary material to this article to foster further research on editorial boards.

Source

Journal of the American Society for Information Science and Technology. 63(2012) no.5, S.977-996

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Abstract

Many papers have appeared recently assessing the effects of using tables and graphs in scientific publications. In this brief communication, we assess some of the methodological difficulties that have arisen in this context. These difficulties encompass issues of data availability, suitability of indicators, nature and purpose of tables and graphs, and the role of supplementary information.

Source

Journal of the Association for Information Science and Technology. 66(2015) no.2, S.408-427

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Abstract

People taking part in argumentative debates through collective annotations face a highly cognitive task when trying to estimate the group's global opinion. In order to reduce this effort, we propose in this paper to model such debates prior to evaluating their social validation. Computing the degree of global confirmation (or refutation) enables the identification of consensual (or controversial) debates. Readers as well as prominent information systems may thus benefit from this information. The accuracy of the social validation measure was tested through an online study conducted with 121 participants. We compared their human perception of consensus in argumentative debates with the results of the three proposed social validation algorithms. Their efficiency in synthesizing opinions was demonstrated by the fact that they achieved an accuracy of up to 84%.

Source

Journal of the American Society for Information Science and Technology. 61(2010) no.2, S.271-287

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Abstract

Peer review supports scientific conferences in selecting high-quality papers for publication. Referees are expected to evaluate submissions equitably according to objective criteria (e.g., originality of the contribution, soundness of the theory, validity of the experiments). We argue that the submission date of papers is a subjective factor playing a role in the way they are evaluated. Indeed, program committee (PC) chairs and referees process submission lists that are usually sorted by paperIDs. This order conveys chronological information, as papers are numbered sequentially upon reception. We show that order effects lead to unconscious favoring of early-submitted papers to the detriment of later-submitted papers. Our point is supported by a study of 42 peer-reviewed conferences in Computer Science showing a decrease in the number of bids placed on submissions with higher paperIDs. It is advised to counterbalance order effects during the bidding phase of peer review by promoting the submissions with fewer bids to potential referees. This manipulation intends to better share bids out among submissions in order to attract qualified referees for all submissions. This would secure reviews from confident referees, who are keen on voicing sharp opinions and recommendations (acceptance or rejection) about submissions. This work contributes to the integrity of peer review, which is mandatory to maintain public trust in science.

Source

Journal of the American Society for Information Science and Technology. 64(2013) no.2, S.405-415

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Abstract

In 2014 leading publishers withdrew more than 120 nonsensical publications automatically generated with the SCIgen program. Casual observations suggested that similar problematic papers are still published and sold, without follow-up retractions. No systematic screening has been performed and the prevalence of such nonsensical publications in the scientific literature is unknown. Our contribution is 2-fold. First, we designed a detector that combs the scientific literature for grammar-based computer-generated papers. Applied to SCIgen, it has a 83.6% precision. Second, we performed a scientometric study of the 243 detected SCIgen-papers from 19 publishers. We estimate the prevalence of SCIgen-papers to be 75 per million papers in Information and Computing Sciences. Only 19% of the 243 problematic papers were dealt with: formal retraction (12) or silent removal (34). Publishers still serve and sometimes sell the remaining 197 papers without any caveat. We found evidence of citation manipulation via edited SCIgen bibliographies. This work reveals metric gaming up to the point of absurdity: fraudsters publish nonsensical algorithmically generated papers featuring genuine references. It stresses the need to screen papers for nonsense before peer-review and chase citation manipulation in published papers. Overall, this is yet another illustration of the harmful effects of the pressure to publish or perish.

Source

Journal of the Association for Information Science and Technology. 72(2021) no.12, S.1461-1476

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Source

Journal of the American Society for Information Science and Technology. 64(2013) no.10, S.2182-2186

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Source

Journal of the Association for Information Science and Technology. 65(2014) no.4, S.812-820

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Source

Journal of the Association for Information Science and Technology. 67(2016) no.4, S.874-884