Does “Evaluating Journal Quality and the Association for Information Systems Senior Scholars Journal Basket…” Support the Basket with Bibliometric Measures?

We re-examine “Evaluating Journal Quality and the Association for Information Systems Senior Scholars Journal Basket…” by Lowry et al. (2013). They sought to use bibliometric methods to validate the Basket as the eight top quality journals that are “strictly speaking, IS journals” (Lowry et al., 2013, pp. 995, 997). They examined 21 journals out of 140 journals considered as possible IS journals. We also expand the sample to 73 of the 140 journals. Our sample includes a wider range of approaches to IS, although all were suggested by IS scholars in a survey by Lowry and colleagues. We also use the same sample of 21 journals in Lowry et al. with the same methods of analysis so far as possible. With the narrow sample, we replicate Lowry et al. as closely as we can, whereas with the broader sample we employ a conceptual replication. This latter replication also employs alternative methods. For example, we consider citations (a quality measure) and centrality (a relevance measure in this context) as distinct, rather than merging them as in Lowry et al. High centrality scores from the sample of 73 journals do not necessarily indicate close connections with IS. Therefore, we determine which journals are of high quality and closely connected with the Basket and with their sample. These results support the broad purpose of Lowry et al., finding a wider set of high quality and relevant journals than just MISQ and ISR, and find a wider set of relevant, top quality journals

The skewness of computer science

Computer science is a relatively young discipline combining science, engineering, and mathematics. The main flavors of computer science research involve the theoretical development of conceptual models for the different aspects of computing and the more applicative building of software artifacts and assessment of their properties. In the computer science publication culture, conferences are an important vehicle to quickly move ideas, and journals often publish deeper versions of papers already presented at conferences. These peculiarities of the discipline make computer science an original research field within the sciences, and, therefore, the assessment of classical bibliometric laws is particularly important for this field. In this paper, we study the skewness of the distribution of citations to papers published in computer science publication venues (journals and conferences). We find that the skewness in the distribution of mean citedness of different venues combines with the asymmetry in citedness of articles in each venue, resulting in a highly asymmetric citation distribution with a power law tail. Furthermore, the skewness of conference publications is more pronounced than the asymmetry of journal papers. Finally, the impact of journal papers, as measured with bibliometric indicators, largely dominates that of proceeding papers.Comment: I applied the goodness-of-fit methodology proposed in: A. Clauset, C. R. Shalizi, M. E. J. Newman. Power-law distributions in empirical data. SIAM Review 51, 661-703 (2009

A single journal study : Malaysian Journal of Computer Science

Single journal studies are reviewed and measures used in the studies are highlighted. The following quantitative measures are used to study 272 articles published in Malaysian Journal of Computer Science, (1) the article productivity of the journal from 1985 to 2007, (2) the observed and expected authorship productivity tested using Lotka's Law of author productivity, identification and listing of core authors; (3) the authorship, co-authorship pattern by authors' country of origin and institutional affiliations; (4) the subject areas of research; (5) the citation analysis of resources referenced as well as the age and half-life of citations; the journals referenced and tested for zonal distribution using Bradford's law of journal scattering; the extent of web citations; and (6) the citations received by articles published in MJCS and impact factor of the journal based on information obtained from Google Scholar, the level of author and journal self-citation