Incidence of predatory journals in computer science literature

Authors : Simona Ibba, Filippo Eros Pani, John Gregory Stockton, Giulio Barabino, Michele Marchesi, Danilo Tigano

Purpose

One of the main tasks of a researcher is to properly communicate the results he obtained. The choice of the journal in which to publish the work is therefore very important. However, not all journals have suitable characteristics for a correct dissemination of scientific knowledge.

Some publishers turn out to be unreliable and, against a payment, they publish whatever researchers propose. The authors call “predatory journals” these untrustworthy journals.

The purpose of this paper is to analyse the incidence of predatory journals in computer science literature and present a tool that was developed for this purpose.

Design/methodology/approach

The authors focused their attention on editors, universities and publishers that are involved in this kind of publishing process. The starting point of their research is the list of scholarly open-access publishers and open-access stand-alone journals created by Jeffrey Beall.

Specifically, they analysed the presence of predatory journals in the search results obtained from Google Scholar in the engineering and computer science fields. They also studied the change over time of such incidence in the articles published between 2011 and 2015.

Findings

The analysis shows that the phenomenon of predatory journals somehow decreased in 2015, probably due to a greater awareness of the risks related to the reputation of the authors.

Originality/value

We focused on computer science field, using a specific sample of queries. We developed a software to automatically make queries to the search engine, and to detect predatory journals, using Beall’s list.

URL : Incidence of predatory journals in computer science literature

DOI : https://doi.org/10.1108/LR-12-2016-0108

What do computer scientists tweet? Analyzing the link-sharing practice on Twitter

Authors : Marco Schmitt, Robert Jäschke

Twitter communication has permeated every sphere of society. To highlight and share small pieces of information with possibly vast audiences or small circles of the interested has some value in almost any aspect of social life.

But what is the value exactly for a scientific field? We perform a comprehensive study of computer scientists using Twitter and their tweeting behavior concerning the sharing of web links.

Discerning the domains, hosts and individual web pages being tweeted and the differences between computer scientists and a Twitter sample enables us to look in depth at the Twitter-based information sharing practices of a scientific community.

Additionally, we aim at providing a deeper understanding of the role and impact of altmetrics in computer science and give a glance at the publications mentioned on Twitter that are most relevant for the computer science community.

Our results show a link sharing culture that concentrates more heavily on public and professional quality information than the Twitter sample does. The results also show a broad variety in linked sources and especially in linked publications with some publications clearly related to community-specific interests of computer scientists, while others with a strong relation to attention mechanisms in social media.

This refers to the observation that Twitter is a hybrid form of social media between an information service and a social network service.

Overall the computer scientists’ style of usage seems to be more on the information-oriented side and to some degree also on professional usage. Therefore, altmetrics are of considerable use in analyzing computer science.

URL : What do computer scientists tweet? Analyzing the link-sharing practice on Twitter

DOI : https://doi.org/10.1371/journal.pone.0179630

The case for open computer programs Scientific…

The case for open computer programs :

« Scientific communication relies on evidence that cannot be entirely included in publications, but the rise of computational science has added a new layer of inaccessibility. Although it is now accepted that data should be made available on request, the current regulations regarding the availability of software are inconsistent. We argue that, with some exceptions, anything less than the release of source programs is intolerable for results that depend on computation. The vagaries of hardware, software and natural language will always ensure that exact reproducibility remains uncertain, but withholding code increases the chances that efforts to reproduce results will fail. »

URL : http://www.nature.com/nature/journal/v482/n7386/full/nature10836.html