Scholarly Research and Publications Over Time: Identifying Trends for an Open Access Journal by Applying Data-Mining Methods

Autor: Judith Schoßböck, Nina Rizun, Anneke Zuiderwijk, Noella Edelmann
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Septentrio Conference Series; No 4 (2020): The 15th Munin Conference on Scholarly Publishing 2020
ISSN: 2387-3086
DOI: 10.7557/scs.2020.4
Popis: See RECORDING (starts at 00:22:38). Journal editors of all types of scholarly publishing face various issues and choices in order to support the development of the journals they lead and manage. One particular issue is what strategic choices can be made to enhance the visibility, accessibility and impact of research published in their journal as much as possible. Another issue is how to provide potential authors of the journal with useful information that will support them with their publication choice. The objective of this study is twofold. First, it aims to provide an approach that can be used by journal editors to identify topical trends in scholarly-led publishing in their journal, in order to better inform potential future authors of the journal. In particular, we analyse what factors impact the trends and research cooperations over time with a view to research topics and thematic streams, regions, and the research methods employed by authors in previous publications. Second, this study derives potential factors responsible for specific journal developments, such as the influence of open access principles, guest editors, indexing systems, research cooperations and topics addressed by the journal on the visibility, accessibility and impact of the journal. To attain the above-mentioned objectives, this study uses data-mining methods to analyse all the articles published in one journal in particular, namely the (diamond(/platinum) open access e-journal for eDemocracy and Open Government called “JeDEM” (see www.jedem.org) that was set up in 2009. The methods used are a combination of data mining (such as the text mining, topic modelling, k-means clustering, social network analysis and community detection) of journal content and metadata with further qualitative interpretation of results from a journal management perspective. The qualitative part confirms or challenges the data analysis part, particularly with view to potential outliers or developments that cannot be explained by quantitative data analysis alone. Combined with internal knowledge from the journal management perspective, we are able to provide an interpretative component and are to relate the trends emerging from the data to strategic decisions or publication details. The results are as follows. First, our study shows the most prominent research topics of the studied journal, and their evolution over time. Second, the research methods employed by authors publishing in the journal are identified, as well as the research cooperations established through publications in the journal. Third, the crucial factors such as indexing, communication with the community and changes in journal management are derived. The developed approach was found to be useful to gain insights concerning journal developments, and might also be used by editors of other journals to determine their journal strategy. For example, using data mining methods, editors can analyse whether the topics included in their call for papers match the topics on which the journal publishes or whether it needs adaptations to better manage the expectations of future authors of the journal. Thus, our results might also help authors with their publication choices and tracing the evolutionary stages of the studying scientific problem. Finally, our study derives further research questions aiming at achieving a critical assessment of scholarly developments within the publishing sphere over time.
Databáze: OpenAIRE
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