Analysis of Literature Reviews Based on Association Rules: A Case Study

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Eminağaoğlu M., Gökşen Y., Ünal C.

4. Uluslararası Sosyal Bilimlerde Kritik Tartışmalar Kongresi, Aydın, Turkey, 22 - 24 October 2021, pp.21

  • Publication Type: Conference Paper / Summary Text
  • City: Aydın
  • Country: Turkey
  • Page Numbers: pp.21
  • Dokuz Eylül University Affiliated: Yes


The purpose of a literature review is to gain an understanding of the existing research and debates relevant to a particular topic or area of study and to present that knowledge in the form of a written document. A literature review should identify critical knowledge gaps and thus motivate researchers to close this breach. is, writing a review not only requires an examination of past research but means making a chart for research. It has been proven that literature review is essential and highly critical for the success of any scientific research. It has also been proven that a literature review should not just be a summary of each source. Instead, it requires the comparison of each source to other relevant literature on the topic, the evaluation of each of the previous studies, elaboration of each reference’s contribution to the body of knowledge, and the integration of the sources into the proposed argument. There are several methodologies and models to carry out a literature review, such as concept-centric review, author-centric review, or a mix of both, using tables to distinguish and summarize the topics, meta-studies, thematic analysis, and other qualitative and quantitative approaches. In some literature reviews, even descriptive statistics are used to summarize the common properties or concepts in the relevant studies. However, to the best of our knowledge, no data mining approach has been used in literature reviews. This study proposes a novel approach for the quantitative analysis of literature reviews with the aid of association rules. The features are decided upon and extracted from the relevant studies in a specific literature review. Then, these features are transformed into nominal attributes and a dataset that could be used for association rule mining. Apriori algorithm, which is the most common algorithm in association rule mining is applied to this dataset and the resultant rules are filtered and analyzed. This new approach has been applied to the literature survey of a published Ph.D. dissertation and some promising results have been obtained. Some of the rules obtained by this novel approach conform to the deductions and conclusions of the literature review in the Ph.D. thesis. This study shows that the use of association rules could be an effective and supportive approach for the analysis of literature reviews for social and/or natural sciences.