Atıf Klasiklerinin Etkisinin Ve İlgililik Sıralamalarının Pennant Diyagramları Ile Analizi
Creators: name: Akbulut, Müge
Publisher: name: Zenodo
Year: 2016
Subjects: Information Retrieval, Bibliometrics, Pennant Diagrams, Relevance, Relevance Rankings, Impact, Tf*idf Weighting

description: Citation indexes are important authority resources for measuring the contribution of scientists and scientific publications to literature. Many studies in information retrieval are based on research aiming to develop retrieval algorithms. These studies tend to receive citations from different fields because of the interdisciplinary nature of information retrieval. Therefore, it is important to analyze the so-called “citation classics” retrospectively to find out their impact on other fields. Yet, it is not easy to do this using citation indexes, especially for relatively old papers, as traditional citation analysis tends not to reveal the full impact of a work on other studies at its time and periods that follow. In order to see the big picture it is important to study the contribution of these studies on other disciplines as well.

In this study the impact of Maron and Kuhns’ citation classic on “probabilistic retrieval” published in 1960 has been visualized using pennant diagrams that were developed on the basis of relevance theory, information retrieval and bibliometrics. We hypothesized that “The interdisciplinary relations that are unobservable with traditional citation analysis can be revealed using the pennant diagrams method”. In order to test the hypothesis works that cited Maron and Kuhns’ study between the years of 1960 and 2015 have been downloaded with their references (a total of 4,176 unique works) and graphics have been prepared by the macros written in MS Excel. Of 4,176 works, 90 were selected using convenience sampling techniques to create static and interactive pennant diagrams for further analysis.

Another important output of this study is the relevance rankings. As an alternative to the relevance rankings based on the similarity of references already used in citation indexes, relevance rankings have been created using the pennant diagrams that took into account not only items that cited the core 

(seed) paper but also citations to the items that cited the core paper. Relevance rankings based on the similarity of references and that of pennant diagrams have been compared. Findings support the hypothesis in that pennant diagrams provide information as to which papers that the core paper on probabilistic model influenced or got influenced from, directly or indirectly. Relevance ranking based on pennant diagrams revealed the impact of the core paper on information retrieval field as well as on other disciplines. Furthermore, it identified the relations between these somewhat disconnected fields, between authors, works, and journals that cannot be readily identified using traditional citation analysis. Relevance rankings using pennant diagrams seem to have been more successful than the relevance rankings based on references similarity. This study is the first such study in Turkey that uses pennant diagrams for relevance rankings.

The data used in graphs and relevance rankings are available through citation indexes (the frequencies of total citations and co-citations). Thus, alternative relevance rankings based on pennant diagrams can be offered to users. Pennant diagrams can help researchers track the relevant literature more easily as well as identify how a core work influences other works in a specific field or in other fields.