The Second Session of the ChatGPT and Gemini-Supported Bibliometric Analysis Training was Successfully Completed

The training focused on overcoming the technical barriers researchers encounter during the literature review process and integrating large datasets into a single analysis pool. Participants learned how to manage and integrate large datasets obtained from databases such as Web of Science (WoS) and Scopus for analysis. In the first phase of the training, practical information was provided on how to overcome the “500-record download limit” in the WoS database, how to seamlessly merge fragmented downloaded files, and how to prepare them for analysis. Additionally, the correct format for downloading bibliometric data from the Scopus database and how to prepare it for analysis were discussed in detail.

One of the key segments of the training was how to clean and combine different dataset structures from WoS and Scopus into a single "Master Data" file. This process enabled researchers to integrate datasets in a way that covered the entirety of the literature. By the end of the training, participants gained the competency to integrate large datasets effectively and conduct comprehensive and accurate bibliometric analyses.

We would like to extend our thanks to Assist. Prof. Adem Yurdunkulu for sharing his valuable knowledge with us and to all the university members who participated in the training.