@article{article_1652981, title={New Generation Working Models With Text Mining And Topic Modeling}, journal={Fenerbahçe Üniversitesi Sosyal Bilimler Dergisi}, volume={5}, pages={1–16}, year={2025}, DOI={10.58620/fbujoss.1652981}, author={Yıldız, Deniz and Koçak, Hüseyin}, keywords={Yeni Nesil Çalışma Modelleri, Metin Madenciliği, Konu Modelleme, LDA}, abstract={This study aims to conduct topic modeling of the news on Google about new generation working models. As a working method, analyzes were performed using the topic modeling method in the RStudio program. The limitation of the research is that the news taken from the website drawn for the data set were published in 2024. Results that meet the characteristics of new generation working models were found in the biagram (binary word group) and triagram (triple word group) formed as a result of the frequency analysis. In the topic modeling analysis, distance maps of the topics and the most frequently used words for each topic were determined and the percentage weights of the topics were included. As a result, while Topics 2, 3, and 5 represent more general and similar content, Topics 1 and 4 focus on distinctly unique and specific areas. Topics 1 and 4 emphasize the themes of working hours, flexibility, and digitalization.}, number={1}, publisher={Fenerbahçe Üniversitesi}, organization={Herhangi bir kurum tarafından finansal destek alınmamıştır.}