New Generation Working Models With Text Mining And Topic Modeling

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.

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Publication Details

Journal
Fenerbahçe Üniversitesi Sosyal Bilimler Dergisi
Published
2025-06-30
DOI
https://doi.org/10.58620/fbujoss.1652981
Primary Topic
Computational and Text Analysis Methods
Type
article
Field-Weighted Citation Impact
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article

New Generation Working Models With Text Mining And Topic Modeling

Deniz Yıldız, Hüseyin Koçak
Fenerbahçe Üniversitesi Sosyal Bilimler Dergisi
Computational and Text Analysis Methods
article

New Generation Working Models With Text Mining And Topic Modeling

Deniz Yıldız, Hüseyin Koçak
article en

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.

Fenerbahçe Üniversitesi Sosyal Bilimler DergisiVol. 5(1)
Ordu University (TR)
Openalex Percentile: Top 78%
Computational and Text Analysis Methods
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