Topic Modelling and Artificial Intelligence Based Method Using Online Employee Assessments to Analyze Job Satisfaction

Abstract

In this study, the performance of the proposed sample selection method was evaluated on some basic classifiers by conducting a basic literature review on the use of topic modelling methods by considering the online evaluations of the employees in order to determine and analyze the job satisfaction factors. In addition, the effectiveness of different representation structures are evaluated in order to represent the data sets effectively and the main results are obtained regarding the use of classification ensemble methods in the field of text mining. In this work it was emphasized that machine learning methods can achieve high performance in classification and work effectively and scalably with large data sets. The dataset used in this study was obtained from www.kaggle.com. A total of 67529 comments collected from people working at Google, Amazon, Netflix, Facebook, Apple and Microsoft were evaluated. Within the scope of this study, a text mining and artificial intelligence-based method will be developed and a solution will be brought to text mining with artificial intelligence methods.