Text mining analysis of factors related to employment anxiety disorders among science and engineering students

Abstract

BackgroundIn recent years, the issue of employment anxiety disorder among science and engineering college students has become increasingly prominent. The study analyzed the relevant factors of employment anxiety disorder among science and engineering students through text mining methods.Subjects and MethodsThe study selected students from a certain university of science and engineering as the research subjects and divided them into anxiety group and non-anxiety group. Social media data was used for text mining to identify factors related to employment anxiety disorder among science and engineering students. The statistical software SPSS23.0 is used to analyze data and evaluate the correlation of factors using methods such as t-tests or correlation coefficients.ResultsBy analyzing social media texts of science and engineering students, research has identified several factors related to employment anxiety. In the anxiety group, the score of employment pressure was significantly higher than that of the non-anxiety group (M=4.58 in the anxiety group, M=3.26 in the non-anxiety group, P<0.001), Score of career uncertainty (anxiety group M=3.92, non-anxiety group M=2.95, P<0.001), competitive pressure (anxiety group M=4.27, non-anxiety group M=3.18, P<0.001), and career development opportunities (anxiety group M=2.68, non-anxiety group M=3.52, P<0.001). The results showed significant high scores in the anxiety group.ConclusionsThe research provides valuable information for universities and related institutions to develop targeted coping measures and psychological support, thereby reducing the employment anxiety disorder of science and engineering students and promoting their career development.