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Purpose The purpose of the study is to explore if and how text mining methodology can be applied to investigate and analyze large amounts of academic papers. Methodology / Approach The study uses probabilistic topic modeling as method to perform exploratory data analysis on QMOD-ICQSS proceedings. Findings The findings give reason for further exploration of text mining and probabilistic topic modeling as a relevant method to extract information from large amounts of academic papers. The generated topic models serve as a foundation for other researchers to conduct more detailed analysis of the QMOD-ICQSS proceedings depending on the specific area of interest. Research Limitations The study was limited to the use of one software and modeling technique, a multi-track approach would have strengthened the results. Originality There seems not to exist any other text mining study that has been conducted on conferenced proceedings in general nor on QMOD-ICQSS proceedings specifically. Keywords Text Mining, Probabilistic Topic Modeling, Quality Movement, Total Quality Management, QMOD-ICQSS Paper type Research paper |
