Topic Evolution and Emerging Topic Analysis Based on Open Source Software
Article Category: Research Paper
Published Online: Sep 07, 2020
Page range: 126 - 136
Received: Jan 23, 2020
Accepted: Jul 20, 2020
DOI: https://doi.org/10.2478/jdis-2020-0033
Keywords
© 2020 Xiang Shen et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Purpose
We present an analytical, open source and flexible natural language processing and text mining method for topic evolution, emerging topic detection and research trend forecasting for all kinds of data-tagged text.
Design/methodology/approach
We make full use of the functions provided by the open source VOSviewer and Microsoft Office, including a thesaurus for data clean-up and a LOOKUP function for comparative analysis.
Findings
Through application and verification in the domain of perovskite solar cells research, this method proves to be effective.
Research limitations
A certain amount of manual data processing and a specific research domain background are required for better, more illustrative analysis results. Adequate time for analysis is also necessary.
Practical implications
We try to set up an easy, useful, and flexible interdisciplinary text analyzing procedure for researchers, especially those without solid computer programming skills or who cannot easily access complex software. This procedure can also serve as a wonderful example for teaching information literacy.
Originality/value
This text analysis approach has not been reported before.