<abstract xmlns="http://www.w3.org/1999/xhtml"><sec><h3>Purpose</h3><p>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.</p></sec><sec><h3>Design/methodology/approach</h3><p>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.</p></sec><sec><h3>Findings</h3><p>Through application and verification in the domain of perovskite solar cells research, this method proves to be effective.</p></sec><sec><h3>Research limitations</h3><p>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.</p></sec><sec><h3>Practical implications</h3><p>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.</p></sec><sec><h3>Originality/value</h3><p>This text analysis approach has not been reported before.</p></sec></abstract>

PurposeWe 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/approachWe 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.FindingsThrough application and verification in the domain of perovskite solar cells research, this method proves to be effective.Research limitationsA 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 implicationsWe 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/valueThis text analysis approach has not been reported before.

Topic Evolution and Emerging Topic Analysis Based on Open Source Software

Information and Archives Management of University of Chinese Academy of Sciences

Journal of Data and Information Science

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Topic Evolution and Emerging Topic Analysis Based on Open Source Software"}

PurposeWe present an analytical, open source and flexible natural language processing and text mining method for topic evolution, emerging topic detection and...

Topic Evolution and Emerging Topic Analysis Based on Open Source Software

Article Category: Research Paper

Online veröffentlicht: 07. Sept. 2020

Seitenbereich: 126 - 136

Eingereicht: 23. Jan. 2020

Akzeptiert: 20. Juli 2020

DOI: https://doi.org/10.2478/jdis-2020-0033

Schlüsselwörter
Topic evolution, Emerging topics, Text mining, Thesaurus, VOSviewer

© 2020 Xiang Shen et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Topic Evolution and Emerging Topic Analysis Based on Open Source Software

Article Category: Research Paper

Online veröffentlicht: 07. Sept. 2020

Seitenbereich: 126 - 136

Eingereicht: 23. Jan. 2020

Akzeptiert: 20. Juli 2020

DOI: https://doi.org/10.2478/jdis-2020-0033

SchlüsselwörterTopic evolution, Emerging topics, Text mining, Thesaurus, VOSviewer

© 2020 Xiang Shen et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
Topic evolution, Emerging topics, Text mining, Thesaurus, VOSviewer