Skip to main content

Tools and Techniques for Text Mining and Visualization

  • 376 Accesses

Abstract

This chapter covers 19 popular open-access text mining and visualization tools, including R, Topic-Modeling-Tool, RapidMiner, WEKA, Orange, Voyant Tools, Gephi, Tableau Public, Infogram, and Microsoft Power BI, among others, with their applications, pros, and cons. As there are many text mining and visualization tools available, we covered only those open-source tools that have a simple GUI so that information professionals who are new to these tools can learn to use and implement them in their daily work.

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-030-85085-2_10
  • Chapter length: 24 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   64.99
Price excludes VAT (USA)
  • ISBN: 978-3-030-85085-2
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   84.99
Price excludes VAT (USA)

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Yang Q, Zhang X, Du X, Bielefield A, Liu Y (2016) Current market demand for core competencies of librarianship—a text mining study of American Library Association’s Advertisements from 2009 through 2014. Appl Sci 6(2):48. https://doi.org/10.3390/app6020048

    CrossRef  Google Scholar 

  2. Lee J, Lapira E, Bagheri B, Kao H (2013) Recent advances and trends in predictive manufacturing systems in big data environment. Manuf Lett 1(1):38–41. https://doi.org/10.1016/j.mfglet.2013.09.005

    CrossRef  Google Scholar 

  3. Noh Y (2015) Imagining Library 4.0: creating a model for future libraries. J Acad Librariansh 41(6):786–797. https://doi.org/10.1016/j.acalib.2015.08.020

    CrossRef  Google Scholar 

  4. Abinaya G, Winster SG (2014) Event identification in social media through latent dirichlet allocation and named entity recognition. In: Proceedings of IEEE international conference on computer communication and systems ICCCS14, pp 142–146. https://doi.org/10.1109/ICCCS.2014.7068182

  5. Google Code Archive. Long-term storage for Google Code Project Hosting. https://code.google.com/archive/p/topic-modeling-tool/wikis/TopicModelingTool.wiki. Accessed 12 Aug 2020

  6. Nguyen G, Dlugolinsky S, Bobák M, Tran V, López García Á, Heredia I, Malík P, Hluchý L (2019) Machine learning and deep learning frameworks and libraries for large-scale data mining: a survey. Artif Intell Rev 52:77–124. https://doi.org/10.1007/s10462-018-09679-z

    CrossRef  Google Scholar 

  7. Sci2 Team (2009) Science of Science (Sci2) Tool. Indiana University and SciTech Strategies. https://sci2.cns.iu.edu

  8. LancsBox Manual (2020) http://corpora.lancs.ac.uk/lancsbox/docs/pdf/LancsBox_5.1_manual.pdf. Accessed 2 Apr 2021

  9. Gephi (2017) https://gephi.org/users/download/. Accessed 12 Aug 2020

  10. Power BI Tutorial (2021) https://data-flair.training/blogs/power-bi-tutorial/. Accessed 2 Apr 2021

  11. RAWGraphs (2021) https://rawgraphs.io/. Accessed 2 Apr 2021

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and Permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Verify currency and authenticity via CrossMark

Cite this chapter

Lamba, M., Madhusudhan, M. (2022). Tools and Techniques for Text Mining and Visualization. In: Text Mining for Information Professionals. Springer, Cham. https://doi.org/10.1007/978-3-030-85085-2_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-85085-2_10

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-85084-5

  • Online ISBN: 978-3-030-85085-2

  • eBook Packages: Computer ScienceComputer Science (R0)