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Big Text advantages and challenges: classification perspective

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Abstract

Big Text, i.e., large repositories of textual data, is a part of Big Data. In total, 80–85 % of Big Text comes in unstructured form, with significant contribution from social media. In this position paper, we discuss Big Text advantages and challenges in respect to text classification. We propose a new approach to performance evaluation of classification algorithms when they applied to Big Text, namely, using corpora comparison in the result evaluation. We also discuss a significant increase in texts with comprehensive information and challenges Big Text methods face in analysis of such texts.

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Notes

  1. Message from the Director, Institute for Big Data Analytics, https://bigdata.cs.dal.ca/about.

  2. http://m.crosstalkonline.org/issues/20/179/.

  3. https://ca.linkedin.com/.

  4. http://news.nationalpost.com/news/canada/ontario-firms-social-media-tracking-software-linked-to-racial-profiling-by-u-s-police, retrieved Jan 10, 2017.

  5. https://wordnet.princeton.edu/.

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  1. School of Epidemiology and Public Health, 308E-600 Peter Morand Cres, Ottawa, ON, K1G 5Z3, Canada

    Marina Sokolova

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Sokolova, M. Big Text advantages and challenges: classification perspective. Int J Data Sci Anal 5, 1–10 (2018). https://doi.org/10.1007/s41060-017-0087-5

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