Complexity Metric for Code-Mixed Social Media Text

Authors

  • Souvick Ghosh Rutgers University, New Brunswick, NJ
  • Satanu Ghosh MAKAUT, Kolkata, WB
  • Dipankar Das Jadavpur University, Kolkata, WB

DOI:

https://doi.org/10.13053/cys-21-4-2852

Keywords:

Natural language processing, computational linguistics, human language technologies, scientometrics, code mixing, code switching, transliteration, social media text, complexity index, code mixing index

Abstract

An evaluation metric is an absolute necessity for measuring the performance of any system and complexity of any data. In this paper, we have discussed how to determine the level of complexity of code-mixed social media texts that are growing rapidly due to multilingual interference. In general, texts written in multiple languages are often hard to comprehend and analyze. At the same time, in order to meet the demands of analysis, it is also necessary to determine the complexity of a particular document or a text segment. Thus, in the present paper, we have discussed the existing metrics for determining the code-mixing complexity of a corpus, their advantages and shortcomings as well as proposed several improvements on the existing metrics. The new index better reflects the variety and complexity of a multilingual document. Also, the index can be applied to a sentence and seamlessly extended to a paragraph or an entire document. We have employed two existing code-mixedcorporatosuittherequirementsofourstudy.

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Published

2017-12-23

Issue

Vol. 21 No. 4 (2017): Advances in Human Language Technologies (Guest Editor: A. Gelbukh)

Section

Articles of the Thematic Issue

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