Paper Info
Title
Complexity Metric For Code-Mixed Social Media Text
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-mixed corpora to suit the requirements of our study.
Year
DOI
Venue
2017
10.13053/CyS-21-4-2852
COMPUTACION Y SISTEMAS
Keywords
DocType
Volume
Natural language processing, computational linguistics, human language technologies, scientometrics, code mixing, code switching, transliteration, social media text, complexity index, code mixing index
Journal
21
Issue
ISSN
Citations 
4
1405-5546
1
PageRank 
References 
Authors
0.38
0
3
Name
Order
Citations
PageRank
Souvick Ghosh1177.81
Satanu Ghosh210.38
D. Das371776.14