A Review on Semantic and Syntactic Similarity Measure for Political Tweets

Authors

  • Bijal Gadhia, Prapti Trivedi, Rashmi Hirani

Keywords:

Artificial Intelligence, Machine Learning, Semantic Analysis, Social Media Mining

Abstract

In the modern era, social media has influenced virtually every public domain, including politics. These platforms enable users worldwide to share vast amounts of content, making social media a valuable resource for research and analysis. In countries like India, social media offers a convenient space for individuals to express their opinions on various issues, including political topics. Consequently, analyzing social media content has become a significant area of research.One key aspect of this analysis is measuring semantic and syntactic similarity within social media posts to understand user opinions effectively. This task becomes particularly challenging due to the use of informal and nonstandard language in short messages, such as tweets. Techniques like word embedding are employed to address this issue by capturing the contextual meaning of words. Additionally, factors such as word sequence and ambiguity play a critical role in deriving meaning from social media content.This review paper examines existing work related to measuring semantic and syntactic similarities in social media data. It also presents a comparative summary of various methods used for this purpose

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References

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Published

24.03.2024

How to Cite

Bijal Gadhia. (2024). A Review on Semantic and Syntactic Similarity Measure for Political Tweets. International Journal of Intelligent Systems and Applications in Engineering, 12(3), 4422 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/7133

Issue

Vol. 12 No. 3 (2024)

Section

Research Article

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