Sentiment Analysis With Emojis for Social Media Using Twitter Data

Conference: The Asian Undergraduate Research Symposium (AURS10)
Title: Sentiment Analysis With Emojis for Social Media Using Twitter Data
Stream: Language, Literature and Linguistics
Presentation Type: Poster Presentation
Authors:
Pasan Kottearachchi, University of Westminster, United Kingdom
Lakshan Costa, Informatics Institute of Technology, Sri Lanka

Abstract:

Sentiment analysis is a crucial task in natural language processing that aims to determine the polarity of a given text or emoji, i.e. whether it is positive, negative, or neutral. With the increasing use of emojis in social media and instant messaging, there is a growing need for sentiment analysis of both textual and emoji data.

This conference paper would present a novel token-based approach to sentiment analysis of emoji combinations. The proposed approach leverages the sentiment of individual emoji tokens to derive the sentiment of a given emoji combination. The paper evaluates the proposed approach on a large-scale emoji dataset and demonstrates its effectiveness in accurately mapping complex emoji combinations to sentiment.

The paper provides valuable insights into the challenges of sentiment analysis of emoji data and presents a promising solution for overcoming these challenges. The findings of this research have the potential to impact various domains, including social media and instant messaging, customer sentiment analysis, brand reputation management, and event detection. The paper is of interest to researchers, practitioners, and students working in the field of sentiment analysis and NLP.

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