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Sentiment Analysis of Text Incorporating Emojis: A Machine Learning Approach
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 184 - Number 20 |
| Year of Publication: 2022 |
| Authors: Mona M. Abd Elsalam, Ahmed M. Gadallah, Hesham A. Hefny |
10.5120/ijca2022922216
|
Mona M. Abd Elsalam, Ahmed M. Gadallah, Hesham A. Hefny . Sentiment Analysis of Text Incorporating Emojis: A Machine Learning Approach. International Journal of Computer Applications. 184, 20 ( Jul 2022), 10-18. DOI=10.5120/ijca2022922216
Abstract
Nowadays, people use emojis in their text to communicate their sentiments or summarize their words. Prior artificial intelligence (AI) strategies only included the order of text, emoticons, pictures, or emoticons with text have always been disregarded, resulting in a slew of feelings being overlooked. This study proposed a calculation and technique for opinion investigation using both text and emoticon. Awell-known sentiment analysis algorithms were inspected, including rule-based and classification algorithms, to assess the effect of enhancing emoticons as extra elements to further develop the algorithm performance. Emoticons were likewise converted into relating sentiment words when con-structing features for correlation with those straightforwardly created from emoticon name words. Furthermore, considering various elements of emoticons in texts, all posts were classified in the dataset by their emoticon use and inspected the progressions in algorithm performance. Here, two methods of information were examined in joined mode with AI calculation for observing feelings from the Twitter-based Covid-19 dataset using a few highlights. Several classification techniques are used which are Random Forest, Supported Vector Machine, Gradient Boosting, K-Neighbors and Latent Dirichlet allocation (LDA). This study demonstrates that whenever emoticons are used, their related feeling rules the opinion passed on by text-based information investigation.
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