A comparative study of genetic algorithm in sentiment analysis
Rahul Katarya, Ashima Yadav · 2018 2nd International Conference on Inventive Systems and Control (ICISC) · 2018
Due to increase in competition, social media is playing a big role in increasing the potential customers for many organizations. Sentiment analysis is an important tool for analyzing the social media. It is a popular area in the domain of Natural Language Processing which deals in identifying the sentiments, opinion, emotion, aspect, view towards a piece of text which may refer to any object or an entity. It helps the organization to analyze their market strategy so that they can improve the product quality and customer service which will foster the sales revenue of the organization. Genetic algorithms are used popularly for sentiment analysis. They are majorly used in this field for optimization and search-related problems. Moreover, various tasks are involved in sentiment analysis. This survey provides a comparative study of the role of the Genetic algorithm in sentiment analysis on the basis of accuracy. It also provides a detail view of the tasks related to sentiment analysis.