Navigating the Sentiment Analysis Landscape: Methodologies and Use Cases in Social Media Analysis

Sentiment analysis has grown in popularity as a tool for businesses to classify customer perceptions of their goods, services, or viewpoints. However, it can also be used to locate extremist groups who promote terrorism on websites like Twitter. Using Twitter data connected to the spread of terrorism, we study and compare various algorithms for sentiment analysis in this review paper. The advantages, methodologies, and limitation of each algorithm will be covered in the paper. The benefits of integrating emoticons in the sentiment analysis process will also be emphasised. Emoticons can offer insightful data that can help increase categorization accuracy. The classification of emotions or sentiments may yield better results if emoticons are incorporated into the opinion mining process. Additionally, it is possible to track such groups by including login and location data. The overall goal of this review paper is to give a general overview of several sentiment analysis algorithms for Twitter data relevant to the spread of terrorism as well as the benefits of incorporating emoticons into the sentiment analysis process.