Twitter Opinion Mining using Artificial Bee Colony Clustering Method
Umang Mundhra, Anushka Priya, Vipin Rai · 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) · 2022
Technology has come a long way over the last few years, people now use the internet as their base medium for retrieving and exchanging information. As a response, ”Social Media” has been an important part of our lives. Millions of people use social media regularly to share their opinions and perceptions, which has led to the availability of extensive data. For assessing public opinion on certain issues, sentiment analysis of such data is critical. Sentiment Analysis at its core is data mining that focuses on identifying and translating feelings found on such Social Media. In our study, we will be using Twitter, which is a microblogging service that allows users to connect to their “followers”. With this particular study, we have devised a methodology, named Artificial Bee Colony with k-means clustering, to extract sentiments from tweets published on Twitter. Because of the subjective nature of tweets, swarm-based metaheuristic approaches outperform traditional techniques.