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A Cooperative Binary-Clustering Framework Based on Majority Voting for Twitter Sentiment Analysis
2020
IEEE Access
Twitter sentiment analysis is a challenging problem in natural language processing. For this purpose, supervised learning techniques have mostly been employed, which require labeled data for training. However, it is very time consuming to label datasets of large size. To address this issue, unsupervised learning techniques such as clustering can be used. In this study, we explore the possibility of using hierarchical clustering for twitter sentiment analysis. Three hierarchical-clustering
doi:10.1109/access.2020.2983859
fatcat:yazthauwr5fzvifbwmq74jrsqu