Abstract

Stock prediction is consider one of the most popular tasks in the last decade. Stock prediction can be achieved through the analysis of the numerical values (e.g., open price and close price) or the sentiment analysis of social media text (e.g., tweets). In this paper, we will discuss the several approach of stock prediction using sentiment analysis methods. These methods can be classified into four main categories, namely, machine learning, lexicon, graph, and hybrid based methods. Besides, we discussed the basic tools used to help in the task of sentiment analysis such as Term Frequency Inverse Document Frequency and word2cev algorithms.

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