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Author/Affiliation: Yuliana TanuliaOpen AccessArticle
7 Pages, 977 KB 
Sentiment Analysis on Twitter for Predicting Stock Exchange Movement
Abstract:
This paper is proposed to build a model by applying two methods, namely support vector machine and nonnegative matrix factorization in the process of predicting stock market movement using twitter and historical data. The stock exchange is based on the LQ 45 stock with period from August 2018 – January 2019. The features consist of…
Read More(This article belongs to Section Cybernetics in Computer Science (CCY))