SNS감성 분석을 이용한 주가 방향성 예측: 네이버 주식토론방 데이터를 이용하여

The scope of data for understanding or predicting stock prices has been continuously widened from traditional structured format data to unstructured data. This study investigates whether commentary data collected from SNS may affect future stock prices. From “Stock Discussion Room” in Naver, we collect 20 stocks’ commentary data for six months, and test whether this data have prediction power with respect to one-hour ahead price direction and price range. Deep neural network such as LSTM and CNN methods are employed to model the predictive relationship. Among the 20 stocks, we find that future price direction can be predicted with higher than the accuracy of 50% in 13 stocks. Also, the future price range can be predicted with higher than the accuracy of 50% in 16 stocks. This study validate that the investors’ sentiment reflected in SNS community such as Naver’s “Stock Discussion Room” may affect the demand and supply of stocks, thus driving the stock prices.