ABSTRACT This paper investigates individual investor sentiment in Chinese stock message board Guba Eastmoney and its relation to the market returns and volatility. Focusing on measuring the sentiment, we propose a novel algorithm Semantic Orientation from Laplace Smoothed Normalized Pointwise Mutual Information(SO-LNPMI). We show that: (i) comparing to traditional methods, SO-LNPMI has higher accuracy and better adaptive property of probability estimate; (ii) negative sentiment is negatively correlated with market returns, whereas positive sentiment does not have any statistically significant impact on market returns; (iii) positive(negative) sentiment is negatively(positively) correlated with market volatility. Our results survive a range of robustness tests.