Typical existing algorithms for sentiment dictionary extension use patterns to construct a graph that reflects the relation between words, clustering algorithm is then applied on this graph to get positive and negative clusters.
the existing dictionaries in Chinese are insufficient, for example, the intersection rate of two popular Chinese sentiment dictionaries HowNet and NTUSD is less than 10%.