Opinion mining has gained increasing attention and shown great practical value in recent years. Existing research on opinion mining mainly focuses on the extraction of lexicon orientation and opinion targets. The explanations of opinions, which are potentially valuable for many applications, are totally ignored. To address this specific research challenge, in this paper, we propose an approach to extract the explanation of reason and/or consequence behind an opinion via learning word pairs and using causal indicators from Chinese online reviews. We also improve our word pair based method by constructing clusters of word paris. Experiments on a Chinese business review corpus show that our method is feasible and effective.