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Recent decades have witnessed online social media being a big-data window forquantificationally testifying conventional social theories and exploring muchdetailed human behavioral patterns. In this paper, by tracing the emoticon usein Weibo, a group of hidden "ambivalent users" are disclosed for frequentlyposting ambivalent tweets containing both positive and negative emotions.Further investigation reveals that this ambivalent expression could be a novelindicator of many unusual social behaviors. For instance, ambivalent users withthe female as the majority like to make a sound in midnights or at weekends.They mention their close friends frequently in ambivalent tweets, which attractmore replies and thus serve as a more private communication way. Ambivalentusers also respond differently to public affairs from others and demonstratemore interests in entertainment and sports events. Moreover, the sentimentshift of words adopted in ambivalent tweets is more evident than usual andexhibits a clear "negative to positive" pattern. The above observations, thoughbeing promiscuous seemingly, actually point to the self regulation of negativemood in Weibo, which could find its base from the emotion management theoriesin sociology but makes an interesting extension to the online environment.Finally, as an interesting corollary, ambivalent users are found connected withcompulsive buyers and turn out to be perfect targets for online marketing.

Emoticon-based Ambivalent Expression: A Hidden Indicator for Unusual Behaviors in Weibo