Do topic-dependent models improve microblog sentiment estimation

A topic-independent sentiment model is commonly used to estimate sentiment in microblogs. But for movie and product reviews, domain adaptation has been shown to improve sen-timent estimation performance. We examined whether topic-dependent models improve polarity estimation of microblogs. We considered both a model trained on Twitter tweets con-taining a target keyword and a model trained on an enlarged set of tweets containing terms related to a topic. Comparing the performance of the topic-dependent models to a topic-independent model trained on a general sample of tweets, we noted that for some topics, topic-dependent models per-formed better. We then propose a method for predicting which topics are likely to have better sentiment estimation perfor-mance when a topic-dependent sentiment model is used