Learning Relationship between Authors' Activity and Sentiments: A case study of online medical forums
نویسندگان
چکیده
Our current work analyses relations between sentiments and activity of authors of online InVitro Fertilization forums. We focus on two types of active authors: those who start new discussions and those who post significantly more messages than other authors. By incorporating authors‟ activity information into a domain-specific lexical representation of messages, we were able to improve multi-class classification of sentiments by 9% for Support Vector Machines and by 15.3 % for Conditional Random Fields.
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