Textual Demand Analysis: Detection of Users' Wants and Needs from Opinions

This paper tackles textual demand analysis, the task of capturing what people want or need, rather than identifying what they like or dislike, on which much conventional work has focused. It exploits syntactic patterns as clues to detect previously unknown demands, and requires domaindependent knowledge to get high recall. To build such patterns we created an unsupervised pattern induction method relying on the hypothesis that there are commonly desired aspects throughout a domain corpus. Experimental results show that the proposed method detects twice to four times as many demand expressions in Japanese discussion forums compared to a baseline method.