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Opinion QA-Pairs Generation From Indonesian Twitter

One objective of opinion mining is to provide knowledge reasoning from sentences given to the system. It requires an understanding for the meaning of each word including the out-of-vocabulary words and the relation between words in that sentence. Twitter is one of social media networking that allows users to broadcast short text message called tweets. Compared to English, Bahasa Indonesia has a different characteristic on its structure in which it has many words coming from local language that can be categorized as the out-of-vocabulary words. This paper is aimed to explain how to generate the question-answer pairs from opinion statements from Twitter in Bahasa Indonesia. Those generated question-answer pairs will be used to build a question-answer opinion corpus. The proposed approach is the transformation of a pattern-based opinion sentences, focused on the identification of objects, features of objects, and opinions of objects. The final result of this research showed the QA-pairs as a knowledge base for the question and answer opinion system with accuracy reaching 81.7%.