Domain identification for intention posts on online social media

• Main Authors: Luong, Thai Le, TRUONG, Quoc Tuan, Dang, Hai-Trieu, Phan, Xuan Hieu
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2016
• Subjects: Domain classification; Intention mining; Social media text understanding; Text classification; User intent identification; Computer Sciences; Numerical Analysis and Scientific Computing; Social Media
• Online Access: https://ink.library.smu.edu.sg/sis_research/3624; https://ink.library.smu.edu.sg/context/sis_research/article/4625/viewcontent/DomainIdentificationIntentionPosts_2016_SoICT.pdf
• Institution: Singapore Management University

Today, more and more Internet users are willing to share their feeling, activities, and even their intention about what they plan to do on online social media. We can easily see posts like "I plan to buy an apartment this year", or "We are looking for a tour for 3 people to Nha Trang" on online forums or social networks. Recognizing those user intents on online social media is really useful for targeted advertising. However fully understanding user intents is a complicated and challenging process which includes three major stages: user intent filtering, intent domain identification, and intent parsing and extraction. In this paper, we propose the use of machine learning to classify intent{holding posts into one of several categories/domains. The proposed method has been evaluated on a medium{sized collections of posts in Vietnamese, and the empirical evaluation has shown promising results with an average accuracy of 88%.