IAENG Transactions on Engineering Sciences

Categorized tip information of social media based on topic detection

A. Nadamoto & Y. Hattori

Konan University, Japan

ABSTRACT: Social media such as Social network systems, blogs, and microblogs is the most popular services. Using social media, users who are members of a social media community post and exchange information that is related to personal behavior, experimentation, and their own sentiments. These information is not written in ordinary web pages, but it is sometimes important information for the users. However, it is difficult to extract such important information from social media, because so much information exists. We propose a method to extract such important information from social media. We call such information “tip information”. ...