According to popularization of many SNS such as Twitter, enterprise users and some other people want to reach interested users more efficiently. However, it is difficult to detect more deep interests of the users without considering the users' behavior. In this study, I focus on a characteristic behavior of the users on Twitter, called retweet by followers. By taking followers' tweet history, a method constructing analytic models based on temporal patterns of term evaluation indices is described in this paper. The method combines ordinary used characteristic term extraction and a temporal pattern extraction of the terms usages. In the experiment, both of the characteristic terms in the retweeted text and the followers' tweet history is shown on the three major e-commerce accounts in Japan. Based on the results, some temporal patterns of the term importance indices are also shown to discuss the feasibility for predicting the retweet behavior of the followers.
IPSJ SIG Notes. ICS 2015 (11), 1-5, 2015-02-23
Information Processing Society of Japan (IPSJ)