Knowledge extraction about brand image using information retrieval method

Abstract

The purpose of this study is to extract characteristic words as the information of expression pertaining to a brand’s image, from the language resources that have accumulated by users on Twitter. In this study, we analyzed Twitter data related to brands extracted the characteristic representations by using Okapi BM25, which is a ranking function that has been recently introduced in information retrieval. To confirm the validity of our approach, we conduct comparative experiments on the Twitter data of several Japanese automobile brands using BM25 and TF-IDF. By using the BM25, the extraction of keywords that are meaningful and buried in high frequency terms can be expected.