11th Annual International Conference on Industrial Engineering and Operations Management

Analytics of Response for Corporate Twitter Accounts Using Text Mining: Case of Japanese Automotive Manufacturers

Yuta Kitano, Tetsuo Yamada & Kim Tan
Publisher: IEOM Society International
0 Paper Citations
Track: Data Analytics and Big Data

Recent years, with the spread of smartphones, Twitter, one of the Social Networking Service (SNS) has become one of the sources of information for people. These new sources of information are also influencing companies’ advertising strategies, with companies also having their own Twitter accounts and using them to promote themselves. However, the companies are still searching for Twitter strategies, such as what kind of content will make a good impression on Twitter users. Therefore, the current status of corporate accounts needs to be investigated and quantitatively analyzed. The purpose of this study is to extract Retweet and LIKE and then analyze the strategy of tweeting that makes a good impression on users. Firstly, the target company’s Tweet data is extracted, and 5 Japanese automotive companies are targeted as examples of companies. Next, Twitter account data and information obtained per Tweet is analyzed by basic statistics, linear regression, and Text Mining. Finally, from the information obtained in the previous analysis, the elements that are highly correlated with RT, are extracted, and the Tweet strategy are considered.

Published in: 11th Annual International Conference on Industrial Engineering and Operations Management, Singapore, Singapore

Publisher: IEOM Society International
Date of Conference: March 7-11, 2021

ISBN: 978-1-7923-6124-1
ISSN/E-ISSN: 2169-8767