The Impact of User Sentiment Aroused by The-Day-of-the-Week on the Recommendation Effectiveness in Microblog

Shih Yun Weng, Ping Yu Hsu, Ming Shien Cheng, Phan Anh Huy Nguyen

研究成果: 書貢獻/報告類型篇章同行評審


Microblogging has become an increasingly popular platform for users to post their views and comments online due to the ease of posting and replying. This generated an abundance of sentiment database which could be used to study the-day-of-the-week sentiment patterns of users. We adopted sentiment database to extract sentiment expressions from the posted Plurk messages to investigate whether there are sentiment fluctuations in the days of a week and if there are opportunities to use the-day-of-the-week sentiment patterns to maximize the effectiveness of sentiment-based product recommendation. The experimental results showed that users’ posts are significantly strong negative on Monday and strong positive on Friday, Saturday, and Sunday. We speculate that the recommended products with positive sentiment words were more effective during Monday and Saturday because of the approach-avoidance motivation. People would usually have negative sentiment after 5 days continuous work during Friday working hours, so that recommended products with negative sentiment words are more effective. Whereas on Friday night the positive sentiment increased after off duty, and caused the recommendation products with positive sentiment words more effective. Negative sentiment on Sunday due to the coming blue Monday may cause negative sentiment recommendations more effective.

主出版物標題Studies in Computational Intelligence
發行者Springer Verlag
出版狀態已出版 - 1 3月 2017


名字Studies in Computational Intelligence