Presentation information

Organized Session

Organized Session » OS-2

[4H1-OS-2a] ニュースメディアのデータサイエンス(1/2)

Fri. Jun 17, 2022 10:00 AM - 11:40 AM Room H (Room H)

オーガナイザ:高野 雅典(サイバーエージェント)[現地]、小川 祐樹(立命館大学)、鈴木 貴久(津田塾大学)、園田 亜斗夢(東京大学)、高 史明(神奈川大学)、保高 隆之(NHK)

10:40 AM - 11:00 AM

[4H1-OS-2a-03] Effect of Article Diversity on retention rates in Online News Service

〇Shusuke Suganuma1, Kojiro Iizuka2, Yoshifumi Seki2, Fujio Toriumi1 (1. The University of Tokyo, 2. Gunosy Inc.)

Keywords:news, recommender system, user engagement

While the problems of filter bubbles and echo chambers caused by recommendation systems on digital platforms and the resulting risk of confusion are well understood, the impact of diverse information recommendations on user engagement has not been well analyzed. In this study, we analyzed user behavior logs of a popular news application to determine how the degree of diversity of the news provided by the application affects the user's continuous usage rate. As a result, we found that users who read homogeneous articles had a significantly lower retention rate. At the same time, it was suggested that users who prefer extremely homogeneous articles have a different behavioral pattern.

Authentication for paper PDF access

A password is required to view paper PDFs. If you are a registered participant, please log on the site from Participant Log In.
You could view the PDF with entering the PDF viewing password bellow.