Analysis of User Dwell Time on Non-News Pages
March 01, 2019 Β· Declared Dead Β· π 2018 IEEE International Conference on Big Data (Big Data)
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Authors
Ryosuke Homma, Keiichi Soejima, Mitsuo Yoshida, Kyoji Umemura
arXiv ID
1903.00213
Category
cs.HC: Human-Computer Interaction
Citations
2
Venue
2018 IEEE International Conference on Big Data (Big Data)
Last Checked
4 months ago
Abstract
There is dwell time as one of the indicators of user's behavior, and this indicates how long a user looked at a page. Dwell time is especially useful in fields where user ratings are important, such as search engines, recommender systems, and advertisements are important. Despite the importance of this index, however, its characteristics are not well known. In this paper, we analyze the dwell times of various websites by desktop and mobile devices using data of one year. Our aim is to clarify the characteristics of dwell time on non-news websites in order to discover which features are effective for predicting the dwell time. In this analysis, we focus on device types, access times, behavior on the website, and scroll depth. The results indicated that the number of sessions decreased as the dwell time increased, for both desktop and mobile devices. We also found that hour and month greatly affected the dwell time, but day of the week had little effect. Moreover, we discovered that inside and click users tended to have longer dwell times than outside and non-click users. However, we can not find a relationship between dwell time and scroll depth. This is because even if a user browsed the bottom of the page, the user might not necessarily have read the entire page.
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