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Modeling dwell time to predict click-level satisfaction

Kim, Youngho, Hassan, Ahmed, White, Ryen W., Zitouni, Imed·2014·Proceedings of the 7th ACM international conference on Web search and data mining
DOI 10.1145/2556195.2556220
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Abstract

Clicks on search results are the most widely used behavioral signals for predicting search satisfaction. Even though clicks are correlated with satisfaction, they can also be noisy. Previous work has shown that clicks are affected by position bias, caption bias, and other factors. A popular heuristic for reducing this noise is to only consider clicks with long dwell time, usually equaling or exceeding 30 seconds. The rationale is that the more time a searcher spends on a page, the more likely they are to be satisfied with its contents. However, having a single threshold value assumes that users need a fixed amount of time to be satisfied with any result click, irrespective of the page chosen. In reality, clicked pages can differ significantly. Pages have different topics, readability levels, content lengths, etc. All of these factors may affect the amount of time spent by the user on the page. In this paper, we study the effect of different page characteristics on the time needed to achieve search satisfaction. We show that the topic of the page, its length and its readability level are critical in determining the amount of dwell time needed to predict whether any click is associated with satisfaction. We propose a method to model and provide a better understanding of click dwell time. We estimate click dwell time distributions for SAT (satisfied) or DSAT (dissatisfied) clicks for different click segments and use them to derive features to train a click-level satisfaction mod…

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Metadata

Authors
Kim, Y., Hassan, A., White, R. W., & Zitouni, I.
Affiliations
  • University of Massachusetts, Amherst, MA, USA
  • Microsoft, Redmond, WA, USA
  • Microsoft, Redmond, MA, USA
Venue
Proceedings of the 7th ACM international conference on Web search and data mining
Publisher
ACM
Published
2014-02-24
Pages
193-202
DOI
10.1145/2556195.2556220
Cited by
164
References
1
Licence
www.acm.org/publications/policies/copyright_policy#Background (vor)

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CoChat. (2026). Citation check: Modeling dwell time to predict click-level satisfaction. https://app.cochat.ai/papers/10.1145/2556195.2556220
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Kim, Y., Hassan, A., White, R. W., & Zitouni, I. (2014). Modeling dwell time to predict click-level satisfaction. Proceedings of the 7th ACM international conference on Web search and data mining. https://doi.org/10.1145/2556195.2556220