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Cursor momentum for fascination measurement

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Abstract

We present a very different cause of search engine user behaviors—fascination. It is generally identified as the initial effect of a product attribute on users’ interest and purchase intentions. Considering the fact that in most cases the cursor is driven directly by a hand to move via a mouse (or touchpad), we use the cursor movement as the critical feature to analyze the personal reaction against the fascinating search results. This paper provides a deep insight into the goal-directed cursor movement that occurs within a remarkably short period of time (<30 milliseconds), which is the interval between a user’s click-through and decision-making behaviors. Instead of the fundamentals, we focus on revealing the characteristics of the split-second cursor movement. Our empirical findings showed that a user may push or pull the mouse with a slightly greater strength when fascinated by a search result. As a result, the cursor slides toward the search result with an increased momentum. We model the momentum through a combination of translational and angular kinetic energy calculations. Based on Fitts’ law, we implement goal-directed cursor movement identification. Supported by the momentum, together with other physical features, we built different fascination-based search result reranking systems. Our experiments showed that goal-directed cursor momentum is an effective feature in detecting fascination. In particular, they show feasibility in both the personalized and cross-media cases. In addition, we detail the advantages and disadvantages of both click-through rate and cursor momentum for re-ranking search results.

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Acknowledgements

This research is supported by the National Natural Science Foundation of China (Grant Nos. 61672368, 61373097, and 61672367), the Research Foundation of the Ministry of Education and China Mobile (MCM20150602) and the Science and Technology Plan of Jiangsu (BK20151222). The authors would like to thank the anonymous reviewers for their insightful comments and suggestions.

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Authors and Affiliations

  1. College of Computer Science and Technology, Soochow University, Suzhou, 215006, China

    Yu Hong, Kai Wang, Yingying Qiu & Guodong Zhou

  2. Science and Technology on Information Systems Engineering Laboratory, Nanjing, 210007, China

    Weiyi Ge

Authors
  1. Yu Hong
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  2. Kai Wang
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  3. Weiyi Ge
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  4. Yingying Qiu
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  5. Guodong Zhou
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Corresponding author

Correspondence to Yu Hong.

Additional information

Yu Hong is an associate professor in Soochow University, China. His main research interests focuses on personal information retrieval, topic detection and tracking, discourse analysis and event extraction.

Kai Wang is an MS candidate at Soochow University, China. Her research interests include natural language processing, information extraction and information retrieval.

Weiyi Ge achieved a PhD degree in Southeast University, China. Now he serves in the Science and Technology on Information Systems Engineering Lab, CETC28. His research interests include natural language processing and big data processing.

Yingying Qiu is an MS candidate at Soochow University, China. Her research interests include natural language processing and information extraction.

Guodong Zhou is a PhD supervisor, and a professor in Soochow University, China. His main research interests focuses on natural language understanding, information extraction, statistical machine translation, machine learning.

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Hong, Y., Wang, K., Ge, W. et al. Cursor momentum for fascination measurement. Front. Comput. Sci. 13, 396–412 (2019). https://doi.org/10.1007/s11704-017-6607-6

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  • DOI: https://doi.org/10.1007/s11704-017-6607-6

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