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Mobile Search Behaviors: An In-Depth Analysis Based on Contexts, Apps, and Devices (en Inglés)
Dan Wu
(Autor)
·
Shaobo H. Liang
(Autor)
·
Springer
· Tapa Blanda
Mobile Search Behaviors: An In-Depth Analysis Based on Contexts, Apps, and Devices (en Inglés) - Wu, Dan ; Liang, Shaobo H.
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Origen: Estados Unidos
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Reseña del libro "Mobile Search Behaviors: An In-Depth Analysis Based on Contexts, Apps, and Devices (en Inglés)"
With the rapid development of mobile Internet and smart personal devices in recent years, mobile search has gradually emerged as a key method with which users seek online information. In addition, cross-device search also has been regarded recently as an important research topic. As more mobile applications (APPs) integrate search functions, a user's mobile search behavior on different APPs becomes more significant. This book provides a systematic review of current mobile search analysis and studies user mobile search behavior from several perspectives, including mobile search context, APP usage, and different devices. Two different user experiments to collect user behavior data were conducted. Then, through the data from user mobile phone usage logs in natural settings, we analyze the mobile search strategies employed and offer a context-based mobile search task collection, which then can be used to evaluate the mobile search engine. In addition, we combine mobile search with APP usage to give more in-depth analysis, such as APP transition in mobile search and follow-up actions triggered by mobile search. The study, combining the mobile search with APP usage, can contribute to the interaction design of APPs, such as the search recommendation and APP recommendation. Addressing the phenomenon of users owning more smart devices today than ever before, we focus on user cross device search behavior. We model the information preparation behavior and information resumption behavior in cross-device search and evaluate the search performance in cross-device search. Research on mobile search behaviors across different devices can help to understand online user information behavior comprehensively and help users resume their search tasks on different devices.
