Characterizing and predicting the cross-app behavior in mobile search

Abstract

PurposeThis paper aims to explore the users' cross-app behavior characteristics in mobile search and to predict users' cross-app behavior using multi-dimensional information.Design/methodology/approachThis paper presents a longitudinal user experiment in 15 days. This paper recruited 30 participants and collected their mobile phone log data in the whole experiment. The structured diary method was also used to collect contextual information in mobile search.FindingsThis study focused on the users' cross-app behavior in mobile search and described cross-app behavior's basic characteristics. Usage of communication app and tool apps could trigger more cross-app behavior in mobile search. The method of cross-app behavior prediction in the mobile search was proposed. Collecting users' more contextual information, such as search tasks, search motivation and other environmental information, can effectively improve the prediction accuracy of cross-app behavior in mobile search.Practical implicationsThe future research on cross-app behavior prediction should focus on context information in mobile search. Better prediction of cross-app behavior can reduce the users' interaction burden.Originality/valueThis paper contributes to research into cross-app behavior, especially in the mobile search research domain.

Does visual attention help? Towards better understanding and predicting users’ good abandonment behavior in mobile search

“…Users with long snippets on mobile devices exhibited longer search times with no better search accuracy for informational tasks (Kim et al, 2017). On mobile devices, users will also choose to change apps while searching, presenting a more diverse search behavior (Liang, 2022).…”

“…, 2017). On mobile devices, users will also choose to change apps while searching, presenting a more diverse search behavior (Liang, 2022).…”

Transitions in daily search tactics: during the cross-app interaction search process

“…Previously, the platform of mobile search research mainly focused on mobile search engines (Liang, 2022). With the diverse development of mobile search environments, cross-APP interaction has become an important way of mobile search alongside search engines (McGee, 2014).…”

“…For instance, the characteristics of the new tactic need to be clarified and explicit enough. Mobile users tend to provide feedback based on search results, such as Likes and Comments (Kim and Yang, 2017;Wang et al, 2019), as well as the presence of multiple social apps, where users will engage in socialization during the search process and so forth (Liang and Zang, 2020;Liang, 2021).…”