Search results

This paper aims to explore the users' cross-app behavior characteristics in mobile search and to predict users' cross-app behavior using multi-dimensional information.

This 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.

This 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.

The 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.

This paper contributes to research into cross-app behavior, especially in the mobile search research domain.

Cross-app interactive search has become the new normal, but the characteristics of their tactic transitions are still unclear. This study investigated the transitions of daily search tactics during the cross-app interaction search process.

In total, 204 young participants' impressive cross-app search experiences in real daily situations were collected. The search tactics and tactic transition sequences in their search process were obtained by open coding. Statistical analysis and sequence analysis were used to analyze the frequently applied tactics, the frequency and probability of tactic transitions and the tactic transition sequences representing characteristics of tactic transitions occurring at the beginning, middle and ending phases. 

Creating the search statement (Creat), evaluating search results (EvalR), evaluating an individual item (EvalI) and keeping a record (Rec) were the most frequently applied tactics. The frequency and probability of transitions differed significantly between different tactic types. “Creat? EvalR? EvalI? Rec” is the typical path; Initiate the search in various ways and modifying the search statement were highlighted at the beginning phase; iteratively creating the search statement is highlighted in the middle phase; Moreover, utilization and feedback of information are highlighted at the ending phase. 

The present study shed new light on tactic transitions in the cross-app interactive environment to explore information search behaviour. The findings of this work provide targeted suggestions for optimizing APP query, browsing and monitoring systems.

Good abandonment behavior refers to users obtaining direct answers via search engine results pages (SERPs) without clicking any search result, which occurs commonly in mobile search. This study aims to better understand users' good abandonment behavior and perception, and then construct a good abandonment prediction model for mobile search with improved performance.

In this study, an in situ user mobile search experiment (N = 43) and a crowdsourcing survey (N = 1,379) were conducted. Good abandonment behavior was analyzed from a quantitative perspective, exploring users' search behavior characteristics from four aspects: session and query, SERPs, gestures and eye-tracking data.

Users show less engagement with SERPs in good abandonment, spending less time and using fewer gestures, and they pay more visual attention to answer-like results. It was also found that good abandonment behavior is often related to users' perceived difficulty of the searching tasks and trustworthiness in the search engine. A good abandonment prediction model in mobile search was constructed with a high accuracy (97.14%).

This study is the first to explore eye-tracking characteristics of users' good abandonment behavior in mobile search, and to explore users' perception of their good abandonment behavior. Visual attention features are introduced into good abandonment prediction in mobile search for the first time and proved to be important predictors in the proposed model.

Social media celebrities are getting popular in promotions, and more people have experienced social media to receive information on diet and health tips. This research presents a study showing how social media can influence young people's diet behavior through collaboration with social media celebrities.

Through recruiting on various social media and online education forums, this research recruited 196 young Hongkongers to participate in an online survey developed based on the AIDA (Action, Interest, Desire, Attention) marketing communication model on how youths access diet information from social media celebrities in Hong Kong.

Hong Kong youths consume diet information from social media celebrities through instant messaging systems, social networking sites and online videos, and, in particular, information on food calories and nutrition. However, sponsorship from vendors would decrease their desire to agree with the messages from social media celebrities. After receiving this information, some participants would follow tips and guides from social media celebrities. However, they seldom share such information. Interestingly, males are more willing to follow these tips and guides.

First, this study fills the gap of prior research, which did not study much on how social media celebrities contribute to diet promotion to youths in Asia. Second, through the AIDA Model, this study shows how social media can affect the awareness and accessibility of diet information by young Hongkongers, followed by initiating their interest in this topic and retrieving more relevant information. Furthermore, the authors further understand their desire to follow and improve their behavior as promoted by social media influencers and how they practice such behavior. Based on these findings, health-related brands could consider using social media influencers helping to promote their products and services, and these brands could further use social media to secure customer engagement.

As voice search has progressively become a new way of information acquisition and human–computer interaction, this paper aims to explore the users' voice search behavior in human–vehicle interaction.

This study employed mixed research methods, including questionnaires and interviews. A total of 151 Amazon MTurk volunteers were recruited to complete a questionnaire based on their most recent and impressive voice search experience. After the questionnaire, this paper conducted an online interview with the participants.

This paper studied users' voice search behavior characteristics in the context of the human–vehicle interaction and analyzed the voice search content, search need, search motivation and user satisfaction. In addition, this paper studied the barriers and suggestions for voice search in human–vehicle interaction through a content analysis of the interviews.

This paper's analysis of users' barriers and suggestions has a specific reference value for optimizing the voice search interaction system and improving the service.

This study is exploratory research that seeks to identify users' voice search needs and tasks and investigate voice search satisfaction in human–vehicle interaction context.

In a world where different communication technologies support social connection, managing unavailability is as important as, if not more important than, managing availability. The need to manage unavailability becomes increasingly critical when users employ several communication tools to interact with various ties. A person's availability information disclosure may depend on different social relationships and the technologies used by the person. The study contributes to the literature by drawing on privacy management theory to investigate how users practice availability management and use its deceptive form, which is sometimes called a butler lie, with various ties across different messaging applications (apps) as part of their online privacy. Relevant factors in mediated communication, including facework, common ground, and interpersonal trust, are included in the developed model.

The authors conducted an online survey (n = 475) to explore the relationship between one's contact with different interactants (significant others, family members, close friends, acquaintances, groups of friends, and groups of acquaintances) and one's practice of availability management and use of butler lies with these interactants at different size levels on various messaging apps.

Factors such as facework, privacy related to technology, and privacy related to social relationships affect the practice of availability management and the use of butler lies. Notably, butler lies are used most frequently with acquaintances and groups of acquaintances and least frequently with significant others. Moreover, the practice of availability management and the use of butler lies are negatively moderated by people's conversational grounding and trust.

The study examined the practice of cross-app availability management with diverse social ties on mobile technologies, which is a socio-informatic practice that is widely adopted in the contemporary digital landscape but on which limited scientific and theoretic research has been conducted. No research has directly investigated users' availability management across multiple apps from a relational perspective. Building on the theoretical framework of privacy management, the paper aims to bridge the gap in the relevant literature. The results of this study can serve as a reference for library professionals to develop information literacy programs according to users' availability management needs. The results also provide insights to system designers for developing messaging tools.

The purpose of this study is to review and synthesize the literature on in-app advertising, identify gaps and propose future research directions.

The authors use a systematic literature review (SLR) approach, following the PRISMA guidelines, to investigate the current state of research in in-app advertising. The study uses 44 shortlisted articles from the Scopus and Web of Science databases. Using the Theory-Context-Characteristics-Methodology (TCCM) framework, the authors analyze the gaps in theory, context, characteristics and methods.

Using thematic analysis, the authors identify five main themes in the in-app advertising literature, namely, ad platform optimization; mobile app user psychology and behavior; ad effectiveness; ad fraud; and security, privacy and other user concerns. The findings show the need for empirical research, with a strong theoretical foundation in emerging ad formats of in-app advertising, user behavior and buy-side of in-app advertising.

This is a maiden study to conduct a domain-based SLR in the emerging field of in-app advertising using the TCCM framework. The authors highlight the key differences between in-app advertising and mobile web advertising. The authors propose theories in the advertising field that could be used in future empirical studies of in-app advertising.

El propósito de esta investigación es revisar y sintetizar la literatura sobre la publicidad en Apps, identificar lagunas y proponer futuras direcciones de investigación.

Utilizamos un enfoque de revisión sistemática de la literatura, siguiendo las directrices PRISMA, para investigar el estado actual de la investigación en publicidad en aplicaciones. El estudio utiliza 44 artículos preseleccionados de las bases de datos Scopus y Web of Science (WoS). Utilizando el marco Teoría-Contexto-Características-Metodología (TCCM), analizamos las lagunas en teoría, contexto, características y métodos.

Mediante un análisis temático, identificamos cinco temas principales en la literatura sobre publicidad en aplicaciones, a saber: optimización de plataformas publicitarias; psicología y comportamiento de los usuarios de aplicaciones móviles; eficacia publicitaria; fraude publicitario; seguridad, privacidad y otras preocupaciones de los usuarios. Nuestros hallazgos muestran la necesidad de investigación empírica, con una sólida base teórica en los formatos publicitarios emergentes de la publicidad en Apps, el comportamiento del usuario y el buy-side de la publicidad en Apps.

Se trata de un estudio pionero para realizar una revisión sistemática de la literatura basada en el dominio en el campo emergente de la publicidad en Apps utilizando el marco TCCM. Destacamos las principales diferencias entre la publicidad en aplicaciones y la publicidad en la web para móviles. Proponemos teorías en el campo de la publicidad que podrían utilizarse en futuros estudios empíricos sobre la publicidad en Apps.

本研究旨在回顾和总结有关应用内广告的文献, 找出差距并提出未来的研究方向。

我们采用系统性文献综述方法, 遵循 PRISMA 指南, 调查应用内广告的研究现状。研究使用了 Scopus 和 Web of Science (WoS) 数据库中的 44 篇入围文章。利用理论-背景-特征-方法（TCCM）框架, 我们分析了理论、背景、特征和方法方面的差距。

通过主题分析, 我们确定了应用内广告文献的五大主题, 即广告平台优化; 移动应用用户心理和行为; 广告效果; 广告欺诈; 安全、隐私和其他用户关注点。我们的研究结果表明, 有必要在应用内广告的新兴广告形式、用户行为和应用内广告买方等方面开展实证研究, 并奠定坚实的理论基础。

这是一项首次使用 TCCM 框架对新兴的应用内广告领域进行基于领域的系统性文献综述的研究。我们强调了应用内广告与移动网络广告的主要区别。我们提出了广告领域的理论, 可用于未来的应用内广告实证研究。

Fire management professionals are using smartphone applications to communicate information about wildland fires. The purpose of this paper is to examine English language wildland fire apps available to the general public to learn what information these apps contain and whether they match what are considered characteristics of well-designed apps.

Content analysis of global app markets and other directories revealed ten relevant apps. Two coders installed the apps on identical smartphones and proceeded to review the apps’ content, features, and design characteristics.

Results reveal that the ten English language wildland fire apps on the global app markets fall into three groups: apps that show nearby fires, emergency plan creation apps, and apps that inform on preparedness, response, and recovery. Strengths of these apps include that most load quickly on devices, they offer real-time contextual information, they can be used even when a device is offline, are easy to navigate, and do not utilize processor-intensive animation. Weaknesses include the fact that many lack a search engine, they do not explain how they protect sensitive user data, and they fail to reveal who authors of content are as well as when content was created or modified.

Few studies have classified, analyzed content, or assessed the design of wildland fire apps. This study reveals that critical issues app designers should address include ensuring that apps contain privacy policies and disclaimers that app information is not supposed to replace live human advice.