Abstract In social Q&A, user‐generated questions can be viewed as goal expressions shaping the responses. Several studies have identified askers' goals from questions. However, it remains unclear how questions set goals for responders. To fill this gap, this research applies goal‐framing theory. Goal‐frames influence responses by attracting responders' attention to different goals. Eight question cues are used to identify gain, hedonic and normative goal‐frames. A total of 14,599 posts are collected. To investigate the influence of goal‐frames, response networks are constructed. Results reveal that gain goal‐frames attract interactions with questions, while hedonic, and normative goal‐frames promote interactions among responses. Further, topic types influence the effects of goal‐frames. Gain goal‐frames increase interactions with questions in Science, Technology, Engineering, and Mathematics (STEM) topics while hedonic and normative goal‐frames attract interactions in non‐STEM topics. This research leverages responders' perspectives to explain responses to questions, which are influenced by the goals set up by question cues. Beyond that, our findings enrich the empirical knowledge of social Q&A topics, revealing that the influence of questions varies across STEM and non‐STEM topics because the question cues for specifying goals are different in the two topics. Our research opens new directions to investigate questions from responders' perspectives.

Analyzing and documenting human information behaviors in the context of global public health crises such as the COVID-19 pandemic are critical to informing crisis management. Drawing on the Elaboration Likelihood Model, this study investigates how three types of peripheral cues-content richness, emotional valence, and communication topic-are associated with COVID-19 information sharing on Twitter. We used computational methods, combining Latent Dirichlet Allocation topic modeling with psycholinguistic indicators obtained from the Linguistic Inquiry and Word Count dictionary to measure these concepts and built a research model to assess their effects on information sharing. Results showed that content richness was negatively associated with information sharing. Tweets with negative emotions received more user engagement, whereas tweets with positive emotions were less likely to be disseminated. Further, tweets mentioning advisories tended to receive more retweets than those mentioning support and news updates. More importantly, emotional valence moderated the relationship between communication topics and information sharing-tweets discussing news updates and support conveying positive sentiments led to more information sharing; tweets mentioning the impact of COVID-19 with negative emotions triggered more sharing. Finally, theoretical and practical implications of this study are discussed in the context of global public health communication.

Children that go missing is a major global problem, and finding them is imperative. One approach to addressing this problem is through crowdsourcing, in which large groups of people participate and contribute to the cause. Drawing from the lens of Self-Determination and Public Service Motivation theories, this study investigates the role of motivations in mobile crowdsourcing participation. First, this study identified the motivational factors behind participation on a mobile crowdsourcing platform to look for missing children. Next, the study examined the direct and indirect effects of these motivational factors on crowdsourcing participation. Data was collected from 264 respondents from an online survey. Results from structural equation modelling analysis revealed the motivations to volunteer have direct effects while motivations to serve the public have significant indirect effects on mobile crowdsourcing participation. This article concludes by presenting implications, limitations and future research directions.

Crowdsourcing applications enable mass collaboration on problem solving by distributing tasks to individual users. However, the success of crowdsourcing relies on active participation of the users and hence requires an effective incentive mechanism. This study presents an application prototype which utilises mobile crowdsourcing for a nationwide automated external defibrillator (AED) database and explores gamification as the sole incentive strategy on it. Based on motivational needs identified in selfdetermination theory (SDT), we conducted a survey study of 160 participants by examining the effects of the gamified mobile crowdsourcing application against a non-gamified version. Results of regression analyses reveal that the gamification influenced how motivational factors, including perceived value, competence and relatedness, drove users' usage intention of the application.

Human computation games (HCGs) harness human intelligence through enjoyable gameplay to address computational problems that are beyond the power of computer programs but trivial for humans. With the popularity of crowdsourcing, different types of HCGs have been developed using various gameplay mechanics to attract online users to contribute outputs. Two commonly used mechanics are collaboration and competition. Yet there is little research examining whether HCGs perform better than nongame applications in terms of motivations and perceptions. Thus, this study investigates the effects of collaborative and competitive mechanics on intrinsic motivation and perceived output quality in mobile content sharing HCGs. Using a within‐subjects experiment, 160 participants were recruited from 2 local universities. The findings suggest that the nongame application was perceived to yield better quality output than both HCGs, but the latter offered a greater satisfaction of motivational needs, which may motivate individuals to continue playing them. Taken together, the present findings inform researchers and designers of HCGs that games could serve as a motivator to encourage participation. However, the usefulness of HCGs may be dependent on how one can effectively manage the entertainment–output generation duality of such games. This article concludes by presenting implications, limitations, and future research directions.

Location‐based information can now be easily accessed anytime and anywhere using mobile devices. Common ways of presenting such information include lists, maps, and augmented reality (AR). Each of these interface types has its strengths and weaknesses, but few empirical evaluations have been conducted to compare them in terms of performance and perceptions of usability. In this paper, we investigate these issues using three interface types for searching and browsing location‐based information across two task types: open and closed ended. The experimental study involved 180 participants who were issued an Android mobile phone preloaded with a specific interface and asked to perform a set of open‐ and closed‐ended tasks using both searching and browsing approaches. The results suggest that the list interface performed best across all tasks in terms of completion times, whereas the AR interface ranked second and the map interface performed worst. Participants rated the list as best across most usability constructs but the map was rated better than the AR interface, even though the latter performed better. Implications of the work are discussed.

Human computation games (HCGs) utilise human intelligence for the purpose of problem solving through games. Recently, HCGs have increased in popularity within various application areas. A proper system of describing such games is necessary in order to obtain a better understanding of the current body of work and identify new opportunities for future research directions. To date, however, there is little research conducted in understanding how such games could be classified in a systematic manner. Past classification schemes rely either on quality or entertainment aspects of these games. In order to have a deeper understanding of such games, this study argues that they should be classified via different dimensions. As a starting point, this paper reviews existing literature on HCGs and then develops a typology consisting of 12 dimensions and related strategies. This typology provides a holistic view of HCGs, and provides a common understanding of the domain among researchers and designers. The typology will help researchers to better understand the nature and consequences of HCGs, and designers better identify strengths and weaknesses of different strategies for each dimension, thus facilitating the creation of entertaining and effective HCGs.

The objective of this research is to investigate the types of problems and their associated perceived risks as well as the effects of risks perceived on frequently used information communication technologies (ICTs) by globally distributed software development teams. We focused on perceived risk in reception, understanding and action and studied two global software teams that were at different software development phases (i.e. requirements analysis versus development and maintenance). Data for this research was collected from a leading global IT consulting company and we found that instant messaging, email and teleconferencing system were frequently used by the two teams. Our results indicate that perceived risks in reception and action were encountered by members in the systems development and maintenance phase. Additionally, we also found differences on the effects of perceived risks on the use of instant messaging, email and teleconferencing system between the teams.

Applications that use games to harness human intelligence to perform various computational tasks are increasing in popularity and may be termed human computation games (HCGs). Most HCGs are collaborative in nature, requiring players to cooperate within a game to score points. Competitive versions, where players work against each other, are a more recent entrant, and have been claimed to address shortcomings of collaborative HCGs such as quality of computation. To date, however, little work has been conducted in understanding how different HCG genres influence computational performance and players' perceptions of such. In this paper we study these issues using image tagging HCGs in which users play games to generate keywords for images. Three versions were created: collaborative HCG, competitive HCG, and a control application for manual tagging. The applications were evaluated to uncover the quality of the image tags generated as well as users' perceptions. Results suggest that there is a tension between entertainment and tag quality. While participants reported liking the collaborative and competitive image tagging HCGs over the control application, those using the latter seemed to generate better quality tags. Implications of the work are discussed.

Indagator is a mobile application which incorporates multiplayer, pervasive gaming elements into content sharing. The application allows users to annotate physical locations with multimedia content (annotations), and concurrently, provide opportunities for play through creating and engaging interactive game elements, earning points, and socializing. This paper examines the motivations for accessing and viewing annotations in Indagator, and highlights the influence of introducing games to mobile content sharing applications in general. Participants used Indagator for one week and were thereafter interviewed. Results were drawn by triangulating data from the interview, server logs, and the content of the annotations accessed. Three overarching motivation categories for accessing annotations emerged from our analysis - Facts, Friends, and Fun. Further, participants generally felt that games would sustain their interest in accessing annotations in the long run. Implications of our work are also discussed.

Abstract The confluence of mobile content sharing and pervasive gaming yields new opportunities for developing novel applications on mobile devices. Yet, studies on users' attitudes and behaviors related to mobile gaming, content‐sharing, and retrieval activities (referred to simply as content sharing and gaming) have been lacking. For this reason, the objectives of this article are three‐fold. One, it introduces Indagator, an application that incorporates multiplayer, pervasive gaming elements into mobile content‐sharing activities. Two, it seeks to uncover the motivations for content sharing within a game‐based environment. Three, it aims to identify types of users who are motivated to use Indagator for content sharing. Informed by the uses and gratifications paradigm, a survey was designed and administered to 203 undergraduate and graduate students from two large universities. The findings revealed that perceived gratification factors, such as information discovery, entertainment, information quality, socialization, and relationship maintenance, demographic variables, such as basic familiarity with features of mobile communication devices, and IT‐related backgrounds were significant in predicting intention to use mobile sharing and gaming applications such as Indagator. However, age, gender, and the personal status gratification factor were nonsignificant predictors. This article concludes by presenting the implications, limitations, and future research directions.