Metaverse adoption rates remain low despite growing commercial and research interest in the concept of metaverse. Previous studies on the drivers and barriers of metaverse adoption predominantly focused on adult users or university students and are mainly conducted in European, North American, and Gulf-area countries. Given that 80% of metaverse users are under the age of 16, the present study investigates children and youth in Asian countries. We employed the “Unified Theory of Acceptance and Use of Technology 2” and “Innovation Resistance Theory” as frameworks to conduct semi-structured interviews with 40 individuals aged between 13 and 24 years old. The purpose was to understand their metaverse usage habits and the perceived drivers and barriers of adoption. The findings revealed that entertainment, socialization, and education were prevalent activities. Adoption was primarily driven by perceived usefulness, facilitating conditions, and social factors, while major barriers included perceived risks and value concerns.

Pair programming is a collaborative activity that enhances students' computational thinking (CT) skills. Analyzing students' interactions during pair programming provides valuable insights into effective learning. However, interpreting classroom dialogues is a challenging and complex task. Due to the simultaneous interaction between interlocutors and other ambient noise in collaborative learning contexts, previous work heavily relied on manual transcription and coding, which is labor-intensive and time-consuming. Recent advancements in speech and language processing offer promising opportunities to automate and scale up dialogue analysis. Besides, previous work mainly focused on task-related interactions, with little attention to social interactions. To address these gaps, we conducted a four-week CT course with 26 fifth-grade primary school students. We recorded their discussions, transcribed them with speech processing models, and developed a coding scheme and applied LLMs for annotation. Our AI-driven pipeline effectively analyzed classroom recordings with high accuracy and efficiency. After identifying the dialogue patterns, we investigated the relationships between these patterns and CT performance. Four clusters of dialogue patterns have been identified: Inquiry, Constructive Collaboration, Disengagement, and Disputation. We observed that Inquiry and Constructive Collaboration patterns were positively related to students' CT skills, while Disengagement and Disputation patterns were associated with lower CT performance. This study contributes to the understanding of how dialogue patterns relate to CT performance and provides implications for both research and educational practice in CT learning.

Abstract Deepfakes are a potential source of disinformation and the ability to detect them is imperative. While research focused on algorithmic detection methods, there is little work conducted on how people identify deepfakes. This research attempts to fill this gap. Using semi‐structured interviews, participants were asked to identify real and deepfake videos and explain how their decisions were made. Three categories of deepfake identification strategies emerged: the use of surface video and audio cues, processing of the messages conveyed in the video, and the searching of external sources. Participants often used multiple strategies within each category. However, identification challenges occurred due to participants' preconceived notions of deepfake characteristics and the message embodied in the video. This work contributes to research by shifting the focus from the algorithmic detection of deepfakes to human‐oriented strategies. Practically, the findings provide guidance on how people can identify deepfakes, which can also form the basis for the development of educational materials.

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.

Given the increasing popularity of gamified crowdsourcing, the study reported here involved examining determinants of users' continuance intention toward crowdsourcing games, both with longitudinal data and reference to a revised unified theory of acceptance and use of technology (UTAUT). At three time points, data were collected from an online survey about playing crowdsourcing games. Time-lagged regression, cross-temporal correlation, and structural equation modeling were performed to examine determinants of the acceptance of crowdsourcing games. Results indicate that the revised UTAUT2 is applicable to explaining the acceptance of crowdsourcing games. Not only did effort expectancy, hedonic motivation, and social influence directly affect users’ continuance intention toward crowdsourcing games, but time-based variations also emerged in users’ perceptions and acceptance of the games and in how their perceptions affect their acceptance. The findings answer the call for a context-specific acceptance model and the identification of factors of adopting gamification.

Within the human computation paradigm, gamification is increasingly gaining interest. This is because an enjoyable experience generated by game features can be a powerful approach to attract participants. Although potentially useful, little research has been conducted into understanding the effectiveness of gamification in human computation. In this experimental study, we operationalized effectiveness as perceived engagement and user acceptance and examined it by comparing the performance of a gamified human computation system against a non-gamified version. We also investigate the determinants of acceptance and how their effects differ between these two systems. Analysis of our data found that participants experienced more engagement and showed higher behavioral intentions toward the gamified system. Moreover, perceived output quality and perceived engagement were significant determinants of acceptance of the gamified system. In contrast, determinants for acceptance of the non-gamified system were perceived output quality and perceived usability.

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.

With the increasing importance of social media in people's lives, more mobile applications have incorporated features to support social networking activities. These applications enable communication between people, using features such as chatting and blogging. There is, however, little consideration of the collaboration between people during information seeking. Mobile applications should support the seeking, sharing, confirming, and validating of information systematically to help users complete their tasks and fulfill their information needs. To support information seeking, especially collaboratively as a group, there is a need to understand people's social interaction behavior. Using tourism as a domain, we conducted a diary study to look into tourists' social interaction during information seeking. Further, based on the diary study findings and current research, we describe a set of triggers that lead to collaboration for each step in the information‐seeking process. Here we present the social collaboration patterns between tourists and the people around them. Further, based on a diary study and current research, we describe a set of triggers that lead to collaboration for each step in the BIG6 information‐seeking process.

Guided by literature on “fatigue” from within the domains of clinical and occupational studies, the present article seeks to define the phenomenon termed social network fatigue in the context of one of the popular uses of social networks, namely, to stay socially connected. This is achieved through an identification of the antecedents and effects of experiences that contribute to negative emotions or to a reduction in interest in using social networks with the help of a mixed‐methods study. Five generic antecedents and varying effects of these antecedents on individual user activities have been identified. Fatigue experiences could result from social dynamics or social interactions of the members of the community, content made available on social networks, unwanted changes to the platform that hosts the network, self‐detected immersive tendencies of the users themselves, or a natural maturing of the life cycle of the community to which the user belongs. The intensity of the fatigue experience varies along a continuum ranging from a mild or transient experience to a more severe experience, which may eventually result in the user's decision to quit the environment that causes stress. Thus, users were found to take short rest breaks from the environment, moderate their activities downward, or suspend their social network activities altogether as a result of fatigue experiences.

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.

The development of numerous information sharing platforms have led to the emergence of multimedia user-generated content. With the prevalence of networking mobile devices and Global Positioning System (GPS) functionality, these contents could also be tagged with their location (geo-tagged) and visualised on a map through a geospatial information system. This in turn raises new challenges to manage the information retrieval process due to the potentially large amounts of data presented on the map. In this paper, we present a spatial clustering approach to enhance the searching feature of MobiTOP, a geospatial annotation system. The technique, which is a modification of DBSCAN (Density based spatial clustering applications with noise) coupled with our ranking schemes, is compared against other techniques. The evaluation results suggest the viability of our approach, and implications are also discussed.

We investigate the usability of MobiTOP (Mobile Tagging of Objects and People), a mobile location-based annotation system. MobiTOP allows users to annotate real world locations with both multimedia and textual content and concurrently, share the annotations among its users. Equipped with a new interface as well as additional functionality such as clustering of annotations and advanced search and filtering options, a usability evaluation of MobiTOP was conducted in the context of a travel companion for tourists. The results suggested the potential of the system in terms of functionality for mobile content sharing. Participants agree that the features in MobiTOP are generally usable as a content sharing tool. Implications and future work are also reported in this paper.

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.

The tourism sector is one of the world's most important economic sectors, and the increasing popularity of mobile devices presents an opportunity for developing innovative mobile tourism services. While there is much research on the development and evaluation of mobile tourism applications and on generalized tourist needs and behavior, there is little work on understanding the types of services tourists desire. Using a factor analytic approach, this study aims to determine what mobile services are important to the tourists. This was first done via a survey of the literature and confirmed by a focus group. The set of candidate tourism services was then translated into a questionnaire for the purposes of quantitatively determining their appropriateness for mobile tourism. Thereafter, exploratory and confirmatory factor analytic procedures were performed. Our findings show that tourists appear to favor basic services such as those providing information about transportation, accommodation and food, while advanced ones such as context-aware services and trip planning were deemed comparatively less desirable. Practical and theoretical implications of our findings are also discussed.

We introduce MobiTOP (mobile tagging of objects and people), a map-based application which allows users to contribute and share geo-referenced multimedia annotations via mobile devices. An important feature of MobiTOP is that annotations are hierarchical, allowing annotations to be annotated to an arbitrary depth. MobiTOPpsilas interface was designed using a participatory design methodology to ensure that the user interface meets the needs of potential users. In an evaluation, a group of student-teachers involved in a geographical field study were tasked to collaboratively identify rock formations using the MobiTOP system. The students who were in the field were guided by their lab counterparts on the tasks required to identify the rock formations. Results suggest the potential of the MobiTOP system for information sharing.

Abstract Web citations have become common in scholarly publications as the amount of online literature increases. Yet, such links are not persistent and many decay over time, causing accessibility problems for readers. The present study investigates the link decay phenomenon in three leading information science journals. Articles spanning a period of 7 years (1997–2003) were downloaded, and their links were extracted. From these, a measure of link decay, the half‐life, was computed to be approximately 5 years, which compares favorably against other disciplines (1.4–4.8 years). The study also investigated types of link accessibility errors encountered as well as examined characteristics of links that may be associated with decay. It was found that approximately 31% of all citations were not accessible during the time of testing, and the majority of errors were due to missing content (HTTP Error Code 404). Citations from the edu domain were also found to have the highest failure rates of 36% when compared with other popular top‐level domains. Results indicate that link decay is a problem that cannot be ignored, and implications for journal authors and readers are discussed.

Abstract The purpose of this study was to develop a method for automatic construction of multidocument summaries of sets of research abstracts that may be retrieved by a digital library or search engine in response to a user query. Sociology dissertation abstracts were selected as the sample domain in this study. A variable‐based framework was proposed for integrating and organizing research concepts and relationships as well as research methods and contextual relations extracted from different dissertation abstracts. Based on the framework, a new summarization method was developed, which parses the discourse structure of abstracts, extracts research concepts and relationships, integrates the information across different abstracts, and organizes and presents them in a Web‐based interface. The focus of this article is on the user evaluation that was performed to assess the overall quality and usefulness of the summaries. Two types of variable‐based summaries generated using the summarization method—with or without the use of a taxonomy—were compared against a sentence‐based summary that lists only the research‐objective sentences extracted from each abstract and another sentence‐based summary generated using the MEAD system that extracts important sentences. The evaluation results indicate that the majority of sociological researchers (70%) and general users (64%) preferred the variable‐based summaries generated with the use of the taxonomy.

In order to organise and manage geospatial and georeferenced information on the Web making them convenient for searching and browsing, a digital portal known as G-Portal has been designed and implemented. Compared to other digital libraries, G-Portal is unique for several of its features. It maintains metadata resources in XML with flexible resource schemas. Logical groupings of metadata resources as projects and layers are possible to allow the entire metadata collection to be partitioned differently for users with different information needs. These metadata resources can be displayed in both the classification-based and map-based interfaces provided by G-Portal. G-Portal further incorporates both a query module and an annotation module for users to search metadata and to create additional knowledge for sharing respectively. G-Portal also includes a resource classification module that categorizes resources into one or more hierarchical category trees based on user-defined classification schemas. This paper gives an overview of the G-Portal design and implementation. The portal features will be illustrated using a collection of high school geography examination-related resources.

G-Portal is a Java-based digital library system for managing the metadata of geography related resources on the Web. In addition to providing a flexible repository subsystem to accommodate metadata of different formats using XML and XML Schemas, G-Portal organizes metadata into projects and layers, and supports an integrated and synchronized classification and map-based interfaces over the stored metadata. G-Portal also includes a classification subsystem that creates category structures and classifies metadata resources into categories based on user-specified classification schemas. Furthermore, G-Portal users can annotate resources and make their annotations available to others. In this paper, we describe the design and implementation of G-Portal and elaborate how Java is used to implement its features. G-Portal has been designed to be modular and some of the modules can be used as stand-alone tools. In this paper, we use UML notation to describe the detailed design of G-Portal and highlight some of the design decisions.