Journal of the Association for Information Science and Technology最新文献

Throughout history, tattoos have served as a means of expressing identity, culture, and preserving information. Beyond their visual appeal, tattoos continue to be used in the modern world as a way for individuals to showcase their identity, honor and remember others, and mark significant events. In this paper, we explore the connection between tattoos and life transitions from an informational perspective. We view tattoos and the act of tattooing as a complex process that involves cognitive, physical, and emotional interactions with information on both an individual and societal level. The information experience approach aligns with this holistic and multifaceted nature of interacting with information, and we have employed this approach to structure our study. The study is based on interviews with 23 participants in Aotearoa New Zealand and highlights how tattoos serve as forms of information and mediums for comprehending and navigating life transitions. The findings reveal the role of tattoos as initiators, enablers, and resolvers of transitions, and explain how transition is experienced through tattoos. This study contributes to the understanding of tattoos as informational transitions and provides insights into their role in addressing the dissonance experienced in life transitions.

This chapter examines the contours of the religious and spiritual information experiences subfield through a review and content analysis of selected contributions from the past two decades in both information science and related fields. The research question that guides this review is: How have spirituality and religion been conceptualized in information science? Our focus has been on the LIS literature along with the fields of information behavior/practice/literacy, as well as related fields such as human–computer interaction (HCI), media and digital studies, religious studies (including sociology and anthropology of religion or religious tourism). Our aim was to highlight the ways in which the information science literature has contributed to advancing these conversations (using a collections/service/user experience or practice lens), but also how the discussions around the sacred, lived religion, contemplation, conversion or techno-spiritual practices (to name a few) have provided insights into information phenomena and processes. We also discuss the evolution of, and practices associated with, social media and digital practices as well as a discussion of representation (or the lack thereof) of less mainstream religious and spiritual traditions in the literature reviewed. We end with suggestions for future research directions.

Clarivate's Web of Science (WoS) and Elsevier's Scopus have been for decades the main sources of bibliometric information. Although highly curated, these closed, proprietary databases are largely biased toward English-language publications, underestimating the use of other languages in research dissemination. Launched in 2022, OpenAlex promised comprehensive, inclusive, and open-source research information. While already in use by scholars and research institutions, the quality of its metadata is currently still being assessed. This paper contributes to this literature by assessing the completeness and accuracy of OpenAlex's metadata related to language, through a comparison with WoS, as well as an in-depth manual validation of a sample of 6836 articles. Results show that OpenAlex exhibits a far more balanced linguistic coverage than WoS. However, language metadata are not always accurate, which leads OpenAlex to overestimate the place of English while underestimating that of other languages. If used critically, OpenAlex can provide comprehensive and representative analyses of languages used for scholarly publishing, but more work is needed at infrastructural level to ensure the quality of metadata on language.

Fake news on social media spreads faster and has become a major societal concern, prompting numerous publications and knowledge sharing among researchers. This research aims to understand the shifting nature of fake news by investigating the citation relationships between significant publications using key route main path analysis (MPA). The process involves generating keywords, collecting and selecting relevant data, and conducting MPA on fake news in social media. The study analyzes 4.057 publications from 2010 to 2023, identifying 27 influential works shaping the knowledge diffusion in fake news research. Findings reveal two main phases: understanding fake news consumption patterns and analyzing its dissemination and detection mechanisms. Through multiple-global MPA, five research trends are identified: health misinformation, fact-checking, sharing behavior, fake news recognition, and physiological interventions. The study shows a continuous rise in publications and citations, with current trends focusing on health-related misinformation. This analysis offers insights into the development and diffusion of fake news topics on social media, emphasizing the importance of historical development in guiding future research by uncovering current trends. Highlighting the historical progression of research provides valuable context, enabling a more nuanced understanding of the field.

This review examines the role of open citations in fostering transparency, reproducibility, and accessibility in scholarly communication. Through a critical synthesis of diverse sources—articles, proceedings, presentations, datasets, and blog posts—it explores the motivations behind citing, the evolving meanings of citations, and key milestones in the open citation movement. Particular attention is given to initiatives like OpenCitations and the Initiative for Open Citations (I4OC), highlighting their contributions to advancing open scholarship. Key findings indicate that open citations democratize research by providing free access to citation data, improving discoverability, and facilitating the creation of public citation graphs. Technological advancements, such as advanced data models and reference mining tools, have significantly contributed to the management and utilization of citation data. Despite these benefits, challenges such as ensuring data quality and standardization, addressing structural inequalities in citation networks, and achieving universal publisher adoption persist. The study concludes with recommendations for future efforts, emphasizing policy advocacy, technological innovation, global collaboration, and educational initiatives to promote the widespread adoption and effective use of open citations. These strategies aim to make the “frozen footprints” of scholarly communication accessible to all, fostering a more equitable and transparent scientific landscape.

We argue that advances in large language models (LLMs) and generative Artificial Intelligence (AI) will diminish the value of Wikipedia, due to a withdrawal by human content producers, who will withhold their efforts, perceiving less need for their efforts and increased “AI competition.” We believe the greatest threat to Wikipedia stems from the fact that Wikipedia is a user-generated product, relying on the “selfish altruism” of its human contributors. Contributors who reduce their contribution efforts as AI pervades the platform, will thus leave Wikipedia increasingly dependent on additional AI activity. This, combined with a dynamic where readership creates authorship and readers being disintermediated, will inevitably cause a vicious cycle leading to a staling of the content and diminishing value of this venerable knowledge resource.

This brief communication presents a novel adaptation of common bibliometric measures to provide a quantitative assessment of an artist's music catalog that incorporates both impact and productivity. Data from Billboard's weekly Hot 100™ music charts are used to rank the all-time greatest artists. Since the sorted data are increasing in value—that is, a number 1 hit is best—a transformation is applied to provide a convex, monotonically decreasing curve. Furthermore, since conventional bibliometrics result in several artists with identical measures, metrics inspired by the multidimensional $��h�$- and $��g�$-indices are used to rank the artists. We find that this approach provides a simple, yet unbiased, approach for ranking the all-time greatest music artists.

When undertaking complex search scenarios, the underlying information need cannot be satisfied by finding a single optimal resource; instead, searchers need to engage in exploratory search processes to find multiple resources by iteratively revising and reformulation their queries. This process of query refinement is particularly challenging when using a mobile device, where typing is difficult. Furthermore, in mobile search contexts interruptions can lead to searchers losing track of what they were doing. To address these challenges, we designed a public digital library search interface for mobile devices that includes two novel features: drag-and-drop query refinement and query history visualization. To assess the value of this interface compared to a typical baseline, we conducted a controlled laboratory study with 32 participants that included pursuing complex search scenarios, being interrupted in the midst of the search, and resuming the search after the interruption. While participants took more time, they generated longer queries and reported positive subjective opinions about the usability of the exploratory search and task resumption features, along with a greater increase in certainty. These findings show the value of leveraging new touch-based interaction mechanisms within mobile search contexts, and the benefits that visualization can bring to supporting search task resumption.

Prior research in human–computer interaction suggests that system-level clarifications are necessary for understanding user intent and communicating effectively with the user. Such clarifications or explanations could contain the system's abstract knowledge of the search or a functional description of the search process (queries and information sources employed). While these interactions may aid the user and the agent in better understanding each other, very few studies have explored the influence of such clarifications on the users' search experience. This research examines whether and how system-level clarifications (or explanations) affect the user experience when searching through spoken dialogues. We analyzed user satisfaction and preferences in systems with and without explicit clarifications in a within-subjects Wizard-of-Oz user study. We recruited 25 participants and collected user–system interaction data for 50 search sessions. The user feedback was collected using pre- and post-task surveys and exit interviews. Statistical and qualitative analysis of user responses yielded some interesting findings. While Wilcoxon Signed Rank Test found that using explicit system-level clarifications had no positive influence on the user's search experience, the overall search experience degraded with system clarifications (Z = −2.066, p = 0.04). The user interview data provided valuable insights into how and when clarifications should be offered to the user.

The study explored college students' use of generative artificial intelligence (GenAI) tools, such as ChatGPT, for academic tasks and their perceptions and behaviors in assessing the credibility of GenAI-generated information. Semistructured interviews were conducted with 25 college students in the United States. Interview transcripts were analyzed using the qualitative content analysis method. The study identified various types of academic tasks for which students used ChatGPT, including writing, programming, and learning. Guided by two models of credibility assessment Hilligoss and Rieh (2008); Metzger (2007), six factors influencing students' motivation and ability to assess the credibility of GenAI-generated information were identified (e.g., task salience, social pressure). We also identified 9 constructs (e.g., refinedness, explainability), 5 heuristics (e.g., inter- and intrasystem consistency heuristics), and 10 cues (e.g., version and tone) used by students to assess the credibility of GenAI-generated information. This study provides theoretical and empirical findings regarding students' use of GenAI tools in the academic context and credibility evaluation of the system outputs using rich, qualitative interview data.