bluuebunny/crossref_metadata_2025_split huggingface dataset:
Accessibility for Motor Disabilities in Immersive Technologies
Authors: Holmner Marlene , Meyer Anika , Ka Kwan Sui Dave , Bothma Theo , Alemneh Daniel , MacLeod John 
Published: October 2024

ABSTRACTThe rise of immersive technologies such as virtual reality (VR), augmented reality (AR), and extended reality (XR) has revolutionized experiences in industry, entertainment, and academia. However, individuals with motor disabilities face challenges in accessing these technologies due to conventional interaction methods relying on motion‐tracked controllers. This panel discussion explores the barriers faced by people with motor disabilities and the potential benefits of overcoming these challenges. It delves into innovative interaction methods, the role of immersive technologies in physical rehabilitation, and designing for diversity and inclusion. Ethical considerations in creating accessible immersive experiences, such as privacy, equity, and responsible data use, are also addressed. Future directions for accessible immersive technologies are discussed, highlighting advancements in adaptive equipment and interfaces. The panel aims to foster collaboration between technology developers, researchers, and disability advocates to ensure immersive technologies are inclusive and beneficial for all.
Researching Informational Technologies of Trust: From Blockchain to Paradata and Digital Archives
Authors: Huvila Isto , Lemieux Victoria L. , Sköld Olle , Donaldson Devan Ray 
Published: October 2024

ABSTRACTInformation science research has a long‐time interest in diverse informational means of codifying, communicating and maintaining trust as an antecedent and outcome of information, and a central constituent of information practices. While the landscape of the gatekeepers and guarantors of access to trustworthy information for a long time remained relatively stable, since the turn of the millennium, it has evolved rapidly with several new and repurposed social and digital technologies developed and repurposed for mediating and preserving trust. The purpose of this panel is to engage in exploring from theoretical, practical and empirical perspectives such technologies across the information field. The panelists present research conceptualizing, documenting, developing and describing informational technologies of mediating and preserving trust specifically addressing: 1) what different approaches to mediating and maintaining trust exist and can be identified in information science and technology research and practice; 2) how different information technologies of trust influence the understanding and conceptualisations of trust and trustworthy information; and 3) what novel insights from the current state‐of‐the‐art research can be drawn for helping practitioners to empower and put people first when interacting with informational technologies of trust in different areas of the information field, including knowledge organisation and information behaviour and practices, records management, digital preservation, and and development of information systems and services.
Queer Data
Authors: Keilty Patrick , Cifor Marika , Watson B.M. , Weibe Andrew 
Published: October 2024

ABSTRACTData is both a worldmaking and a dismantling force. This panel brings together four approaches to queer data studies. The first talk focuses on genealogies of queer data studies, providing its intellectual history and foundations. The second talk examines a historically significant moment of queer data activism during the height of the HIV/ AIDS pandemic. The third talk examines current queer metadata interventions for libraries and archives. Finally, guided by queer approaches to computational data, the fourth talk focuses on forms of identification for Indigenous queer subjects in archives.
What Does It Mean to “Misuse” Research Data?
Authors: Pasquetto Irene V , Thomer Andrea , Acker Amelia , Chtena Natascha , Desai Meera 
Published: October 2024

ABSTRACTIn this panel, we will discuss how “data misuse” is understood across different disciplines, and in particular digital curation, critical data studies, scholarly communication, and algorithmic fairness. The audience will be invited to contribute to the discussion by reporting on their own experience with data misuse, and brainstorming potential interventions to prevent misuse. Controversial reuses of open research data are emerging, including exploitation of marginalized communities, geo privacy violations, and perpetuation of harmful stereotypes. Incidents of data misuse hinder scientific progress and erode public trust, yet defining misuse remains challenging as one community's misuse might be another's best practice. The development of a shared framework to understand when, how, and why misuse of research data occurs can help science stakeholders decide when and how to release crucial research data, evaluate the potential for misuse, and tailor documentation of research data to prevent misuse. Our goal for this panel discussion is to take us a step closer to the development of such a theoretical framework for defining data misuse.
College Students' Metaphors for ChatGPT: An Exploratory Study
Authors: An Jiaxin , Bak Hyerin , Choi Wonchan , Zhang Yan , Stvilia Besiki 
Published: October 2024

ABSTRACTThe introduction of ChatGPT has sparked significant interest and presented both great opportunities and challenges to higher education. While more students are using ChatGPT, little is known about their mental models for and sensemaking of the system, including the metaphors they use to understand the system. In this exploratory study, we interviewed 25 students at three universities in the US during the summer of 2023 to identify the metaphors they use for ChatGPT. Through qualitative analysis of the interview transcripts, we found that participants commonly used metaphors to make sense of ChatGPT. They compared ChatGPT to humans and popular technologies or tools, with being the most frequently Google mentioned. These findings highlight the potential for metaphor‐based design and the development of AI literacy programs.
Recognizing Implicitly Toxic Content Based on Multiple Attention Mechanisms
Authors: Deng Shengli , Wang Fan , Wang Haowei , Cai Yunna 
Published: October 2024

ABSTRACTToxic content on social media has posed a significant threat to user experience and societal stability. In contrast to explicitly toxic content, implicitly toxic content, lacking overt toxic words, is challenging to identify through single‐text features. Therefore, this study proposes a multi‐feature fusion algorithm to recognize implicit toxic content. Firstly, we collect various features for each post, including text content, likes, comments, user information and other features. Subsequently, employing a multi‐head attention mechanism, we extract and fuse these features. Then, utilizing ensemble learning algorithms, we identify implicitly toxic content based on the fused features. Finally, we analyze the decision‐making process of the model using an interpretable algorithm and derive the most critical features and factors for identifying implicitly toxic content. The experimental results show that the proposed algorithm outperforms algorithms such as BERT, TextCNN, and XGBoost, demonstrating the advantage of multiple features over a single text feature in recognizing implicitly toxic content. In addition, this study provides insights into the decision‐making process of the model and provides more effective toxic content management strategies for social media platforms.
Can I Collaborate with You? An Investigation of Trust in Generative AI
Authors: Ding Zih‐Yan , Chiu Ming‐Hsin 
Published: October 2024

ABSTRACTThis study investigates the role of trust in human‐AI collaboration in K‐12 education, focusing on generative AI. Using a two‐factor experimental design (n = 26), we examined attitudes toward AI and creativity level as independent variables and assessed cognitive trust, affective trust, perceptions of usability, and continuance intention to use generative AI tools in text‐to‐text (ChatGPT) and text‐to‐image (Canva) tasks. The results is analyzed with two‐way ANOVA, we find that: (1) text‐to‐text human‐AI collaboration tends to foster higher emotional engagement and trust compared to text‐to‐image human‐AI collaboration; (2) perceptions of usability and continuance intention to use are slightly higher in text‐to‐text interactions, suggesting a preference for text‐based generative AI tools; (3) significant interactive effects between attitudes toward AI and creativity were observed across all measured variables, highlighting the importance of considering both factors in understanding and improving human‐AI collaboration in educational settings, contributing to research on generative AI for learning assistance.
The Obsolescence and Time Lag between Early Publications and Non‐Early Publications
Authors: Dong Huei‐Ru , Huang Mu‐Hsuan , Lo Szu‐Chia 
Published: October 2024

ABSTRACTEarly publishing, or preprints/e‐preprints, is the practice of making research available before formal publication. This research examines early and non‐early publications in Library and Information Science, focusing on trends, citation impact, obsolescence, and time lag. It reveals an upward trend in early publications, which, despite their lower quantity, have a higher citation impact. Early publications also demonstrate a longer citing half‐life, indicating their sustained relevance. Analysis of time lags reveals that about 49.25% of early publications are formally published within three months, with 75.5% published within six months, and only 5.66% taking more than a year. These findings underscore the importance of early publication in enhancing research impact and visibility.
Educational Use of AI Chatbot Responses: Exploring Situational Relevance in Higher Education
Authors: Hyun Hong Bo , Manman Luo 
Published: October 2024

ABSTRACTThis study investigates various types of situational relevance as assessed by students in the context of AI‐generated responses for educational purposes. Data were collected through interviews with four undergraduate students, and a qualitative research method was employed to analyze data. The findings reveal the specific roles of AI chatbots concerning students' tasks and types of situational relevance. The research highlights differences between system inefficiencies and students' coping behaviors in situational relevance types, providing implications for future research.
Tools for Integrating Data by Complex, Dynamic Categories
Authors: Hruschka Daniel , Cheng Yi‐Yun , Hsiao I‐Han , Bischoff Robert , Peeples Matthew , Kasi Harsha , Huang Cindy 
Published: October 2024

ABSTRACTA key challenge in conducting comparative analyses across social units, such as religions, ethnicities, or cultures, is that data on these units is often encoded in distinct and incompatible formats across diverse datasets. This can involve simple differences in the variables and values used to encode these units (e.g., Roman Catholic is V130 = 1 vs. Q98A = 2 in two different datasets) or differences in the resolutions at which units are encoded (Maya vs. Kaqchikel Maya). These disparate encodings can create substantial challenges for the efficiency and transparency of data syntheses across diverse datasets. We introduce a user‐friendly set of tools to help users translate four kinds of categories (religion, ethnicity, language, and subdistrict) across multiple, external datasets. We outline the platform's key functions and current progress, as well as long‐range goals for the platform.
People First Services: A Qualitative Study on Library Consolidations
Authors: Johnson Melissa E. , Lanford Michael 
Published: October 2024

ABSTRACTThis poster presents results from a phenomenological research study investigating the effects of a university consolidation on the affiliated libraries of three U. S. public universities. Semi‐structured interviews were conducted through purposive sampling of twelve librarians working at three different consolidated institutions within the same university system. Data was analyzed through the lens of sensemaking theory, a process where individuals attempt to construct meaning and enact their roles within an organization through their evolving experiences (Ancona, 2011; Weick, 1995), and organizational theory which provides both a theoretical and practical way of managing, understanding, analyzing, and improving organizations based on patterns of design and behavior (Daft, 2001). The use of Bolman and Deal's (1997) organizational theory, including the structural frame, the human resource frame, the political frame, and the symbolic frame, provides insight into the effects on library services and librarians' identity resulting from consolidations.
Interaction with Information in the Japanese Job‐Seeking Practice: A Study of Female College Students
Authors: Hitoshi Kamada 
Published: October 2024

ABSTRACTThis research examines how female college students interact with various types of information in the social practice of job seeking in Japan. Qualitative analysis of semi‐structured interviews with female college students reveals how they sift through abundant information during this process, which puts them under considerable pressure. Considering their prospects as women in the workplace adds another layer to the factors influencing their interaction with information during job search. Their information activities involved internal mediation between the information and experiences they gain and their own understanding of themselves regarding the goal of their job search, which can change over time. They come to terms with their results by making sense of or accepting their decisions. This study offers practical insights for designing more effective support for students.
Enhancing Accessibility in Archives of Developing Countries: Strategies for Inclusive Information Access in Pakistani Context
Authors: Khan Muhammad Tehmash , Ullah Midrar 
Published: October 2024

ABSTRACTThis study explores these challenges, focusing on language diversity, literacy levels, and technological infrastructure. Sindh's linguistic diversity, with Sindhi, Urdu, and English as primary languages, creates barriers for users not proficient in multiple languages. The need for translation services, limited by financial constraints, further complicates access. Additionally, literacy disparities between urban and rural areas hinder engagement with textual materials, necessitating educational outreach programs that require substantial investment. Technological barriers, including limited internet access and digital devices in rural areas, exacerbate these challenges. This research proposes strategies to enhance accessibility in Sindh Archives, such as multilingual cataloging, audiovisual resources, community outreach programs, mobile libraries, user‐friendly digital interfaces, collaborative partnerships, and capacity‐building initiatives. These strategies aim to promote equitable access to archival resources, enabling broader participation in research and education. By implementing these approaches, the rich cultural heritage of Sindh can be preserved and made accessible for future generations. The Sindh Archives in Karachi, with its extensive collection of historical documents, serves as a case study to illustrate the potential impact of these strategies.
The Impact of DEI Work on Retention of Librarians: A Moderated Mediation SEM Model
Authors: Kim Sunha , VanScoy Amy , Ding Weiyi , Crabtree Ayiana 
Published: October 2024

ABSTRACTThis study explores the effects of diversity, equity, and inclusion (DEI) work on retention and job satisfaction of librarians. Using existing data from the Workforce Issues in Library and Information Science 2 project, a moderated mediation Structural Equation Modeling (SEM) showed that being prepared to advocate for or serve diverse populations did not directly affect librarian retention, nor did collaborating with the community or promoting outreach and engagement with the community. However, this preparation and these job activities did affect librarians' job satisfaction, which ultimately affected their decision to stay in the profession. In addition, preparation for DEI work and opportunities to work with the community are just as important for White librarians as for Black, Indigenous, and People of Color (BIPOC) librarians. These findings have implications for library and information science education, practice, and research.
How Can Academic Librarians Support Generative AI Literacy: An Analysis of Library Guides Using the ACRL Information Literacy Framework
Authors: Ko Chun Ru , Chiu Ming‐Hsin (Phoebe) 
Published: October 2024

ABSTRACTThis poster investigates how ACRL award‐winning libraries address generative AI literacy in their libguides. Using the ACRL “Framework for Information Literacy for Higher Education,” we analyzed newly created guides from 28 libraries. We found that this framework could serve as a foundation for AI literacy. The coding scheme developed from this analysis can be used as a reference for librarians when planning instruction or creating libguides. In addition, we identified common strategies and literacy components that librarians emphasize at this stage.
AI Transparency in Academic Search Systems: An Initial Exploration
Authors: Liu Yifan , Sullivan Peter , Sinnamon Luanne 
Published: October 2024

ABSTRACTAs AI‐enhanced academic search systems become increasingly popular among researchers, investigating their AI transparency is crucial to ensure trust in the search outcomes, as well as the reliability and integrity of scholarly work. This study employs a qualitative content analysis approach to examine the websites of a sample of 10 AI‐enhanced academic search systems identified through university library guides. The assessed level of transparency varies across these systems: five provide detailed information about their mechanisms, three offer partial information, and two provide little to no information. These findings indicate that the academic community is recommending and using tools with opaque functionalities, raising concerns about research integrity, including issues of reproducibility and researcher responsibility.
Securing Repair: Examining Cybersecurity's Influence on the Right to Repair
Authors: Mann Jasvinder , Centivany Alissa 
Published: October 2024

ABSTRACTCybersecurity is a perennial concern for technology companies, consumers, and policymakers. Recently it has become a lever of opposition against the Right to Repair movement as companies and industry groups position security and reparability as antagonistic, even incompatible, interests. This paper pushes back on those claims. We use critical discourse analysis to explore two contemporary controversies at the intersection of security and repair: (1) the U.S. National Highway Transportation Safety Administration's statements concerning automotive repair in Massachusetts and (2) the memorandum of understanding between John Deere and the American Farm Bureau Federation concerning agricultural equipment repair. We find that security concerns are raised as featureless specters of harm rarely supported by concrete or compelling evidence that reparability risks security. Rather, these arguments reflect a rhetorical strategy aimed at thwarting the repair activities of consumers and independent technicians, shifting ongoing policy debates, and influencing public sentiment around the right to repair.
Examining the Impact of Brenda Dervin's Sense‐Making Methodology across Different Fields
Authors: Mooney Hannah , Agarwal Naresh Kumar 
Published: October 2024

ABSTRACTBrenda Dervin's Sense‐Making Methodology has had a significant impact on communication, information science, and other fields, with over 18,800 citations on Google Scholar. Researchers over the years, including a recent ARIST review, have studied Dervin's work. However, prior research has not analyzed a single article to see how it has been cited over the years across different fields. In this study, we examine 50 of the 1,766 articles published after the year 2000 that cited her 1983 paper. The research question investigated is, “What is the impact of Dervin's Sense Making Methodology in the twenty‐first century in fields outside of information science?” We found that sense‐making has been applied to social media, academia, and health information seeking, among other related fields. The findings should be useful to scholars interested in information science and methodology. The study also shows that information science is not a siloed field and impacts other fields.
The AI Divide in Norrland, Sweden
Authors: Sheldrick Susan , McKay Dana , Chang Shanton , Kurnia Sherah 
Published: October 2024

ABSTRACTSmall and Medium Enterprises (SMEs) in rural areas are likely to be impacted by the digital divide arising from their geographic location and size of their organizations. With the integration of Artificial Intelligence (AI) into many business processes and systems, it is important to investigate how AI will impact the digital divides, especially in light of its potential to minimalize this disadvantage. This paper presents the preliminary findings of a qualitative study investigating how SMEs in rural Norrland are impacted by AI.
Developed Countries Dominate Leading Roles in International Scientific Collaborations: Evidence from Scholars' Self‐Reported Contribution in Publications
Authors: Tian Yifan , Bu Yi 
Published: October 2024

ABSTRACTThis study investigates the inequality of roles in international scientific collaboration, revealing that scholars from developed countries dominate leadership positions. Using data from high‐impact journals, we find significant underrepresentation of scholars from developing countries who often occupy supporting roles. After controlling authors' seniority, productivity, and scientific impact, developed country scholars are still more likely to lead research teams, perhaps because of the North–South disparity in academic resource distribution.
Responsible Practices for Crowdsourced Transcription and Accessibility for Web‐based Library, Archive, and Museum Content
Authors: Van Hyning Victoria , Jordan J. Bern , Jones Mace 
Published: October 2024

ABSTRACTHundreds of Libraries, Archives, and Museums (LAMs) around the world run crowdsourced transcription projects in order to engage users with their collections. Some LAMs explicitly use crowdsourcing projects to make non‐machine‐readable images of documents, such as manuscripts, discoverable to people who are blind or have low vision. We present findings from Crowdsourced Data: Accuracy, Accessibility, Authority (CDAAA), a 3‐year Institute of Museum and Library Services (IMLS) grant project that investigates whether and how LAMs integrate crowdsourced transcriptions into their discovery systems, and whether these efforts result in accessible web‐content for blind people and those with low vision who use assistive technology to navigate the web. We share research findings as well as practical suggestions for those in charge of crowdsourcing projects, the resulting transcription data, or similar web‐based textual content such as scholarly editions. These research and practice‐oriented findings are relevant to any national or local context where inaccessible images are transcribed, and are especially timely in the US context given recent Federal rule‐making to ensure that all web and app‐based content provided by US State and local governments is accessible, including tools, resources, and content created in‐house, through contracts or by license (2024).