bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cross‐Domain Information Integration in Government: Hierarchies and Responsibilities
Authors: Zogheib Ciara , Mahetaji Kaushar 
Published: October 2024

ABSTRACTCross‐domain integration of information is increasingly identified as a priority across public sector contexts because (in theory) it enables the use of more information, including information from groups and communities historically excluded from public sector decision making. In this paper, we reject the tendency to take ‘integration’ for granted, arguing the need to position cross‐domain integration as an information practice, and conducting mixed methods thematic analysis of government strategic documents to validate the utility of this approach. We find that depending on the type of information proposed to be integrated — digital data versus the knowledge of peoples and communities — our sample of Canadian government institutions treats cross‐domain integration with differing levels of procedural rigour and detail. Reflecting ASIS&T 2024 themes of prioritizing responsibility and reflexivity in information practice, and of cultivating community partnerships through practice, not merely in name, we discuss the information hierarchies that emerge in the cross‐domain information integration in government and the associated impacts on stakeholder communities.
Are Prompts All You Need?: Chatting with ChatGPT on Disinformation Policy Understanding
Authors: Chen Haihua , Cherukuri Komala Subramanyam , Zhu Xiaohua (Awa) , Yang Shengnan 
Published: October 2024

ABSTRACTChatGPT has shown promise in assisting qualitative researchers with coding. Previous efforts have primarily focused on datasets derived from interviews and observations, leaving document analysis, another crucial data source, relatively unexplored. In this project, we address the rapidly emerging topic of disinformation regulatory policy as a pilot to investigate ChatGPT's potential for document analysis. We adapt our existing qualitative research framework, which identifies five key components of disinformation policy: context, actors, issue, instrument, and channel, to sketch out policy documents. We then designed a two‐stage experiment employing a multi‐layer workflow using a dataset with highly relevant policy documents from US federal government departments. Through iteratively developing and refining six different prompt strategies, we identified an effective few‐shot learning strategy that achieved 72.0% accuracy and a 70.8% F‐score with the optimal prompt. Our experimental process and outcomes explore the feasibility of using ChatGPT to support manual coding for policy documents and suggest a coding approach for conducting explicit document analysis through an interactive process between researchers and ChatGPT. Furthermore, our results initiate a wider debate on how to integrate human logic with ChatGPT logic, along with the evolving relationship between researchers and AI tools.
Fostering Community Dialogue through Participatory Methods: A People‐First Approach in Participatory Development Activities
Authors: Gomez Ricardo , Beltran Mauricio 
Published: October 2024

ABSTRACTThis paper introduces innovative participatory methods designed to foster community dialogue and engagement in development initiatives. We present participatory mapping, participatory photography, and two culturally grounded games, “Mayuk” and “Cachiveras,” as tools to facilitate community participation, dialogue, and reflection. Grounded in the theory of participatory action research (PAR) by Orlando Fals Borda, these methods prioritize local knowledge, foster a dialogue of knowledge between communities and researchers, and aim for social transformation through active community participation. By implementing these participatory activities, we not only engage communities in identifying resources, strengths, and opportunities but also promote a playful strategy for adults to deepen analysis and engage in critical dialogue about their culture and communication. This approach aligns with the conference theme of Putting People First, demonstrating responsibility, reflexivity, and care in the creation and evaluation of participatory development activities.
Comparative Study of GenAI (ChatGPT) vs. Human in Generating Multiple Choice Questions Based on the PIRLS Reading Assessment Framework
Authors: Lam Yu Yan , Chu Samuel Kai Wah , Ong Elsie Li Chen , Suen Winnie Wing Lam , Xu Lingran , Lam Lavender Chin Lui , Wong Scarlett Man Yu 
Published: October 2024

ABSTRACTHuman‐generated multiple‐choice questions (MCQs) are commonly used to ensure objective evaluation in education. However, generating high‐quality questions is difficult and time‐consuming. Generative artificial intelligence (GenAI) has emerged as an automated approach for question generation, but challenges remain in terms of biases and diversity in training data. This study aims to compare the quality of GenAI‐generated MCQs with humans‐created ones. In Part 1 of this study, 16 MCQs were created by humans and GenAI individually with alignment to the Progress in International Reading Literacy Study (PIRLS) assessment framework. In Part 2, the quality of MCQs generated was assessed based on the clarity, appropriateness, suitability, and alignment to PIRLS by four assessors. Wilcoxon rank sum tests were conducted to compare GenAI versus humans generated MCQs. The findings highlight GenAI's potential as it was difficult to differentiate from human created questions and offer recommendations for integrating AI technology for the future.
Beyond Navigation: Exploring Users' Contextual Information Needs and Concerns When Interacting with Mobile Map Apps
Authors: Li Jinhao , Zhao Yuxiang (Chris) , Song Shijie 
Published: October 2024

ABSTRACTMobile map applications greatly facilitate users' everyday information practices and provide them with real‐time and accurate information in different contexts. However, few studies have explored the contextual information needs of users in their interactions with mobile maps. Semi‐structured interviews with 18 participants revealed that users present diverse and rich information needs in their everyday use of map applications, and in addition to the most common information needs for situ navigation, users' contextual information needs varied. Particularly, mobile map applications are increasingly characterized by serious leisure while highlighting their utility. In addition, with the evolution of the platformization of map applications, users are also demanding more autonomy, visibility, and security. This study contributes to the literature on human‐information interaction in mobile maps and sheds light on the user experience design of mobile map applications.
Acceptability of Nudge in Digital Learning Environment
Authors: Lim Kok Khiang , Lee Chei Sian 
Published: October 2024

ABSTRACTDigital nudging is gaining traction in the educational domain to guide students' decision‐making processes and achieve desirable learning outcomes through subtle changes in the digital learning environment. From the information science perspective, these changes are realized through informational cues and human‐computer interface design to affect the influences. Studies have shown nudge effectiveness in influencing students' behaviors, but the extent to which digital nudging affects them and who is susceptible to nudges remains unclear. Although progress has been made in understanding nudge acceptability, research in the context of learning and students' characteristics, such as procrastination behavior, remains limited. To fill this gap, this study surveyed 305 university students to assess their nudge acceptability on two types of nudges: System 1, which involves automatic and intuitive processes, and System 2, which engages deliberate and reflective thinking. The results show that students, regardless of their procrastination tendencies, were receptive to nudges in supporting their learning. System 1 nudge was preferred due to its simplistic and straightforward intervention approach. The insights gained from this study contributed to the advancement of nudge research by demonstrating that students with various procrastination tendencies were receptive to nudging and guiding researchers in designing tailored nudges to maximize effectiveness.
The Cognitive Map Mechanism in Digital Reading: An Experimental Study on the Influence of Textual Representation on Cognitive Effects
Authors: Liu Yeping , Zhao Liang , Fang Qing , Song Mofan 
Published: October 2024

ABSTRACTThe Cognitive Map Mechanism explains that different textual representations influence cognitive effects by affecting how readers mentally organize and navigate information. The application of this mechanism in digital reading remains underexplored. We conducted a lab experiment(N = 148) manipulating low/medium/high textual representation through non−/micro−/combined‐annotation modes. Our aim was to clarify how the cognitive map based digital reading variations impact reading comprehension, performance calibration, and reading speed. Sufficient results showed that high‐level textual representation provides superior cognitive effects in all dimensions. It is interesting to discover that medium‐level textual representation impaired cognitive effects compared to low‐level representation. Specifically, metacognition negatively moderated the influence of textual representation level on reading speed, suggesting that texts with both micro‐annotations and graphic organizers can provide comprehensive cues and visual correlations to build cognitive map, thereby enhancing cognitive effects. Our study contributes novel insights for future research and practical implementation of cognitive‐oriented strategies in digital context.
The Shape(s) of Information Practice: Using Radial Mapping Qualitatively
Authors: McKenzie Pamela J , Hicks Alison , Bronstein Jenny , Hyldegård Jette , Ruthven Ian , Widén Gunilla 
Published: October 2024

ABSTRACTInformation practices comprise both seeking and avoidance. Although information practices scholars use qualitative and visual methods to understand seeking practices, they rarely do so to understand avoidance. This paper proposes a new visual method that supports revealing and explaining the complex interplay of seeking and avoidance in rich qualitative data. We introduce seven dimensions of information seeking and avoidance practice (intensity, granularity, engagement, control, relevance, quality, and timeliness). We conceptualize these visually as axes radiating outward from a central origin. We use Excel radar charts to depict these dimensions, allowing us to identify and characterize the shapes of information seeking and avoidance in everyday information practices. We apply our approach to two cases from published literature to show how mapping reveals the interplay between seeking and avoidance at one point in time and over time. We propose potential data collection and analysis applications of this method for information practices research.
Has OA Moved Past a Lingua Franca?
Authors: Moulaison‐Sandy Heather , Shelton Amanda 
Published: October 2024

ABSTRACTOpen access (OA) publishing has been touted as an equalizer to access. However, English has effectively attained a status of lingua franca in science, and the extent to which OA supports cross‐language dissemination and consumption of information beyond English is not well understood. This preliminary work investigates English‐language sources as referenced in OA articles across 8 world languages in the four most common subject areas of study (i.e. Medicine; Biochemistry, Genetics, and Molecular Biology; Engineering; and Social Sciences) as indexed in Scopus in 2023. Non‐English languages and language families analyzed (i.e., Chinese, Spanish, Portuguese, and Russian) consistently included references to English language sources. Further, English‐language articles strongly favored providing references to other English‐language sources, with 17 out of 20 English‐language articles exclusively containing English‐language references. Future work will extend the current investigation, while considering the affordances and disadvantages of Scopus to access non‐English OA articles.
Cybersecurity: Putting Indigenous Peoples First
Authors: Oliver Gillian , Lawrence Chris , Timbery Narissa , Lilley Spencer , Rudolph Carsten , Whitty Monica , Saha Manika 
Published: October 2024

ABSTRACTDespite rising awareness of the critical importance of Indigenous data sovereignty principles for the empowerment of Indigenous communities, there is minimal evidence of any engagement from cybersecurity policy makers or researchers to actualise these goals. This paper reports preliminary findings from the first phase of a more extensive research programme investigating cybersecurity in relation to Indigenous communities, which analysed national cybersecurity policies in Australia, New Zealand, Canada and the United States.
Social Justice and Indoctrination: Views of Faculty Accused of Bias
Authors: Oltmann Shannon , Dowell Meghan 
Published: October 2024

ABSTRACTThis study explores the discourse surrounding ideological bias in American higher education, particularly focusing on perceptions of bias against conservative viewpoints as documented by Professor Watchlist. Through interviews with individuals included on the watchlist, this research investigates the existence and nature of political bias on college campuses. The findings reveal a nuanced understanding among respondents, with many disputing the notion of systemic bias against conservative students, while also acknowledging potential bias against conservative ideas. The study highlights the complexities between academic freedom, ideological diversity, and perceptions of bias. The results contribute to ongoing debates about the role of political ideology in academia and its implications for classroom dynamics.
Stewarding Contextual Integrity in Data Services for Indigenous Scholarship
Authors: Palmer Carole L. , Sebastian Karcher , Belarde‐Lewis Miranda , Littletree Sandy , Guerrero Nestor 
Published: October 2024

ABSTRACTThe CARE Principles for Indigenous Data Governance provide essential guideposts for the stewardship of Indigenous data. To put CARE into practice in libraries and repositories, resources are needed to support implementation and integration into current research data services (RDS). Based on analysis of case studies with scholars of Indigenous language and culture, this paper articulates specific Indigenous research and data practices to guide metadata work and other areas of responsibility in RDS. The cases surface the richness of relationships and the significance of accountability in the research process—demonstrating the “relational accountability” inherent in Indigenous research methods. Robust representation of relationality is essential to retaining integrity of context in metadata for Indigenous research data. We consider the practical implications of documenting relational context with current descriptive metadata approaches and challenges in achieving CARE adherent metadata, which we argue is the backbone for broader application of CARE for Indigenous RDS.
Harnessing the Power of Scientists and Livestreaming: Health Information Outreach in a Medical Library
Authors: Song Shijie , Ying Jun , Zhao Yuxiang (Chris) , Li Jinhao 
Published: October 2024

ABSTRACTOver the last two decades, medical libraries have shifted from being careful suppliers of health information for consumers and patients to taking on prominent roles in outreach initiatives. The emerging livestreaming technology provides opportunities for medical libraries to disseminate health information and facilitate dialogues between health professionals and the public. This article presents a case study of Fudan University Medical Library's innovative approach to health information outreach through livestreaming. By leveraging the expertise of health professionals and embracing the livestreaming technologies, the library successfully engaged a broad audience, surpassing the limitations of traditional outreach methods. Based on the case, the article discusses the transformative potential of livestreaming in reshaping health information outreach and promoting health.
Assessing Preregistration Deviations: A Comparative Analysis of Psychologists and Open Science Experts
Authors: Ting Yu‐Ning , Huang Pao‐Pei , Kung Li‐Fei , Huang Yu‐Wen , Jeng Wei 
Published: October 2024

ABSTRACTUndisclosed deviations between preregistration plans and published articles challenge research transparency. This study examines whether open science experts can aid in assessing such deviations by comparing their evaluations with those of psychology experts. Using content analysis, we compared assessments of 25 preregistration plans and articles, following a psychologist studying preregistration discrepancies framework. The 72.6% agreement rate suggests differences stemmed from distinct perspectives. Psychologists leveraged domain knowledge to scrutinize subtle inconsistencies, while open science experts, deeply committed to transparency principles, focused more on procedural adherence. Open science experts, unfamiliar with psychology's implicit norms, faced challenges in discerning field‐specific knowledge and interpreting ambiguities as non‐deviations due to unclear preregistration formats and ambiguous content. Targeted support and collaborative approaches engaging both expert groups could enhance preregistration adherence evaluations, balancing the open science experts' emphasis on transparent processes with the psychologists' domain expertise, ultimately strengthening research transparency and reproducibility.
Recognizing Large‐Scale AIGC on Search Engine Websites Based on Knowledge Integration and Feature Pyramid Network
Authors: Wang Fan , Wang Afeng , Pan Minghao , Deng Shengli , Qian Qianwen , Jia Ruiqi , Zheng Ruyi 
Published: October 2024

ABSTRACTThe proliferation of Artificial Intelligence Generated Content (AIGC) poses significant challenges to user experience and information accuracy, especially on search engine websites(Guo et al., 2023). The current solution is to identify AIGC by machine learning algorithms or publicly available AI detection tools, whereas, machine learning(Wang & Wang, 2022) algorithms degrade in accuracy as more data is available and tools such as GPTZero perform poorly in the task of AIGC detection on social media. In this paper, we propose an EPCNN model to identify AIGC on search engine websites, which maintains good performance in large‐scale samples. The ERNIE model integrates cross‐domain knowledge and improves language understanding and generalization. We use ERNIE to extract text features, then use a feature pyramid network to capture semantic information at different levels, and finally use an end‐to‐end structure to connect ERNIE and the feature pyramid network to construct the EPCNN. Experimental results show that our proposed algorithm has high accuracy and the ability to handle large‐scale data compared with machine learning algorithms and AI detection tools.
Digital Literacy Education for Older Adults: A Scoping Review
Authors: Xu Lingran , Lam Yu Yan , Ng Davy Tsz Kit , Peng Pei , Suen Wing Lam , Lee Cameron Shum Yi , Chu Samuel Kai Wah 
Published: October 2024

ABSTRACTIn the context of global aging, digital technologies are increasingly recognized as a means to address the challenges associated with aging. Although many studies have explored the relationship between older adults and digital literacy, there is a gap identifying their necessary skills, challenges, and learning motivations. This review identified 30 articles from 2014 to 2024 and delineated five areas of digital literacy skills that older adults acquire, the hurdles they face in this process, and what drives their learning efforts. The difficulties faced by older adults in learning digital literacy include unfamiliarity with technology, cognitive decline, emotional barriers, limited access to digital resources, and physical and health issues. These challenges may lead to frustration in their use of devices and apps, which may affect their willingness to learn. This study, despite a small sampling size, paves the way for future research, including evaluating online fake information and addressing safety risks.
Information Standards and Guidelines on AI: Ethical Concerns, Trustworthiness, Quality Assessment, and Human Oversight
Authors: Dickey Timothy J. , Dobreski Brian , Hlava Marjorie , Lund Brady , Needleman Mark , Zeng Marcia L. 
Published: October 2024

ABSTRACTThis panel, sponsored by the ASIS&T Standards Committee, has two purposes. First, the panel gives a brief report on the most recent activities of the national and international standards in the field of information science and technologies in which the ASIS&T Standards Committee and members have been involved. More importantly, the panel will focus on several recent significant standardization efforts that address the ethical concerns, trustworthiness, quality assessment, and human oversight of artificial intelligence (AI) systems. A final open discussion on these issues will involve the audience, to highlight the benefits, challenges, and standards needed while addressing the important role of information science within our evolving society.
Who Are They? Redefining Demarcation of Research Participant Characteristics and Related Conceptualizations
Authors: Fourie Ina , Agarwal Naresh K. , Bothma Theo JD. , Mierzecka Anna , Nesset Val 
Published: October 2024

ABSTRACTIn any research that involves people, whether as respondents or participants, demarcation of their characteristics is crucial for necessary context. These can include their roles (e.g., patient, caregiver), relationships (e.g., partner), and demographics such as age range, [dis]ability, ethnicity, gender, language, race, socio‐economic group or geographic region. Yet, despite this need for precision, terminology used for demarcation is often treated as intuitive (“y'know”). For example, age demarcations seem to be obvious but are often laden with vagueness, lack of standardization, and/or acknowledgement of differences in age ranges. Some demarcations might also be influenced by country norms or by disciplinary interpretations (e.g., legal vs medical). Considering the emphasis on respect for diversity and the need for rigor in research it seems timely to open a discussion of the many questions to be answered when demarcating characteristics of research participants. Using examples, this panel will explore some applications and definitions of demarcations.
Health Misinformation Research
Authors: Greyson Devon , Lundy Morgan , Rutter Sophie , Walugembe David 
Published: October 2024

ABSTRACTHealth misinformation research has dramatically increased since the start of the COVID‐19 pandemic, although not all of this work has taken advantage of the rich theoretical and methodological background information science as a discipline has to contribute. This panel presentation will feature information scientists conducting health misinformation research from and in various settings, to showcase the value and range of information science approaches to health misinformation research. Each panelist will describe their work in the area of understanding and/or addressing health misinformation in institutions such as libraries and schools, health systems and interventions such as vaccination or public health promotion, or the general public in their online or offline information environments. Presentations will also highlight the ways researchers are applying information science theory, methods, and/or approaches to health misinformation topics, as well as lessons panelists have learned through this work. The panel will conclude with an interactive audience discussion that will center on the ways in which information science can help understand and address health misinformation challenges around the world.