bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring How Acquired Diversity of Teams Influences the Innovation Diffusion in Artificial Intelligence
Authors: Tang Xuli , Li Xin , Yi Ming 
Published: October 2024

ABSTRACTThis study explores innovation diffusion in Artificial Intelligence (AI) over the past 70 years, focusing on the impact of acquired diversity(including discipline diversity and topic diversity) of teams. We obtained 906,065 AI papers with 18,357,761 citations written by 1,316,936 authors between 1950 and 2015 from the Microsoft Academic Graph. Using citation analysis, we examine how AI innovations spread and the influence of the acquired diversity of teams on this process. We measure innovation diffusion from four aspects: innovation speed, innovation diffusion power, innovation diffusion breadth, and innovation diffusion breadth diversity. Our findings show that: (1) AI papers published before and after 2000 demonstrate distinct diffusion patterns. AI papers published before 2000 show a bimodal citation trend, while those released after 2000 present only a single peak in citations. (2) The first citation interval can be reduced by 2.35 years before 2000 and by 0.27 years after 2000 by enhancing topic diversity. (3) Both discipline diversity and topic diversity effectively promote innovation diffusion power, innovation diffusion breadth, and innovation diffusion breadth diversity in the field of AI.
A Framework for Defining Algorithmic Fairness in the Context of Information Access
Authors: Udoh Emmanuel Sebastian , Yuan Xiaojun , Rorissa Abebe 
Published: October 2024

ABSTRACTAs technologies powered by Artificial Intelligence (AI) and Machine Learning (ML) algorithms increasingly take over personal computing online and public sector domains, they simultaneously raise the promise of an extensively productive and sustainable future, as well as fears of widening inequalities, information and content divide, and a more complex information‐seeking landscape. Thus, the hopes of improved accuracy, efficiency, productivity, reduced human bias in decision‐making, and access to information are fast giving way to a trove of ethical and human rights issues with far‐reaching consequences for accountability, privacy, social justice, equity, inclusion, and informed consent, and public participation in decision‐making. Since no technology is entirely free of bias, this paper identifies algorithmic fairness as a more realistic threshold and goal. Building on findings from a previous PRISMA review of relevant literature, the paper proposes a comprehensive framework for defining algorithmic fairness in the context of information access.
Roles and Responsibilities in University‐Community Engagement for Library and Information Scientists
Authors: Bullard Julia , DeForest Heather , Detlor Brian , Ekmekcioglu Cansu , McDavid Kristina , O'Brien Heather , Shiri Ali 
Published: October 2024

ABSTRACTThis panel describes innovative digital projects and services supporting university‐community engagement. Panelists will draw on their experiences as librarians and researchers collaborating with a range of constituents, including newcomers, Indigenous communities, non‐profit organization leaders, and over‐researched, low‐income communities in rural and urban settings across Canada. The panel seeks to highlight the need to foster place‐based, contextually driven approaches to university‐community engagement efforts, and the opportunities and challenges inherent in this work. Audience members will be asked to reflect on their own experiences and consider the roles and responsibilities for library and information science scholars and professionals in facilitating reciprocity and capacity building in community‐university partnerships.
Social Media and Crisis Informatics Research in LIS
Authors: Dinh Ly , Hong Lingzi , Dumas Catherine , Patin Beth , Ghosh Souvick , Li Lingyao , Khoury Christy 
Published: October 2024

ABSTRACTCrisis informatics is centrally situated within the realms of LIS research and practice, given the focus on the interconnection between information, people, and technology during disasters such as hurricanes, earthquakes, wildfires, and global health crises. However, there is yet to be a community dedicated to crisis informatics research at ASIS&T, where researchers can exchange theoretical frameworks, the latest methodologies, and collected datasets, potentially fostering long‐term collaborations. Therefore, this panel proposes to bring together scholars within LIS who have been active contributors to crisis informatics research, from multiple perspectives ranging from critical librarianship, machine learning, and human‐computer interaction (HCI), to mixed‐methods approaches. The panelists will first share their most current crisis‐related research project and how they envision their research agenda advancing crisis informatics research in the LIS community. Then, they will engage in an interactive Q&A with the audience to discuss the current state of crisis informatics research and their prospective plans for advancing the field within the LIS research and practice community. The panel will foster collaborations and contribute to the improvement of response planning and policies through evidence about how information is sought, processed, and used during crises. This panel is sponsored by SIG Social Media (SIG SM).
Embracing Ubuntu: Cultivating Inclusive Information Access in Decolonising African Information Curriculum
Authors: Laughton Paul , Holmner Marlene , Meyer Anika , Alemneh Daniel , Rorissa Abebe , Hawamdeh Suliman 
Published: October 2024

ABSTRACTDecolonising the information curriculum through the process of indigenization is a crucial process that advocates for a paradigm shift towards the integration of various political ideologies and knowledge systems in order to correct the marginalisation and exclusion that have been sustained by colonial legacies. The Ubuntu ideology offers a foundation for promoting an inclusive, people‐centered approach to curriculum development because it places an emphasis on communal values and connection. Educators can establish learning environments that support empathy, inclusivity, and cooperation while reflecting and accommodating the needs and experiences of every student by emulating the values of Ubuntu. By appreciating students' cultural origins in the information sciences, Culturally Responsive Pedagogy enhances academic engagement and equips students for a diverse global information landscape, which further supports these efforts. Collectively, these strategies seek to foster an information society that is more socially just and equitable, which is consistent with the overarching objective of guaranteeing inclusivity and fairness in education.
Ethnographic Stories in Information Science
Authors: Montague Kaitlin E. , Hartel Jenna , Greyson Devon , Fourie Ina , Tracey Pelle 
Published: October 2024

ABSTRACTConsidering the conference theme “Putting People First: Responsibility, Reciprocity, and Care in Information Science Research and Practice,” this panel brings an ethnographic methodological conversation to the 2024 ASIS&T Annual Meeting. Our session emphasizes how participants' stories are one of the most human‐centered tools we have in research, highlighting how storytelling is an integral part of being human. The panelists have conducted ethnographic fieldwork in various contexts and begins with an introduction about ethnography as a form of storytelling, introducing concepts of vulnerability and reciprocity. Panelists will then reflect on ethnographic stories before turning to teaching Information Ethnography. Our session aims to broach the joys and challenges of ethnographic research by bringing a new honesty to the conversation in Information Science. We will engage the audience in open discussion, before breaking out into smaller groups, fostering an intimate, safe space to share stories about past research.
Why VR? Exploring the Intersection of Virtual Reality and Information Science
Authors: Williams Rachel D. , Dumas Catherine , Chow Anthony , Hofman Darra , MacLeod John 
Published: October 2024

ABSTRACTThis 90‐minute panel is structured to provide a space for open conversation among panelists and the ASIST community to consider the role and impact of virtual reality (VR) in teaching and research in information science. In the panel, we will address two key areas, including the current landscape of VR related research in information science and why VR is a valuable tool for teaching and research. The panel will begin with speakers briefly discussing their areas of expertise. From there, the panelists will facilitate open discussion using guiding questions and open dialogue with the audience. Finally, the panel will conclude with hands‐on sessions where audience members can try out several different types of VR headsets, projects, and games.
Call for Research: Leveraging Social Networking for Modern Slavery & Human Trafficking Awareness
Authors: Allen Jeff , Zimmerman Tara 
Published: October 2024

ABSTRACTHuman trafficking is a complex global issue that continues to challenge efforts aimed at raising awareness and preventing its occurrence. Overall, the literature suggests that social networking platforms have the potential to significantly enhance human trafficking awareness efforts but require careful strategy development to overcome algorithmic limitations and ensure meaningful engagement with users. Further research is needed to evaluate the long‐term impact of social networking campaigns on human trafficking awareness and prevention. This poster is an extension of a presentation at the ASIS&T Midwest Chapter Spring 2024 Symposium with the purpose of increasing attention to this important research area. This poster provides five broad research questions that can be immediately addressed by information science researchers for the purpose of increasing understanding of this devastating global issue.
Health Data Exchange: A Search Engine to Identify Health Experts
Authors: Ar Rakib Nibras , Kibria Mohammad Golam , Mostafa Javed 
Published: October 2024

ABSTRACTThe study proposes and describes a novel system called the Health Data Exchange. HDX is useful for identifying relevant experts in healthcare based on specific skill sets and their cohorts. Initial experience suggests that an expert database based on biographical data can be developed. Several techniques for automatically identifying the critical data, data normalization, storage, and retrieval are described that supported the development of the system. Such a system has the potential to facilitate efficient search and foster global collaboration among healthcare experts.
Mind Over Misinformation: Investigating the Factors of Cognitive Influences in Information Acceptance
Authors: Dewan Mouly , Shah Chirag 
Published: October 2024

ABSTRACTMany scholars have tried to investigate the identification, characterization, dissemination, and prevention of misinformation in recent years. But a fundamental question that lies behind these investigations is ‘Why do people believe in a piece of information, whether true or false?’. The primary objective of this study is to understand the psychological drivers of belief systems that makes individuals believe any information prior assessing its veracity. The study specifically tries to understand cognitive biases that influence an individual's decision making about information in digital settings. Based on a quantitative survey with 41 participants, we try to induce cognitivity among the participants and try to measure the effect in their decision making. We find a major portion of our participants being cognitively induced which in turn had a significant effect on their decision making while engaging with information. Furthermore, we try to assess whether an individual's political affiliation has any effects in perceived truthfulness while engaging with political information. This study shows us how easily cognitive bias can be induced and how it affects an individual's belief structure in digital platforms.
“We Don't Have a Lot of Answers”: An Investigation of COVID Long‐Haulers' Information Needs & Practices
Authors: Downey Miranda L. , St. Jean Beth , Behre Jane , Raymond Katherine , Liu Brooke Fisher , Shi Duli 
Published: October 2024

ABSTRACTThe information behaviors of people who have COVID‐19 have been well studied, however, there is a gap regarding those who experience long COVID. We conducted an exploratory mixed‐methods study to examine the information needs and practices of these COVID ‘long‐haulers’ with the intention of suggesting new health communication strategies to help people in similar health crises or future pandemics from an information standpoint. Several themes have emerged from our preliminary findings: how participants tend to define long COVID, their long COVID‐related information seeking and their difficulty with finding such information, and their experiences with discrimination and stigma. Throughout data collection, we have experienced issues with suspicious respondents (such as potential bots), though we were able to implement new criteria to determine legitimacy. Data collection and analysis is still ongoing and we expect to report additional findings in the near future.
Identifying Semantic Shift Reasons of Domain Entities Using Diachronic Embedding
Authors: Du Chenxin , Ye Chao , Chen Guo 
Published: October 2024

ABSTRACTIn academic literature, the semantic evolution of scientific terms reflects the development of domain knowledge. While there have been studies using diachronic word embeddings to reveal cultural and social shifts, research on the semantic evolution of scientific terms remains limited. This paper proposes a method utilizing diachronic semantic vectors to elucidate the semantic evolution of scientific entities. Firstly, diachronic semantic vectors of entities are trained using incremental learning to compute the semantic shift (ΔA) of a given entity A between periods t1 and t2. Secondly, entities similar to ΔA in periods t1 and t2 are defined as leading reasons and accompanying reasons, respectively. The experiment result shows that the leading reasons can capture the shifts of entities in the nascent stage, and the accompanying reasons can capture the shifts of words in the mature stage. The proposed method offers a better quantitative insight into the details and reasons behind domain knowledge evolution.
Humans Versus Machines: A Deepfake Detection Faceoff
Authors: Goh Dion Hoe‐Lian , Pan Jonathan , Lee Chei Sian 
Published: October 2024

ABSTRACTMachine learning (ML) models for deepfake detection are important for countering the threat of such videos. However, human detection is also critical because automated approaches may not always be available to people online. This study compares ML models versus humans for deepfake detection. Results surprisingly showed that humans performed better. Implications of our work are discussed.
Tracing the Contours of Archival Silences: A Case Study of Critical Collection Building on the Rock Springs Massacre
Authors: Han Yingying , Han Ruohua , Wickett Karen M 
Published: October 2024

ABSTRACTArchives can reinforce silences of marginalized communities, further erasing their stories and voices. This study aims to understand the contours of archival silences, focusing on experiences of Chinese people in the United States in the late 19th and early 20th centuries. We are building a digital archival collection that centers Chinese peoples' voices around the Rock Springs Massacre of 1885, an incident of racial violence that killed at least 28 Chinese people and displaced hundreds more. As we selected items, we wrote structured reflections to critically examine each item's content, source, presentation, arrangement and description in their original context, as well as any absences and silences that we encountered in the search and assessment process. Based on a praxis of radical empathy, ethics of care, and slow archives, we engaged with our positionalities, past experiences, professional training in Library and Information Sciences (LIS), and affective responses throughout the research process to reflect on how they shape our decisions and hesitations in item selection and contextualization. Three main themes emerged from a preliminary thematic analysis of our reflections: complexity of archival silences and silencing, challenges of inclusive representation, and problematizing and going beyond primary sources.
Modeling Memory Institutions: The Ainu Case Study
Authors: Iwasaki Nanami , Momodori Naoki , Koizumi Masanori 
Published: October 2024

ABSTRACTThis study aimed to construct a model of memory institutions (libraries, archives, and museums) as a lens for analyzing contemporary collective memory practices related to the Ainu people. First, we developed a pilot model to organize the current phenomena and practices of collective memories and suggest a respective circulation mechanism consisting of three core elements: media, collective representations, and collective memory. Additionally, employing this pilot model, we conducted close readings of 449 pieces of literature and illustrated the characteristics of collective memory practices and phenomena in a case study of the Ainu. Our findings indicate that 1) the traditional collective memory of the Ainu has gradually shifted toward recognizing them as a unique ethnic group, and 2) by translating their oral literature into diverse media, the Ainu have reshaped their cultural identity.
Quantitative Process of Retrieving Documents on Specific Technology Using an Academic Database and the Sentence Transformer
Authors: Lee Chul , Jun Seung‐pyo 
Published: October 2024

ABSTRACTAs competition in technologies such as semiconductors and AI intensifies, the importance of technology analysis in establishing R&D strategies is increasing. Although frequently used, technological document searches by domain experts often suffer from limitations in qualitative judgment and inconsistency. This study proposes a process for quantitatively assembling a collection of documents on specific technologies using an academic database and a language model. Using approximately 92 million records from the Web of Science, we identified related keywords from author keywords and used scientometric approaches to determine a core set of technology‐related literature. Then, a deep learning‐based Sentence Transformer model was employed to extract technology literature with high similarity to the documents, ultimately forming a set of documents for technology analysis. This study aims to overcome cognitive limitations and introduce quantitative criteria for technology analysis, which is particularly significant for data‐driven science and technology policy.
Transforming Creative Process: A Systematic Literature Review of Discourse on AI Image Generators
Authors: Lee Hyun Seung , Luo Manman 
Published: October 2024

ABSTRACTAI image generator, also known as Text‐to‐image generation (TTIG) technology, allows users to generate images based on natural language input. With advancements in AI, debates related to its application in the creative field have flourished. A systematic literature review was conducted to examine discourse that addresses the perception of people in the creative industry towards AI image generators and the impact of AI image generators on these individuals. The analysis of discourse revealed four major categories: 1) Evaluation of product or outcome of AI; 2) Impact of AI on practitioners/artists; 3) Impact of AI on creative industry and society; 4) Capabilities of AI technology. These findings provide insights into the areas of interest within AI image generator discussions on creative activity.
Health Insurance Literacy Among Young Adults: The Role of Search Generative Experience and AI
Authors: Lockett Amand , Zhang Jiaxuan , Borji Samaneh , Towne Georgia , Singh Sadie , Mobley‐Lee Jalen , Conway Laila , McConnell Molly , Stanton Aidan , Wilson Morgan , Novin Alamir 
Published: October 2024

ABSTRACTDespite global recognition of health as a fundamental human right, disparities persist due to gaps in Health Insurance Literacy (HIL). This study investigates HIL among young adults, focusing on their search behaviors and the impact of Search Generative Experience (SGE) and Generative AI. Participants displayed skepticism towards sponsored ads, preferring unbiased sources on government websites. Brand familiarity, notably with Blue Cross Blue Shield (BCBS), also influenced decision‐making. Engagement with SGE for simplified explanations suggests its potential to impact HIL. Transparent and user‐centered interventions are crucial for improving HIL, contributing to more informed healthcare decisions and reduced disparities in access to care.
Research on the Development Strategy of Cultural and Creative Products of Libraries from the Perspective of Consumer Behavior
Authors: Miao Hanyu , Wang Chunying , Zhou Lihong , Qian Jing , Wang Fan 
Published: October 2024

ABSTRACTIn recent years, there has been a notable trend and exemplary practice among libraries in effectively developing cultural and creative products. This endeavor not only foster the creative transformation and innovative development of culture, but also meets the escalating demand for high‐quality cultural consumption. Focusing on the consumption behavior of library culture and creative products in China, underscores the critical consideration for libraries, including the evolution of the consumption themes, addressing the symbolic consumption demands, creating new consumption scenarios, enhancing product quality, and augmenting consumer service awareness. Our findings highlight the importance of product diversity and aesthetic appeal, the fulfillment of commemorative value and social value, and the balancing of emotional and cognitive satisfaction in consumer demand. Moreover, the effective integration of both online and offline channels and leveraging the influence of Key Opinion Leader (KOL) are recommended marketing strategies. Regarding pricing, consumers are sensitive to price, preferring products of high quality and originality within reasonable price ranges. Finally, the study highlights the significance of enhancing the overall purchase experience and service quality, which significantly influence subsequent consumption behavior.
Everyday Triangulation within Challenging Informational and Legal Contexts: Exploring Everyday Triangulation in Individuals Considering Cannabis Use during Pregnancy or Lactation
Authors: Mulder Maria , O'Brien Heather , English Faith , Greyson Devon 
Published: October 2024

ABSTRACTMedical evidence on the risks and benefits of cannabis is limited; existing research is often inconclusive or conflicting. In the United States, cannabis use during pregnancy is stigmatized and often subject to complex legal constraints; these contextual components may have significant effects on information seeking and informed decision‐making processes. This study applies Reflexive Thematic Analysis to 23 telephone interviews with individuals considering cannabis use in pregnancy or lactation to explore their information needs; how adequately those needs were met; and how information triangulation, and other information seeking behaviours, were used to make decisions given the dearth of scientific evidence. Findings suggest that information needs are complex and contextual, and that participants used forms of triangulation that included relational and intuitive elements as well as cognitive assessment processes. A new model of Everyday Triangulation (ET) is presented to represent these complex assessment practices in a holistic manner.