bluuebunny/crossref_metadata_2025_split huggingface dataset:
The New Information Retrieval Problem: Data Availability
Authors: Sharma Sarika , Wilson James , Tian Yubing , Finn Megan , Acker Amelia 
Published: October 2023

ABSTRACTThe goals of open science are driven by policies requiring data management, sharing, and accessibility. One way of measuring the impact of open science policies on scientific knowledge is to access data that has been prepared for re‐use. But how accessible/available are data resources? In this paper, we discuss a method for exploring and locating datasets made available by scientists from federally funded projects in the US. The data pathways method was tested on federal awards. Here we describe the method and the results from analyzing fifty federal awards granted by the National Science Foundation to pursue data resources and their availability in publications, data repositories, or institutional repositories. The data pathways approach contributes to the development of a practical approach on availability that captures the current ways in which data are accessible from federally funded science projects –ranging from institutional repositories, journal data deposit, PI and project web pages, and science data platforms, among other found possibilities. This paper discusses some background and motivations for such a method, the method, research design, barriers encountered when searching for data resources from projects, and how this method can be useful to future studies of data availability.
“Garbage Bags Full of Files”: Exploring Sociotechnical Perceptions of Formats within the Recovery and Reuse of Scientific Data
Authors: Wagner Travis L. , Fenlon Katrina , Sorensen Amanda 
Published: October 2023

ABSTRACTThis paper explores the social and technical perceptions of physical and digital formats as they relate to work in the recovery and reuse of scientific data, specifically historical, archival, and defunct data sources. Proprietary and obsolete formats, or formats that need significant transformation work, stand out as central challenges for scientists and data curators who are recovering reusable data from archival or legacy data sources. The challenges confronting data sharing and reuse of contemporary scientific data are already known to be myriad; formats often pose a major, compounding challenge to retrospective data curation research and practice. Based on 23 qualitative interviews with practitioners conducting data recovery and reuse, ranging from marine biologists to data librarians, we study how they understand, engage with, and utilize formats within their data curation work. This paper enumerates the formats deployed throughout the scientific data curation process and explores how practitioners creating and curating scientific data based on historical and archival materials encounter, make sense of, and utilize formats. The paper focuses on practitioner perceptions of formats around the following themes: how practitioners' historical relationships to certain challenging formats inform their ongoing curation practices; the importance of contexts in prioritizing or ignoring formats within scientific curation work; and how formats reveal larger sociotechnical issues. The paper concludes by with practical and theoretical implications of navigating formats within the recovery and reuse of scientific data and offers suggestions for reconfiguring formats within broader data curation lifecycles.
Social VR: A Promising Platform for Enhancing Mental Wellness among College Students
Authors: You Xinyue (Sally) , Bailey Jakki O. , Won Andrea Stevenson , Ahn Sun Joo (Grace) , MacIntyre Blair 
Published: October 2023

ABSTRACTIn recent decades, there has been an alarming increase in the number of university and college students struggling with intensifying psychological distress, which has become a mental health crisis on campuses. To address this issue, this study proposes social VR as a potential platform to promote social interaction and improve mental well‐ being for college students. In this study, 68 students explored a variety of social VR applications in a classroom setting. Results showed that a) virtual space, audio, avatar, communication types, and activities were key contributing features that facilitated social interaction among college students in social VR and have the potential to enhance mental wellness, and b) the anonymous nature, communicative cues, and designated private areas provided by social VR platforms were effective in facilitating self‐disclosure, indicating social VR's potential in delivering mental health services such as individual and group counseling and therapy. This study provides evidence that social VR can enhance social interaction and communication while serving as a platform for professional mental health care, a venue that has yet to be explored in previous studies.
The Causality between Offensive Language Use and Negative Emotions in the Public Event— An Empirical Study Using Convergent Cross Mapping
Authors: Chen Miaomiao , An Lu , Li Gang 
Published: October 2023

ABSTRACTThe mutual causal interdependence between offensive language use and negative emotions has been largely underexplored in the public event. Using 784,179 posts about the Tangshan violence event collected from Sina Weibo, nine themes were recognized based on framing theory. The mutual causal relationship between offensive language and negative emotions under each theme was examined through Convergent Cross Mapping. Results suggested that the mutual causal relationships between offensive language and negative emotion intensity under various themes were different with bidirectional causality under moral judgement, emotional venting, and power conflict, unidirectional causality under the vulnerable framework and the trust framework, and no causality under other themes. More detailed examination revealed special bidirectional or unidirectional causality between offensive language and some fine‐grained negative emotions under the vulnerable framework, the trust framework, and secondary opinion. This study provides insight into the interaction between offensive language and negative emotions and helps emergency managers make targeted strategies to solve the problems of offensive language use and negative emotions.
Trust in Search Engines: Developing a Trust Measure and Applying It in an Experiment
Authors: Häußler Helena 
Published: October 2023

ABSTRACTNowadays, users trusting search engines appears fundamental, although this claim is built on little research. In face of new developments of search, the question comes up again: to what extent users trust a search engine, how it is justified, and which consequences does it imply. Based on interdisciplinary research on trust, the individual concepts of trust, trustworthiness, and trust‐related behavior ares outlined and applied to the web search context. To date, there is not an adequate instrument for collecting the ambiguous concept of trust for technical artifacts like search engines. Therefore, a trust measure will be developed with the help of a qualitative laboratory study and validated with an online survey. Afterwards, the measure will be applied in an experiment to the search engines Google and Ecosia and scenarios from the health and finance domain. The expected results indicate the causes and effects of trust in a search engine. In consequence, misplaced and well‐founded cases of trust in search engines can be identified and discussed among civil society, researchers, and policymakers.
Exploring Applications and User Experience with Generative AI Tools: A Content Analysis of Reddit Posts on ChatGPT
Authors: Choi Wonchan , Zhang Yan , Stvilia Besiki 
Published: October 2023

ABSTRACTAs part of a larger project, this paper reports on preliminary findings of a study exploring use cases of ChatGPT and associated behaviors and experiences among users of an online forum. Posts on a ChatGPT‐related forum on Reddit (n = 452) were analyzed using qualitative content analysis. This paper reports on themes relevant to this study, including the types of tasks for which users used ChatGPT, user experiences, and perceived impacts of ChatGPT. ChatGPT was often used to facilitate various writing tasks (e.g., writing an essay), academic tasks (e.g., finding scientific references for a research paper), everyday tasks (e.g., creating a meal plan), and conversational purposes (e.g., having a simulated conversation about a past event). Users expressed positive (e.g., excited, amazed) and negative (e.g., fooled, concerned) feelings toward the technology. They raised various issues and problems with ChatGPT at the content (e.g., inaccuracy, incompletes) and system (e.g., unavailability, instability) levels. Users discussed the perceived impacts of ChatGPT on individuals (e.g., unemployment) and society (e.g., AI divide). Study findings can inform the design of policies and guidelines for mitigating AI problems and promoting the effective and ethical use of emerging AI technologies.
A Preliminary Investigation of the Effects of Open Review on Citation Impact
Authors: Liang Tiantian , Zhong Zhuosheng , Zuo Zhiya , Li Hui , Wang Xi 
Published: October 2023

ABSTRACTThis study investigates the impact of open review on citation counts of academic articles. By collecting articles published in the material science area of Nature Communications from 2014 to 2018, we exploit the adoption of voluntary open review in 2016 to examine how article citation counts are associated with open review using propensity score matching and regression analysis. OLS regression results show that open review comes at the expense of fewer citations received by articles. Specifically, open‐reviewed articles received 44% fewer citations than their non‐open‐reviewed counterparts. An additional mediation analysis reveals that this decrease in citations may be partially attributed to the lengthening of the review cycle of articles that were open reviewed–open‐reviewed articles experienced 16% longer review cycles; every 16% extension of the review cycle led to 5.8% fewer citations. Results remained qualitatively similar when we restricted the citation windows to three years since publication. Contrary to previous findings concerning the positive effects on articles’ citation impact, our preliminary results call for additional efforts in identifying the costs and benefits associated with open review.
Online Incivility and Contextual Factors: Data‐Driven Detection and Analysis
Authors: Dumas Catherine , Ghosh Souvick , Hong Lingzi , Karami Amir , Vaidya Priya 
Published: October 2023

ABSTRACTUncivil behaviors like rude or hate speech have been a persistent problem on social media, which could lead to negative user experience or even affect the psychological well‐being of users. Automatic detection and moderation of such behaviors are critical to creating a supportive online community for effective user communication and positive user experience. In this tutorial, we propose methods to study online incivility, which includes data collection from a social media platform, i.e., Reddit, automatic detection of incivility with pretrained deep learning classifiers, and statistical and visual analytical methods to investigate the combination of community characteristics and users’ interactive patterns that relate to the occurrences of incivility. Similar methods can be applied to understand other information misbehaviors online, such as misinformation, dissemination of rumors, and cyberstalking. This panel is sponsored by SIG SM.
Storytelling for Translational Research Impact
Authors: Gonzalez Sarah , Liu Ying‐Hsang , Syn Sue Yeon , Makri Stephann , Connaway Lynn Silipigni , Given Lisa M. , Hartel Jenna , McDowell Kate 
Published: October 2023

ABSTRACTTranslational research converts research knowledge into practical wisdom for a community (What is Translational Research, n.d.). Storytelling for translational research means that the researcher knows the audience, crafts a narrative, sticks to the plot, and imparts wisdom in a meaningful way – all elements of a good story from a good storyteller. In this hybrid panel and workshop, led by Stephann Makri and other members of the ASIS&T Research Engagement Committee, our successful researchers/storytellers will illustrate how a good translational research impact story is structured. Then, our storytelling experts will help participants craft their own research narratives to put translational research storytelling into practice for their own research stories. Dr. Kate McDowell, panelist and storytelling expert, teaches both storytelling and data storytelling courses, and is the 2022 recipient of the ASIS&T Outstanding Information Science Teacher Award. She states: “When research successfully translates into legislative or policy changes, it always comes down to a shared narrative experience. The story emerges in the dynamic interaction between the teller and the audience.” The aim of this session is to create confident storytellers.
Messages and Calls Ignored? A Survey of Four Thousand Smartphone Users on Non‐Response Behavior
Authors: Agarwal Naresh Kumar 
Published: October 2023

ABSTRACTWe are living in a world where a lot of people maintain constant connectivity through sending and receiving messages and calls. Contemporary research has focused on how smartphones disconnect us from our physical environment. Yet, in a digital disconnect, almost daily, people choose not to respond to certain messages or calls, which can make the sender anxious and adversely affect their communication. The first phase of this project consisted of an interview study of 24 participants which led to publications covering the sender and receiver perspectives. A follow‐up large‐scale survey of 4,001 respondents was carried out to investigate the receiver's reasons for not responding including the role of power, the psychological impact on the sender, and other communication. Theories on information avoidance, power, interpersonal deception, and emotions inform this study. Preliminary findings are shared here. The findings will inform the fields of information science, communication, psychology, and mental health, and should help software designers build tools to help users communicate their context to each other.
Generative Artificial Intelligence (GAI) Divide: An Empirical Examination of the Micro–Macro Factors that Predict GAI Knowledge and Use
Authors: Ball Christopher , Huang Kuo‐Ting 
Published: October 2023

ABSTRACTGenerative artificial intelligence (GAI), a branch of AI capable of generating new content from human input has the potential to impact every aspect of our society. However, as with any emerging technology, the benefits and detriments of GAI may not be evenly distributed, leading to digital inequality. Aspects like AI access, effectively usage, and usage outcomes could define this emerging and evolving GAI divide. To fill the current research gap on GAI inequality, this study aims to empirically explore the factors that may contribute to a GAI divide to ensure that the benefits of this technology are distributed equitably throughout society. To address these challenges, An online survey will be conducted to examine both macro‐ and micro‐level factors that may potentially proliferate and ameliorate the GAI divide.
Enabling Historical Thinking through Interorganizational Cooperation
Authors: Bossaller Jenny , Witt Steven , Aparac‐Jelušić Tatjana 
Published: October 2023

ABSTRACTThis poster problematizes selected presentations and outcomes of an IFLA satellite conference on the history of professional organizations of librarians and information scientists. Representatives from organizations, including ASIST and library associations around the world from four continents (Europe, North America, Asia, Africa) will meet at the Mundaneum in Mons, Belgium. The theme of the conference is “Preserving our origins: Approaches to the organization, curation, and historiography of the record of national and international organizations in libraries, information, and documentation.”An irony within information science is that its many professional associations often fail to identify and preserve their own history. Their work is documented, but often not well preserved, and hidden from a wider audience. Born digital materials are especially vulnerable to loss (Neal, 2015). This poster identifies problems and best practices in managing the documents of historical value of volunteer‐led associations and invites ASIST members to contribute to the historical work of the association.The goal is to identify common problems in preserving association histories. The poster will present several projects discussed at the IFLA satellite conference, as well as proposed ways forward that will advance historical work for the information professions.
Making Ends Meet in a Pandemic: African Library Initiatives During COVID‐19
Authors: Bugre Charles , Jowaisas Chris , Young Jason C. 
Published: October 2023

ABSTRACTThis poster captures the initiatives of African community and public libraries in the early stages of COVID‐19. This is part of an ongoing research on the impact of the COVID‐19 and long‐term implications for African libraries. We conducted 11 interviews in 9 countries using both purposive and snowball sampling. We analyzed the recorded data through a thematic analysis approach. Arising from the data, we found that librarians employed empathetic information interventions using widely available information technology tools to deliver critical information to promote the well‐being of their communities. The libraries initiated social cohesion talks to foster unity among families. They also used WhatsApp to send snapshots of study materials to examination candidates and to point people to social services. This work contributes data to scant literature about the initiatives of African community and public libraries during the COVID‐19 and how low resource libraries can support their communities in crisis.
Performance and Organizational Characteristics of Analytics Teams in Healthcare and Population Health: Methods and Preliminary Observations
Authors: Buie Ronald W. , Zachry Mark , Chen Annie T. 
Published: October 2023

ABSTRACTExisting models of the work of analytics teams and how they impact health organizations do not describe the activities, nor their relationship to the organization, in sufficient detail for optimal decision making. This poster reports on an ongoing study of the work of healthcare and population health analytics teams to rectify this gap. We are interviewing members of analytics teams in healthcare and population health organizations to gather data on the processes, deliverables, downstream and upstream stakeholders, and artifacts that the teams rely on to conduct and manage their work. The primary analysis uses a grounded theory approach, with a secondary activity theory analysis of relationships between the analytics team, identified cognitive artifacts, and intended outcomes. In this poster, we intend to present the methods, participants, and some preliminary observations. We hope that this presentation will solicit feedback that leads to improvements in the study.
Data Governance Practices Unveiled: Insights from Multiple Data Collection Approaches
Authors: Chang Yun‐Chi , Lin Fang‐Pang , Jeng Wei 
Published: October 2023

ABSTRACTThe poster discusses varying data collection approaches in investigation of an organization's data governance practice of a single case study. The aim is to promote transparency in data governance practice on a case‐by‐case basis and to unveil the circumstances of adapting approaches in data collecting. Four distinct data collecting approaches were utilized in this study, each tailored to diverse needs and scenarios, including group interview, design‐thinking workshop, semi‐structured interview and field study. Clarifying the rationale of taking certain approaches, the research team aims for providing the benchmark for future data governance research.
Digital Information Service to Combat Violence against Women: The Comunica Mulher Project
Authors: Costa Michelli 
Published: October 2023

ABSTRACTThe present study discusses the methods and outcomes of a project conducted at the University of Brasília with the aim of providing information services to the community of the Federal District (Brazil) on COVID‐19 prevention and vaccination, as well as addressing domestic violence. Employing social marketing strategies, such as content marketing and viral marketing, the project sought to disseminate pertinent information and engage the target audience through social media platforms, primarily Instagram. The content marketing approach entailed the creation and distribution of reliable information utilizing authoritative sources and visual resources, such as illustrations, graphs, infographics, and diagrams. Simultaneously, the viral marketing strategy endeavoured to identify emerging subtopics of interest by leveraging the Google Trends tool and relevant commemorative dates. These integrated strategies yielded a remarkable 700% surge in the project's Instagram account reach alongside heightened audience engagement. The study concludes that community information services should prioritize the dissemination of contextually relevant information for various population segments, particularly those that are historically marginalized.
ChatGPT Media Coverage Metrics; Initial Examination
Authors: Delellis Nicole S. , Chen Yimin , Cornwell Sarah E. , Kelly Dominique , Mayhew Alex , Onaolapo Sodiq , Rubin Victoria L. 
Published: October 2023

ABSTRACTThis paper presents an overview of coverage of OpenAI's ChatGPT in media outlets from November 2022–March 2023, a comparison to previous media coverage of the chatbot Tay across the same outlets, and a count of ChatGPT media articles pertaining to government legislation and regulation. The New York Times, Wired, Gizmodo, The Globe and Mail, and The Guardian were searched for coverage. Across all five outlets there is an uptick in media coverage surrounding ChatGPT, with total numbers of included articles per month being 0 in November, 39 in December, 68 in January, 104 in February, and 143 in March. Findings exemplify the trend of increased coverage of ChatGPT in media public discourse, which contrasts with previous smaller media coverage of Tay. Examination of headlines and subheadings of included articles reveals minimal coverage (5.7%) dedicated to government legislation of ChatGPT. Future research will evaluate what is being said about ChatGPT within these media outlets.
Comparing the Writing Styles of Multiple Disciplines: A Large‐Scale Quantitative Analysis
Authors: Dong Shuyi , Mao Jin , Pei Lei 
Published: October 2023

ABSTRACTInvestigating the writing styles of different disciplines is crucial for comprehending the scientific language in scholarly communication. This study examines the variations in scientific writing styles across disciplines using a large‐scale analysis on 14 million abstracts from the Microsoft Academic Graph database. Writing styles are quantified in four aspects: symbolic, lexical, syntactic, and readability. The t‐tests were employed to explore potential trends in the evolution of writing style and investigate linguistic differences across disciplines. Results indicate an overall trend towards increasing complexity and informativeness in writing, with significant changes observed in Biology, Chemistry, Computer Science, and Psychology. Disparities of linguistic features in writing styles were observed across disciplines. The findings shed light on the distinct language use in scholarly communication across disciplines.