bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Library/Surveillance Interface
Authors: Floegel Diana , Doty Philip 
Published: October 2021

AbstractFew topics are more often discussed than surveillance, particularly in the context of surveillance technologies that reflect structural inequities. There is space, however, to bring more discussion of surveillance tech into the library literature. At the same time, literature on digital surveillance and associated systems such as Big Data, surveillance capitalism, and platform capitalism often discuss these phenomena as if they are novel rather than iterations of long‐standing inequitable circumstances. We propose that a dialogue between surveillance literature and critical library literature will benefit both areas: theories from the surveillance domain can strengthen examinations of structural oppression in libraries while theories from critical library literature can strengthen acknowledgment of surveillance techs' historical roots. Moreover, overlap exists between concepts used in surveillance and library literature, including concerns about neutrality and classification practices. Therefore, after reviewing surveillance theories and their applicability to libraries, we demonstrate how these scholarly areas may strengthen each other, with three major consequences: (a) moving library literature beyond considerations of the panopticon in favor of the surveillant assemblage; (b) recognizing that surveillance tech is a hyper‐visible form of historical oppression; and (c) acknowledging that the library ethos is critical to any fight for justice within information science.
Analysis of Mapping Knowledge Domains for Privacy Issues in Data Ethics Research
Authors: Gao Yuan , He Jianping 
Published: October 2021

ABSTRACTThis paper is based on the Web of Science database and takes advantage of CiteSpace, a scientometric software, to conduct visualization analyses. It is found that privacy issues in data ethics have reached the research peak in the past two years. The findings of this paper are that the current global research in this field is characterized by three different periods and multidisciplinary perspectives. And the hotspots of this field are relatively concentrated and gradually deepened. Besides, the research in this field has moved from the theoretical stage to the practical application stage. This paper attempts to present the scientific knowledge structure, patterns and distribution of privacy issues in data ethics, exploring the global frontier hotspots, providing inspiration and experience for Chinese academic research and industry practice in data ethics.
“COVID19 is_”: The Perpetuation of Coronavirus Conspiracy Theories via Google Autocomplete
Authors: Houli Daniel , Radford Marie L. , Singh Vivek K. 
Published: October 2021

AbstractAs the impact of the COVID‐19 pandemic grew in 2020, uncertainty surrounding its origins and nature led to widespread conspiracy‐related theories (CRT). Use of technological platforms enabled the rapid and exponential dissemination of COVID‐19 CRT. This study applies social contagion theory to examine how Google Autocomplete (GA) propagates and perpetuates these CRT. An in‐house software program, Autocomplete Search Logging Tool (ASLT) captured a snapshot of GA COVID‐19 related searches early in the pandemic (from March to May 2020) across 76 randomly‐selected countries to gain insight into search behaviors around the world. Analysis identified 15 keywords relating to COVID‐19 CRT predictions and demonstrate how searches across different countries received varying degrees of GA predictions. When grouped with similar keywords, two major categories were identified “Man‐Made Biological Weapon” (42%, n = 2,111), and “Questioning Reality/Severity of COVID‐19” (44%, n = 2,224). This investigation is also among the first to apply social contagion theory to autocomplete applications and can be used in future research to explain and perhaps mitigate the spread of CRT.
Information as Meaningful Experience
Authors: Kizhakkethil Priya 
Published: October 2021

AbstractLeisure is seen as important in the settlement and acculturation experiences of immigrant and refugee populations as well as helping them in maintaining their cultural identity and ties to their homeland. The study covered by this paper looks at a virtual small world, converging around a leisure activity of fanfiction reading and writing from a gender and diaspora perspective, with an aim to understanding what is experienced as information within that context. Adopting a theoretical lens drawing on information and document experience literature, information was found to be experienced as everyday, as social ties, as awareness and as memories leading to a broad conceptualization of information as meaningful experience. The study also highlighted the important role played by the social context in these experiences of information, while underscoring the usefulness in adopting an experience approach, going beyond what has been the norm in the form of information seeking and problematic situations.
Genuine Information Needs of Social Scientists Looking for Data
Authors: Papenmeier Andrea , Krämer Thomas , Friedrich Tanja , Hienert Daniel , Kern Dagmar 
Published: October 2021

AbstractPublishing research data is widely expected to increase its reuse and to inspire new research. In the social sciences, data from surveys, interviews, polls, and statistics are primary resources for research. There is a long tradition to collect and offer research data in data archives and online repositories. Researchers use these systems to identify data relevant to their research. However, especially in data search, users' complex information needs seem to collide with the capabilities of data search systems. The search capabilities, in turn, depend to a high degree upon the metadata schemes used to describe the data. In this research, we conducted an online survey with 72 social science researchers who expressed their individual information needs for research data like they would do when asking a colleague for help. We analyzed these information needs and attributed their different components to the categories: topic, metadata, and intention. We compared these categories and their content to existing metadata models of research data and the search and filter opportunities offered in existing data search systems. We found a mismatch between what users have as a requirement for their data and what is offered on metadata level and search system possibilities.
“It makes me sad”: Archival Pedagogy in a Time of Covid‐19
Authors: Poole Alex H. , Zhang Jane 
Published: October 2021

AbstractDespite COVID‐19's devastating repercussions on higher education, scholars have yet to address its impact on Library and Information Science pedagogy. This exploratory qualitative case study centers on how archival educators weathered the onslaught of the pandemic. Drawing upon semistructured interviews with 31 archival educators and documentary evidence, this research addresses the sudden shift to online education; the concomitant loss of hands‐on work opportunities and the workarounds educators developed; affectivity and an emergent ethics of pedagogical care among students and educators; and educators' lessons learned from the pandemic and their future projections regarding archival education. This paper illuminates the evolving landscape of pedagogy and its attendant challenges preparing the next generation of archival professionals during an unprecedented period of duress.
Just Infrastructure? Field Research on a Standardized Assessment Tool for a Continuum of Care for People Experiencing Homelessness
Authors: Slota Stephen C. , Fleischmann Kenneth R. , Greenberg Sherri , Surka Michelle , Evans Keyanna S. , Snow James , Rodriguez Sarah , Zimmerman Tara 
Published: October 2021

AbstractAs community‐oriented programs move from intervention to infrastructure, questions of just and equitable access to that infrastructure both arise and become more consequential to those served. However, extant tools are general in scope, often undertested, and inconsistently linked with positive outcomes for served communities and service providers. We explore the dynamics and implications of a key tool within this infrastructure intended to enable portable collaboration across organizations serving those who are experiencing homelessness: the VI‐SPDAT (Vulnerability Index ‐ Service Prioritization Decision Assistance Tool). This tool, while providing a means of coordinated assessment, must itself be negotiated according to the values, data concerns, and goals of the agencies and service providers who make use of it. This paper reports findings from 29 interviews with individuals working in nonprofits, charities, and government agencies that provide services or resources to people experiencing homelessness within the City of Austin's Continuum of Care. The life‐and‐death stakes of the VI‐SPDAT, which is designed to prioritize access to services based in part on a prediction of potential for premature mortality, drive home the need for equitable and just infrastructure.
Why Do You Trust Siri?: The Factors Affecting Trustworthiness of Intelligent Personal Assistant
Authors: Wu Dan , Huang Yeman 
Published: October 2021

AbstractTrust greatly contributes to human‐AI collaboration, however, human's trust to IPA is hard to establish and lacks exploration. The purpose of this paper is to recognize the factors that affect the trustworthiness of IPA. 358 questionnaires were analyzed by PLS‐SEM to construct the model, while thematic analysis was used to discover expectance of IPA. Chi‐square tests and T‐test were used to distinguish the difference between two user groups. Three factors that capability of system, personality of agent, and availability of interface have a significant impact on the trustworthiness of IPA. The capability of system is the most essential as the threshold with users’ plenty of expectations. Most users pay less attention to the availability of interface and the personality of agent has a great impact on the trustworthiness of IPA. The factors found enrich the trusted AI research and inspire insights of design of IPA.
Perceived Usability and Experience with Digital Tools in the Context of Digital Humanities Research
Authors: Du Jesse , Yuen Chris , Slaughter Micah , Chen Annie T. 
Published: October 2021

AbstractThis paper examines differences in the user feedback of scholars with varied experience with digital tools. As part of a usability study of a historical digital collection, our team conducted semi‐structured interviews with scholars with varying backgrounds. We categorized the sample into two groups, one with significant experience and one with little experience in using digital technology. Qualitative analysis of the interview data showed that users generally provided similar feedback. However, there were instances in which those with significant experience provided more design suggestions, and those with less experience expressed confusion and provided more feedback on website content. Drawing upon our findings, we provide recommendations for the usability evaluation of historical digital collections.
#StopAsianHate: Archiving and Analyzing Twitter Discourse in the Wake of the 2021 Atlanta Spa Shootings
Authors: Fan Lizhou , Yu Huizi , Gilliland Anne J. 
Published: October 2021

AbstractOn March 16, 2021, six Asian women were killed in Atlanta, US, possibly out of racist motivations. This tragic event, now known as the 2021 Atlanta Spa Shootings, precipitated a massive increase in the volume of counter‐anti‐Asian declarations and discussion on social media platforms such as Twitter. In a pilot study to chronicle and profile public opinions, social movements and patterns in the global Twitter discourse we scraped the Twitter API using the query term “StopAsianHate”, obtaining more than 5.5 million tweets and their metadata. By using social movement analytical frameworks to analyze traffic peaks and the use of hashtags, we identified a set of more than 300 frequently used hashtags that can serve as specific query words in future archival ingest activities, as well as the dimensions of and current problems with this social movement. This suggests the utility of this approach for both archiving applications and social‐political analyses of emerging topics and concerns.
Towards Finding a Research Lineage Leveraging on Identification of Significant Citations
Authors: Ghosal Tirthankar , Singh Muskaan 
Published: October 2021

AbstractFinding the lineage of a research topic is crucial for understanding the prior state of the art and advancing scientific displacement. The deluge of scholarly articles makes it difficult to locate the most relevant prior work and causes researchers to spend a considerable amount of time building up their literature list. Citations play a significant role in discovering relevant literature. However, not all citations are created equal. A majority of the citations that a paper receives are for providing contextual, and background information to the citing papers and are not central to the theme of those papers. However, some papers are pivotal to the citing paper and inspire or stem up the research in the citing paper. Hence the nature of citation the former receives from the latter is significant. In this work in progress paper, we discuss our preliminary idea towards establishing a lineage for a given research via identifying significant citations. We hypothesize that such an automated system can facilitate relevant literature discovery and help identify knowledge flow for at least a certain category of papers. The distal goal of this work is to identify the real impact of research work or a facility beyond direct citation counts.
Publisher References in Bibliographic Entity Descriptions
Authors: Hahn Jim 
Published: October 2021

AbstractThis paper describes a method for improved access to publisher references in linked data RDF editors using data mining techniques and a large corpus of library metadata encoded in the MARC21 standard. The corpus is comprised of clustered sets of publishers and publisher locations from the library MARC21 records found in the Platform for Open Data (POD). POD is a data aggregation project involving member institutions of the IvyPlus Library Confederation and contains seventy million MARC21 records, forty million of which are unique. The discovery of publisher entity sets described forms the basis for the streamlined description of BIBFRAME Instance entities. The result of this work includes a database of association rules and RDF editor improvements. The association rules are the basis of a prototype autosuggestion feature of BIBFRAME Instance entity description properties designed specifically to support the auto‐population of publisher entities in linked data RDF editors.
AI Literacy: Definition, Teaching, Evaluation and Ethical Issues
Authors: Ng Davy Tsz Kit , Leung Jac Ka Lok , Chu Kai Wah Samuel , Qiao Maggie Shen 
Published: October 2021

AbstractArtificial Intelligence (AI) is at the top of the agenda for education leaders today in educating the next generation across the globe. However, public understanding of AI technologies and how to define AI literacy is under‐explored. This vision poses upcoming challenges for our next generation to learn about AI. On this note, an exploratory review was conducted to conceptualize the newly emerging concept “AI literacy”, in search for a sound theoretical foundation to define, teach and evaluate AI literacy. Grounded in literature on 18 existing peer‐reviewed articles, this review proposed four aspects (i.e, know and understand, use, evaluate, and ethical issues) for fostering AI literacy based on the adaptation of classic literacies. This study sheds light on the consolidated definition, teaching, and ethical concerns on AI literacy, establishing the groundwork for future research such as competency development and assessment criteria on AI literacy.
Reconciling Authority and Agency through Information Practices Research
Authors: Olsson Michael 
Published: October 2021

AbstractAuthority and Agency have been central concepts in information science since its beginnings in 19th century documentalism. This paper begins with a brief historical overview of how these concepts have been constructed in the traditional and user‐centred paradigms. It will then explore how an information practices perspective affords the possibility of seeing authority and agency not as oppositional but rather as synergistic: two sides of the same theoretical coin. This exploration will be contextualised by examples drawn from the author's own research over more than two decades across a range of studies. This body of research includes studies of academic, artistic and serious leisure communities.
Named Entity Disambiguation for Archival Collections: Metadata, Wikidata, and Linked Data
Authors: Polley Katherine Louise , Tompkins Vivian Teresa , Honick Brendan John , Qin Jian 
Published: October 2021

AbstractRepresenting archival metadata as linked data can increase the findability and usability of items, and linked data sources such as Wikidata can be used to further enrich existing collection metadata. However, a central challenge to this process is the named entity disambiguation or entity linking that is required to ensure that the named entities in a collection are being properly matched to Wikidata entities so that any additional metadata is applied correctly. This paper details our experimentation with one entity linking system called OpenTapioca, which was chosen for its use of Wikidata and its accessibility to librarians and archivists with minimal technical intervention. We discuss the results of using OpenTapioca for named entity disambiguation on the Belfer Cylinders Collection from the Special Collections Research Center at Syracuse University, highlighting the successes and limitations of the system and of using Wikidata as a knowledge base.
LEADING the Way: A New Model for Data Science Education
Authors: Poole Alex H. 
Published: October 2021

AbstractAddressing the data skills gap, namely the superabundance of data and the lack of human capital to exploit it, this paper argues that iSchools and Library and Information Science programs are ideal venues for data science education. It unpacks two case studies: the LIS Education and Data Science for the National Digital Platform (LEADS‐4‐NDP) project (2017–2019), and the LIS Education and Data Science‐Integrated Network Group (LEADING) project (2020–2023). These IMLS‐funded initiatives respond to four national digital platform challenges: LIS faculty prepared to teach data science and mentor the next generation of educators and practitioners, an underdeveloped pedagogical infrastructure, scattered and inconsistent data science education opportunities for students and current information professionals, and an immature data science network. LEADS and LEADING have made appreciable collaborative, interdisciplinary contributions to the data science education community; these projects comprise an essential part of the long‐awaited and much‐needed national digital platform.
Using Future Work Sentences to Explore Research Trends of Different Tasks in a Special Domain
Authors: Qian Yuchen , Li Zhicheng , Hao Wenke , Wang Yuzhuo , Zhang Chengzhi 
Published: October 2021

AbstractResearch trend detection is an important topic for scientific researchers. Future work sentences (FWS), as direct descriptions of future research, aren't fully utilized in research trend detection. Therefore, this article uses FWS to investigate research trends of different tasks in a particular domain. Taking the conference papers in the natural language processing (NLP) field as our research objects, we obtain the FWS in each paper to build the corpus and classified them into 6 main types. After that, the task of each paper is annotated, and a task system with 29 categories is constructed to compare the FWS in different tasks. The results show that the proportion of method mentioned in FWS is the highest, and different tasks focus on different FWS types: emerging tasks need more resources, while mature tasks prefer method and application. This study provides researchers a reference to understand the research trend of specific tasks and is helpful to compare different tasks.
Content Moderation of Speech in Political Discussions
Authors: Sang Yisi , Liang Lizhen , Stanton Jeffrey 
Published: October 2021

AbstractSocial media platforms have been hailed as “politically disruptive communication technologies” (Hong & Nadler, 2012). Individuals express opinions and engage with politicians, the press, and each other on social media, sometimes using offensive language (Rossini et al., 2020). Content moderation has been adopted by many social media platforms to screen and evaluate offensive speech. In the present study we trained offensive speech classifiers to analyze offensive speech examples by integrating three archival datasets. We then used the trained classifier to examine a large body of comments about YouTube videos posted during the 2018 midterm election cycle. This provided information on the prevalence of various kinds of offensive comments and the pattern of content moderation used by YouTube. We also examined comment negativity using offensive speech lexicons. Our results showed systematic variance in the prevalence of offensive speech topics depending upon the political orientation of the content. Language use was significantly different between left and right‐leaning videos for comments related to sexism.
Recognition and Analysis of Emotional Words in Ancient Chinese Poetry under Different Themes
Authors: Zhang Wei , Wang Hao 
Published: October 2021

AbstractThe emotional connotation in ancient poetry is a valuable human spiritual culture, adopting the key semantic technique to parse the emotional word in poetry under different themes is beneficial to discover the relationship between poetry theme and emotion. In a “cold environment” (without learning corpus) of Tang poetry, this work presents, for the first time, the automatic recognition and analysis of large‐scale humanistic emotional words within ancient Chinese poetry from different themes. A “cold start” automatic citation method for character sequences is proposed to obtain the learning corpus. The best F1 and F1_distinct of trained BERT‐BiLSTM‐CRFs model respectively reach 96.27% and 86.04%. Deep learning expanded imagery words that convey emotion to realize knowledge discovery. The relationships between theme and emotion word show that Chinese poetry is good at using natural objects to express various sentiments to people, with each theme of poetry owns distinguished emotion feature.
Health Information Behavior in the Context of Medical Decision‐making: An Exploratory Study based on Vaccination in Beijing
Authors: Zhang Yuhao , Zheng Guangchun 
Published: October 2021

AbstractCOVID‐19 vaccination could be the most economical and effective public health intervention to prevent and control novel coronavirus. Beijing is one of the first regions in China to implement the COVID‐19 vaccination policy, we conducted semi‐structured interview on 20 participants with past vaccination AND/OR COVID‐19 vaccination decision‐making. This study summarizes the consistency and particularity in the context of decision‐making in terms of information sources, information content and information behavior.