bluuebunny/crossref_metadata_2025_split huggingface dataset:
AI or Authors?: A Comparative Analysis of BERT and ChatGPT's Keyword Selection in Digital Divide Studies
Authors: Kang Woojin , Lee Myeong , Lee Jongwook , Oh Sanghee 
Published: October 2023

ABSTRACTAuthor keywords attached to academic papers are often used in intellectual structure analysis. However, the length and selection criteria for keywords vary across publications and, even some publishers do not require keywords for their articles. To explore the opportunity to overcome such keyword inconsistency issues, this study compared author keywords from papers focused on the digital divide with those extracted using the language models, BERT and ChatGPT. Preliminary findings reveal structural variations across the keyword networks and suggest a potential need to revisit keyword‐based research. Future research will expand the scope of the dataset and conduct an in‐depth analysis of keyword patterns across the language models.
Reading Comprehension in Information Retrieval (RCIR) for Personalized Results
Authors: Kim Yumi , Kim Heesop 
Published: October 2023

ABSTRACTRecent research on personalized retrieval technology has been actively conducted to meet the needs of users for seeking adequate information. To refine the retrieval, researchers are considering user behavior patterns in a variety of ways. In this study, we use eye‐tracking metadata to predict users' levels of comprehension as textual evidence for IR processes. Furthermore, we incorporated eye‐tracking metadata on the Automated Readability Index (ARI), a readability assessment tool of an English text. Our research is largely divided into two tasks: i) comprehension evaluation task (CET) and ii) comprehension‐based retrieval task (CRT). In the CET task, for predicting the comprehension level, we applied various regression models. Among them, the Voting regressor demonstrated the highest performance with a Spearman's 𝜌 of 0.68. In the CRT task, we incorporated the level of comprehension predicted in the CET task and ARI score into the ranking results. We derived a sentenceBERT to find the relevant text for a query and the Normalized Discounted Cumulative Gain (nDCG) for evaluating the CRT task. The nDCG score for Comprehension Level only and that with ARI together were 0.65 and 0.78, respectively. Thus, applying ARI resulted in a higher nDCG score compared to comprehension level only.
Usability Evaluation of Kiosks for Visually Impaired College Students
Authors: Kim Yumi , Kim Kyounghoon , Lee Jongwook 
Published: October 2023

ABSTRACTIn the rapid flow of digital transformation, kiosks have naturally become part of our daily lives. In this study, we targeted visually impaired college students in their 20s, the primary user group of kiosks. We evaluated the usability of a self‐service certificate issuance and fast‐food restaurant kiosks. Based on Nielsen's five usability evaluation criteria, we presented experimental tasks to the visually impaired college students, monitored their performance, and conducted interviews to assess usability. Through this process, we aimed to understand the usage difficulties of visually impaired people when using kiosks and identify their specific requirements. Furthermore, we aimed to provide insights into improving the accessibility and usability of kiosks for this population and offer practical implications for developing kiosk education programs.
Toward the Conceptualization of Data Quality Assurance in Research Data Repositories
Authors: Lee Dong Joon , Ali Faizan , Stvilia Besiki , Pang Yuanying , Gonthina Karthik 
Published: October 2023

ABSTRACTData quality assurance (DQA) is critical to research data sharing and reuse. There has been a growing recognition of data transparency, reproducibility, credibility, and validity in research. Although the research data curation literature is large, it lacks data quality theory‐guided examinations of DQA practices in research data repositories. This poster paper reports on the preliminary findings of a larger study that examines DQA practices in research data repositories, including their use of DQA ontologies, standards, and metadata vocabularies. In particular, the paper examines two quality standards and an ontology for their conceptualization of DQA activities and their structure. The authors used the findings of the analysis and the data quality literature to synthesize an initial model of a DQA process in research data repositories that conceptualizes three DQA activities: evaluation, intervention, and communication. This paper can inform the development of ontologies and best practice guides for designing and evaluating DQA workflows in research data repositories.
Analysis of the Dissemination Characteristics of Papers on WeChat Official Accounts of Chinese Academic Journals
Authors: Li Lei , Wang Xuyan 
Published: October 2023

ABSTRACTNew media platforms have enhanced the efficiency and diversity of information dissemination, providing new possibilities for the dissemination and promotion of academic papers. Currently, a large number of Chinese academic journals from different disciplines have established WeChat official accounts to promote their papers. This study examines WeChat official accounts from three disciplines: social sciences, natural sciences, and medicine. We analyze the existing paper promotion methods employed by these academic journal official accounts from four dimensions: content presentation format, number of papers promoted in a single post, interactive forms, and publishing time. The findings reveal that the current promotion methods for academic papers on WeChat official accounts are relatively limited, with low utilization of multimedia content. Therefore, there is a need for further improvement in new media promotion for academic papers.
Humanities Scholars' Understanding of Data and the Implications for Humanities Data Curation
Authors: Li Wenqi , Zhang Pengyi , Wang Jun 
Published: October 2023

ABSTRACTThis study addresses the need for a shared understanding of humanities data to enhance data curation. Through interviews with 27 scholars, it identifies two ways scholars conceptualize data ‐ by format or role in research. It highlights three unique aspects: diverse requirements of materiality and processing levels, significance of authorship and perspective, and the dual role of tertiary sources. The study suggests prioritizing provenance, facilitating data documentation, curating tertiary sources for wider use, and establishing scholarly communication mechanisms for effective data curation.
A Cognitive Model of Data Retrieval Interaction
Authors: Li Xueyi , Li Qiao , Wang Ping , Hou Jingrui 
Published: October 2023

ABSTRACTThis study introduces and examines the “Multi‐dimensional Interaction‐Attitude‐Usage Model” (MIAU Model), drawing from cross‐disciplinary theories. The MIAU Model proposes dimensions of interactive data retrieval, including resource, technology, context, and dual‐process‐based cognition, and explores their relationships with user attitude toward systems and usage intention. To test the MIAU Model, a structural equation modeling analysis was conducted on the questionnaire data. The results support the proposed model. The MIAU Model suggests that resources, technology, contexts, and individual characteristics directly impact data searchers' dual‐process‐based cognition. System 1‐based cognition has a direct influence on system 2‐based cognition. Moreover, dual‐process‐based cognition and contexts directly affect attitude and usage intention. Additionally, resources, technology, contexts, and individual characteristics indirectly affect system 2‐based cognition through system 1‐based cognition, and similarly, these factors indirectly influence attitude and usage intention through dual‐process‐based cognition.
Informal Learning Trends on YouTube during the COVID‐19 Pandemic: A Topic Modeling Analysis
Authors: Lim Kok Khiang , Lee Chei Sian 
Published: October 2023

ABSTRACTThis study explores the impact of the COVID‐19 pandemic on informal online learning behavior through the lens of online video tutorials hosted on YouTube. Over 40,000 YouTube comments were collected for topic modeling analysis and uncovered thirteen latent topics related to three learning behavior types, that is, environment structuring, help‐seeking, and self‐evaluation. These learning behaviors underwent varying degrees of change after the pandemic declaration and normalized after that, highlighting the importance of adapting teaching methods to meet the changing needs of learners in response to any learning disruptions.
A New Ontology for Restaurant Review Sentiment Analysis
Authors: Luo Manman , Mu Xiangming 
Published: October 2023

ABSTRACTUnderstanding the aspects of a restaurant that contribute to people's sentiment is crucial for restaurant owners and marketers to improve customer experiences. A sentiment ontology for restaurant review sentiment analysis was proposed in this study. The proposed ontology identified six aspects of a restaurant evaluation: food, service, ambience, cleanliness, location, and price, based on 1,000 annotated Yelp data. Applying the proposed ontology in the annotated Yelp data showed that it helped improve the sentiment analysis accuracy by 11.2% on average. We believe that this study provides insights into the key factors that contribute to restaurant review sentiments.
Expanded Model of Everyday Information Practices with Information Avoidance in Digital Environments
Authors: Matsubayashi Mamiko 
Published: October 2023

ABSTRACTUntil recently, research on information behavior and practices has focused on a series of actions, including having information needs, seeking information to satisfy those needs, and using the acquired information to varying degrees. However, in digital environments with an enormous distribution of information, it is necessary to consider information practices by focusing on their relationship with negative behaviors, such as information avoidance. Based on the discourses by Japanese Canadian seniors on information behavior during the COVID‐19 pandemic, this study attempted to construct an expanded model of everyday information practices (EIP) that incorporates the concept of information avoidance into the EIP model proposed by Savolainen. Findings suggest that information avoidance is likely related to an individual's social context and that, as a result of information avoidance, different means of information acquisition are chosen from a person's stock of knowledge, resulting in different aspects of the individual's information practices.
Do Black‐Owned Restaurants Matter?: Yelp and Platform Visibility amid a Racial Reckoning
Authors: Moy Cameron , Bui Matthew 
Published: October 2023

ABSTRACTIn Spring 2020, the murder of George Floyd catalyzed calls for racial justice across the United States, ushering in a series of organizational and institutional responses. One response from Yelp, a popular review‐based platform, included its addition of a searchable Black‐owned attribute, a tag intended to signal its solidarity with Black businesses and communities. Analyzing a repository of over 300,000 Yelp reviews from Black and non‐Black‐owned restaurants in Los Angeles, CA, USA and Detroit, MI, USA, we pose the question: How did the addition of the Black‐owned tag impact the online reputation of Los Angeles and Detroit Black‐owned restaurants on Yelp? To examine this, we use restaurant review counts and average star ratings as proxy measures for online reputation and track these metrics over the year following the platform design intervention. We find that the addition of the Black‐owned tag did not create positive, sustainable change for Los Angeles and Detroit Black‐owned restaurants. In all, we call attention to the disparate impacts of platform design features on users and communities, especially for Yelp and digital platforms seeking to effect racial justice through novel platform design interventions.
Exploring the Information Privacy Practices of Persons with Diverse Sexual Orientation and Gender Identities (SOGI)
Authors: Nobbs Breanna 
Published: October 2023

ABSTRACTThis poster describes the research design to study the information behaviours of individuals with diverse sexual orientation and gender identities (SOGI) and how they negotiate between their personal privacy and their social and public identities in the digital world. In Australia, there is no legal right to privacy, and our increasing reliance on new technologies has created legal and regulatory challenges, especially for vulnerable populations such as persons with diverse SOGI. The poster will outline the literature review, research questions, aims, and methods guiding the research. Methods proposed for this study include an analysis of legal frameworks and policies, a survey of approximately 100 people with diverse SOGI about their use of digital social technologies, and in‐depth interviews with a sub‐set of self‐selected survey participants. Information behaviour theories and privacy literacy theories will be used to understand participants' behaviours and experiences regarding how they use digital social media, and the practices they have in place to manage their privacy.
Investigating the Intersections of Ethics and Artificial Intelligence in the Collections as Data Position Papers
Authors: Osti Giulia , Cushing Amber , Little Suzanne 
Published: October 2023

ABSTRACTA paradigm shift is currently underway with the emergence of the Collections as Data movement, which advocates the creation and dissemination of cultural heritage collections that are amenable to large‐scale computation to empower both collection managers and users. Although this discourse is beginning to gain some traction in the literature, critical evidence‐based assessments of the opportunities and risks of this process are underexplored. This paper presents the results of a content analysis of the official position statements (n = 83) produced in the Collections as Data forums and written by international professionals working with digital collections. Although preliminary, the analysis presented and discussed here sheds light on the initial reception of the idea of Collections as Data and its articulation in practice. The study represents the first systematic attempt to explore the complexities of the intersection of ethics and artificial intelligence in the context of cultural heritage, aiming at providing a valuable precedent for further elaboration and discussion.
Exploring an Online Community of Blind Programmers by Using Topic Modeling and Network Analysis
Authors: Park Jaihyun , Seo JooYoung , Lee Jae Young 
Published: October 2023

ABSTRACTMuch work has been carried out to highlight the accessibility challenges of blind programmers. Yet, relatively little has been known about how blind programmers help each other to solve problems. We present a data‐driven approach to explore collaborative problem‐solving of users in the Program‐l community of, by, and for blind programmers. We collected 8,344 longitudinal email threads from 778 users from 2004 through 2022 to observe the dynamics of collaborative problem‐solving among blind programmers. Our embedding‐based topic modeling and assortativity network analysis reveal that the knowledge of blind programmers diverges between when asking and answering questions. Our findings also suggest that users who have a high cluster level in the first year of activity and members are more likely to interact with other members with different roles. Our paper contributes to the field of social computing by introducing the first large‐scale study of a unique community of blind programmers.
From Digitization and Images to Text and Content: Transkribus as a Case Study
Authors: Prebor Gila 
Published: October 2023

ABSTRACTThis poster explores the potential of using technological tools, specifically the Transkribus platform, for the transcription of Hebrew manuscripts. The digitization of historical resources has made them accessible, but the textual content of the scanned images remains inaccessible. Transkribus, an AI‐powered platform, offers tools for text recognition, transcription, and search of historical documents. The poster discusses the process of automatic text recognition (ATR) and the challenges it faces, particularly in handling handwritten texts and Hebrew letters. It provides an overview of the Transkribus platform, its functionalities, and the training process for creating transcription models. The author presents a case study of transcribing a 15th‐century Sephardic semi‐cursive Hebrew manuscript using the Transkribus platform and evaluates the performance of different models. The poster concludes by discussing the implications and possibilities of using Transkribus for automatic transcription of historical Hebrew manuscripts. While the results show promising improvements in accuracy, further challenges and solutions are also discussed. Overall, Transkribus offers significant potential for the study and transcription of Hebrew manuscripts, revolutionizing the field of Jewish studies and historical research.
Knowledge Work Activities of a Systematic Review Task
Authors: Segura‐Rodas Stephanie , Griffin Martyn , Simpson Andrew , Toms Elaine 
Published: October 2023

ABSTRACTMost workers' activities in the workplace can be classed as knowledge work (KW). Previous research has described workers' tasks very broadly, making it difficult to know the actual work. We hypothesise that deconstructing what goes on inside a task could reveal many subtasks and activities at levels that are, as yet, unexamined and in need of deeper understanding. To explore this further, a data set collected from research fellows who described a specific task was examined. The task was broken down into many subtasks and activities, showing that one single task contains many levels of tasks. This understanding may allow for the development of tools to support the worker.
How Do Open Patents Affect Follow‐On Innovation? Evidence from Tesla
Authors: Shi Jing , Kang Lele , Chen Ye , Sun Jianjun 
Published: October 2023

ABSTRACTIn the past, high‐tech enterprises aimed to apply for patents to protect their innovation and obtain a competitive advantage. However, Open Innovation models encourage enterprises to open and exchange knowledge to accelerate technology development because of higher innovation complexity. Nonetheless, the impacts of open knowledge on follow‐on innovation are unclear. Tesla's patent openness event provides a better opportunity to observe a causal relationship between open knowledge and follow‐on innovation as it is an exogenous shock for the whole Electric Vehicle (EV) field. Against this backdrop, this poster uses patent data of Tesla and EVs before and after the open‐patent events from Derwent Innovations Index (DII) between 2003 and 2020. The difference‐in‐difference regression results show that patent openness has an inhibition effect on follow‐on patents and patentees and the high‐value open patents will strengthen this inhibition effect. Surprisingly, once technologies were shocked by openness, more open patents would stimulate them to boost in the future.
Automated Metadata Enhancement for Physical Sample Record Aggregation in the iSamples Project
Authors: Song Hyunju , Cui Hong , Vieglais Dave , Mandel Danny , Thomer Andrea K. 
Published: October 2023

ABSTRACTLarge amounts of samples have been collected and stored by different institutions and collections across the world. However, even the most carefully curated collections can appear incomplete when aggregated. To solve this problem and support the increasing multidisciplinary science conducted on these samples, we propose a method to support the FAIRness of the aggregation by augmenting the metadata of source records. Using a pipeline that is a combination of rule‐based and machine learning‐based procedures, we predict the missing values of the metadata fields of 4,388,514 samples. We use these inferred fields in our user interface to improve the reusability.
Result Assessment Tool: A Software Toolkit for Conducting Studies Based on Search Results
Authors: Sünkler Sebastian , Yagci Nurce , Sygulla Daniela , von Mach Sonja , Schultheiß Sebastian , Lewandowski Dirk 
Published: October 2023

ABSTRACTThe Result Assessment Tool (RAT) is a software toolkit for conducting research using results from commercial search engines and other information retrieval (IR) systems. This software combines modules used for the design and management of studies, the automatic collection of search results through web scraping, and the assessment of search results by jurors using different scales in an assessment interface. Due to the flexibility of RAT, several types of studies can be implemented, for example, classification studies and qualitative content analyses in addition to classic retrieval tests. Therefore, RAT is a versatile tool and useful in various disciplines.
Who Communicates Well with Data: Examining Data Literacy among Pre‐service Secondary Teachers
Authors: Tsai Tien‐I , Lee San 
Published: October 2023

ABSTRACTThe current study developed a data literacy instrument with 20 contextual questions and conducted a multi‐mode survey with 232 pre‐service secondary teachers in a university system. Three‐way ANOVA was used to test whether pre‐service teachers with different characteristics (i.e., field of study, library use, and Internet use) performed differently on data literacy. Pre‐service teachers got a decent overall percentage score. They performed better in “identifying problems” and “analyzing data” than in “transforming data” and “collecting data.” While pre‐service teachers in humanities and social sciences performed better in “identifying problems,” those in sciences performed better in “analyzing data.” Humanities pre‐service teachers with high Internet use scored significantly lower; social science pre‐service teachers with high Internet use and low library use scored significantly lower; science pre‐service teachers with low library use scored higher. Implications for future data literacy education and instrument design are discussed based on the preliminary findings.
Which Information Behavior Concepts Bridge the Gap from Research to Reference Practice?
Authors: VanScoy Amy , Merčun Tanja , Hands Africa , Švab Katarina , Kuhar Maja 
Published: October 2023

ABSTRACTAlthough there is much discussion of the theory/practice gap in library and information science, there is little research about how librarians use formal theory in their practice. Using a card sort and interviews, we explore the extent to which public librarians encounter or use theoretical concepts and models from information behavior in their reference practice. Results from our pilot study show that our procedures, including plain language descriptions of theoretical concepts and models printed on cards, are effective for eliciting examples of theory in practice. Librarians are clear about which concepts are relevant to their practice and can easily provide examples of real‐world application. Results of the study will suggest which theoretical concepts might be most important for instructors to teach to students in reference courses and which translate best from the research to the practice environment. In addition, the examples provided by librarians of how they use the concepts in their practice will be useful for instructors as they try to engage students in learning.