bluuebunny/crossref_metadata_2025_split huggingface dataset:
Challenges of Ovarian Cancer Patient and Caregiver Online Health Information Seeking
Authors: Chi Yu , Hui Vivian , Kunsak Hannah , Brusilovsky Peter , Donovan Heidi , He Daqing , Lee Young Ji 
Published: October 2021

AbstractOvarian cancer (OvCa) patients and caregivers have constant and evolving information needs. To meet their needs, they seek information from various resources, including online health information. Although about 60% of cancer patients are now using the Internet to meet their information needs, little is known about online health information seeking (OHIS) among OvCa patients and caregivers. To address this gap, we interviewed 18 OvCa patients and 2 family caregivers of OvCa patients and conducted content analysis on the transcribed data. We identified three challenges of OHIS: (1) lack of OvCa‐related knowledge, (2) poor quality of online information, and (3) inherent characteristics of OvCa, such as the high complexity and aggressive progression of the disease. The findings deepen the understanding of OvCa patients and caregivers and provide insights to better support their OHIS experience.
Discovery of a Hidden Pattern in Social Discussion
Authors: Choi Yunseon 
Published: October 2021

AbstractThis study investigates whether socially discussed book reviews would help understand the characteristics and features of books in selecting books for children. The study identifies users' interests in discussing books by analyzing the frequency of words used in their book reviews on a social networking site. This study also examines whether the patterns of word frequency would help understand the features of books. The findings of this study identify the aspects of a book that users are concerned about in reviewing the books. The results also reveal that online book reviews help us understand the specific features of books and user behavior in discussing books on a social networking site. This study has implications for providing practical insights into the intrinsic values of users' book reviews in discovering a pattern of social discussion.
Analyzing Readers' Responses to Fake News on Facebook
Authors: Chua Alton Y.K. , Chen Xiaoyu 
Published: October 2021

AbstractThis paper investigates how different framings of fake news on social protests are related to readers' responses on Facebook. A 2 (news standpoint: pro‐protest vs. pro‐establishment) × 2 (violence description: protesters' violence vs. police’ violence) within‐participants web‐based experimental survey (N = 90) was used to study readers’ intention to like, share, and comment on Facebook. Results suggested that exposure to different framings of fake news led readers to respond differently on Facebook. Moreover, the intention to click “Like” did not necessarily translate to the intention to click “Share” or “Comment” and vice versa. This paper concludes with theoretical implications, practical implications, and limitations.
Boundary Crossing in Online Community of Practice: “Between Art and Quarantine”
Authors: Dedema Meredith , Fichman Pnina 
Published: October 2021

ABSTRACT“Between art and quarantine” became a popular social media challenge during the COVID 19 lockdown. Thousands of users posted art recreations and formed several online communities of practice (CoPs) around this common interest. The boundaries of some of these CoPs are more permeable than others and they all utilize Instagram visual affordances to cross language barriers. We aim to gain a better understanding of the unique boundaries within and between these CoPs and their boundary crossing processes. Initial analysis of 1,555 posts reveals patterns of overlap and the roles of boundary brokers and boundary objects; yet, further in‐depth analysis is still needed, to gain a better understanding of the visual and cross language boundary crossing that is at play within and between these CoPs.
A Peek into the US Informal STEM Landscape through Theconnectory.org
Authors: Deimen Sebastian , Cui Hong , Higgins Michelle 
Published: October 2021

AbstractIt's well‐known that informal STEM learning is a critical component of STEM education. However, there is not a comprehensive directory, at the state or national level, listing informal STEM programs offered in the US. This makes it difficult to assess the national landscape of informal STEM programs. Theconnectory.org is by far the most comprehensive listing that aims to connect learners and volunteers to informal STEM learning opportunities. In this poster, we present the results from a data analytics project using the informal STEM program information collected through theconnectory.org API to sketch a preliminary picture of what kind of programs are offered and what audiences are targeted. Theconnectory.org has the potential to become a primary resource for STEM learners, educators, and policymakers. There are ways the ASIST community (faculty and students) can help enrich this resource.
Information Organization and Information Retrieval in the LIS Curriculum
Authors: Dobreski Brian , Zhu Xiaohua , Yang Tao , Ridenour Laura 
Published: October 2021

AbstractWithin LIS programs, information organization (IO) and information retrieval (IR) serve as foundational topics of instruction. While traditionally represented by required, dedicated courses in LIS curricula, they may now appear as a combined course or in combination with other topics across required courses. The present analysis of 58 IO/IR‐related course syllabi is part of a larger project examining the interrelation of IO and IR instruction across current ALA‐accredited LIS curricula. Preliminary results presented here show significant IO and IR coverage in a range of course types, as well as the heavily applied nature of IR instruction and the movement of IO instruction toward more emergent topics.
Street Art as Visual Information: Mixed Methods Approach to Analyzing Community Spaces
Authors: Dozal Laura W. 
Published: October 2021

AbstractThis paper uses a mixed method approach to analyze how a community space can be perceived by a visual information via physical spaces. In this analysis, Street Art images are considered as a type of visual information that can represent a specific perception of a community as a member of a community space. While understanding community attributes through perceptual tools we can use social network analysis methodology to understand how different neighborhoods are connected and how they might differ. The results show that specific neighborhood traits, urban, population, culture contribute to stronger ties within the Street Art community network.
Information Flow and Social Organization in a Bitcoin Discussion Network on Twitter
Authors: Færch Celina Jepsen , Sen Poon Sze , Yunqian Tian 
Published: October 2021

AbstractThis study investigates the information flow and social organization in a Bitcoin discussion network on Twitter (BDN), using social network analysis to examine user‐user interactions. Results suggest that BDN presents a heterogenous degree distribution, where most users have few interactions. A myriad of weakly defined but well‐connected subcommunities enables efficient information flow in the network. BDN emanates a small‐world effect, without the dominance of a few influential users. “Star‐power agents,” such as Elon Musk, are popular references among users, but the network is driven bottom‐up by smaller “two‐sided” users. This explorative study demonstrates how the classification of different users can be used in analyzing online communities. Future research could compare the network structure of BDN with other networks and utilize sentiment analysis to analyze the quality of information.
Is Gamification Effortful? A Study in the Crowdsourcing Context
Authors: Goh Dion Hoe‐Lian , Dan Yi , Huang Tiantian , Zhang Mengtian , Lee Chei Sian 
Published: October 2021

AbstractResearchers have claimed that gamification adds to the workload of users, potentially influencing their perceptions of effort and performance expectancy negatively. Through an experimental study which compared a gamified and a non‐gamified mobile app for crowdsourcing restaurant reviews, we found participants had similar perceptions of effort and performance expectancy, contrary to expectations,. Interestingly, participants perceived reviews in the gamified application to be more accurate. There were also more reviews made in the gamified application.
Radical Empathy in the University Archives: Examining Archival Representations of Chinese Students from 1906 to 1920
Authors: Han Ruohua , Han Yingying 
Published: October 2021

AbstractWith the increase in Anti‐Asian hate crimes in the United States in 2020, it is essential for information institutions to reflect on how they are confronting the oppression of Asian communities. Guided by the concept of radical empathy, we conducted an analysis on how historical Chinese students at the University of Illinois were documented and described in the university's archives. Relevant archival materials, descriptive metadata, and additional archives‐generated materials were examined to identify potential representation issues. The preliminary findings include: (1) Chinese students are mostly visible in registers and yearbooks, with some well‐known alumni also appearing in newspapers and correspondence; (2) Some culturally insensitive terms occasionally appeared in historical student newspaper articles; (3) Name variations related to Chinese “courtesy names” and hyphenations can lead to challenges in creating descriptive metadata and affect the discoverability of Chinese students in the archives.
Clusters, Stars, and Hashtags: Understanding Librarians’ Professional Online Networks
Authors: Hicks Deborah 
Published: October 2021

ABSTRACTTwitter serves as a platform for librarians to connect with each other and discuss, debate, and find consensus around professional issues. Using Social Network Analysis and participant interviews, the Twitter conversations that coalesced around the hashtags #NoHateALA and #IStandWithALA, with particular attention to the role of central actors, are examined. Findings reveal that five Twitter accounts were responsible for 75.5% of all posts under these hashtags out of 1693 posters. In interviews, some of the central actors indicated that their centrality in these networks was deliberate and part of a larger activist agenda. Understanding the depth and breadth of the online network, alongside an understanding of how and why the central actors took on such important roles in the network sheds light on how librarians use online tools to connect and debate professional issues and effect important professional changes.
What Does Channel Say? Understanding How Social Media Social Capital Facilitates COVID‐19‐Related Information‐Seeking and Opinion‐Expression on Two Types of Platforms: User‐oriented versus Content‐oriented
Authors: Hu Junwen 
Published: October 2021

AbstractSocial capital (i.e., resources obtained from social relationships) facilitates informational use of media, yet how in detail the mechanism functions in a multi‐platform social media environment remains underexplored. Taking an affordance approach, this study aimed to investigate the differentiated effects of social media social capital on COVID‐19‐related information behaviors on user‐oriented and content‐oriented social media (USM&CSM). It was hypothesized that information exposure on USM mediates the relationship between social capital and information‐seeking intention, whereas exposure on CSM was expected to mediate the relationship between social capital and opinion expression. Web‐based survey data collected among Chinese social media users (N = 256) supported the hypotheses, and in‐depth interviews (N = 15) further revealed how people explored the affordances of different platforms to enjoy the information resources. Implications were discussed.
A Critical Discourse Analysis of the Hashtag #WeAreAllIsraaGhrayeb on Twitter: An Exploration of Honor Killing Crimes in Palestine
Authors: Jaber Baheya 
Published: October 2021

AbstractThis research investigates a crucial social justice concern “honor killing” that are affecting women worldwide especially in Palestine. Feminist theory and critical theory provide a lens to explore issues of gender inequality, patriarchy, and oppression. The researcher utilized qualitative research method based on critical discourse analysis of the Twitter hashtag #WeAreAllIsraaGhrayeb between August 22 – September 22, 2019. Analyzing the tweets identified three themes: tweeters' anger and frustration against the killing of Israa Ghrayeb, the impact of honor killing crimes within the Palestinian community, and an urgent call for justice by action. The author is a participatory action researcher (PAR) who gained an experiential understanding and deeper insights of cultural relevance to address contemporary issues and to contextualize a cultural reality to benefit stakeholders (i.e., entities or individuals who witnessed the horrors of honor killing) by developing a strategic action plan that can bring social change leading to a just society.
Appraising Research Data for Long‐Term Preservation: An Analysis of Research Data Collection Policies
Authors: Kim Jeonghyun , Faulkner James 
Published: October 2021

AbstractTraditionally, research data has been managed independently by individual researchers and only shared at the discretion of the researcher upon request. Appraisal and selection of research data has become a major issue in recent years as the number of data types and volume of data have grown greatly, but little empirical study has been done regarding how academic libraries document their research data appraisal practices. This study surveyed academic libraries' research data collection policies, which govern the identification, appraisal, and selection of research data. A total of 17 academic libraries' research data collection policies were examined in this study.
Synchronous Ideation Workshop with Rural Library Professionals to Envision Future Makerspaces
Authors: Kim Soo Hyeon 
Published: October 2021

AbstractIdeation can support the development of educational programs and services at public libraries. Prior studies on ideation workshops focus on face‐to‐face settings; less is known about synchronous ideation workshops with library professionals with limited design experience. This paper reports on the results of a reflective case study of an online ideation workshop with three rural library professionals to envision future makerspaces. Preliminary findings suggest design considerations for a synchronous ideation workshop around librarian experience, design space, and technology.
Out of the Past: The Challenges of B.C.E. Dates in Metadata
Authors: Klose Annamarie C. , Goldstein Scott , Levy Morris 
Published: October 2021

AbstractWhile well‐established standards for encoding date metadata exist, Before Common Era (BCE) dates, previously referred to as Before Christ (BC) dates, are a challenge. Libraries, archives, and museums have a rich variety of artifacts from this era. However, the lack of encoding or underuse of available standards hinders the ability to search and browse for this content. While several metadata standards support encoding of BCE dates, the full capability is often not exploited. By analyzing metadata in the Digital Public Library of America (DPLA, https://dp.la/), the authors examine the benefits and limitations of the Extended Date Time Format (EDTF) and related interoperability issues.
Public Engagement with Science via Social Media: A Case of Communicating the Pandemic on Twitter
Authors: Knox Emma , Hara Noriko 
Published: October 2021

AbstractThe poster describes a project which analyzes interactions between laypeople and experts via social media. Our aim is to understand how experts and the general public interact with each other on social media, and how we can use current data to improve these interactions in the future. We created a Twitter bot to obtain data from 15 COVID‐19 experts and 7 federal government‐sponsored public health organizations from English‐speaking countries. The data were analyzed in R to investigate the relationships among Followers, Favorites, Retweets, and Hashtag Count per tweet. The preliminary analysis indicated statistically significant differences between various variables including: Number of Favorites, Number of Retweets, Number of Hashtags, and Number of Followers; the results shed light on the current relationship between the public and experts on social media.
Understanding the Temporal Effects on Tweetcussion of COVID‐19 Vaccine
Authors: Lee Chei Sian , Goh Dion Hoe‐Lian , Tan Han Wei , Zheng Han , Theng Yin Leng 
Published: October 2021

AbstractIn the fight against COVID‐19, the Pfizer and BioNTech vaccine announcement marked a significant turning point. Analysing the topics discussed surrounding the announcement is critical to shed light on how people respond to the vaccination against COVID‐19. Specifically, since the COVID‐19 vaccine was developed at unprecedented speed, different segments of the public with a different understanding of the issues may react and respond differently. We analysed Twitter tweets to uncover the issues surrounding people's discussion of the vaccination against COVID‐19. Through the use of Latent Dirichlet Allocation (LDA), nine topics were identified pertaining to vaccine‐related tweets. We analysed the temporal differences in the nine topics, prior and after the official vaccine announcement.
A Survey of Exclusively Data Journals and How They Are Indexed by Scientific Databases
Authors: Li Kai , Lu Chuyi , Jiao Chenyue 
Published: October 2021

ABSTRACTAs data becomes omnipresent in the scientific system, a new academic genre aiming to describe data objects (data papers) and the venue to publish these articles (data journals) gradually emerged from the end of the 2000s. However, it is largely unknown how much these scientific outputs are indexed in scientific databases, which has greatly prevented them from being thoroughly studied in large‐scale, quantitative studies. This poster presents our preliminary efforts to address this gap, by compiling a list of data journals that primarily accept data papers (i.e., exclusively data journals) and examining their presence in four major scientific databases. Our results indicate that exclusively data journals are comprehensively indexed in Crossref and Dimensions, two relatively new scientific databases, which can be used to conduct future studies on data papers and journals. The next steps of our project are also discussed in this poster.
XR Accessibility Initiatives in Academic Libraries
Authors: Lischer‐Katz Zack , Clark Jasmine 
Published: October 2021

AbstractVirtual reality and other extended reality (XR) technologies are being integrated into academic libraries to support research and teaching in innovative ways; however, new technologies are often adopted without considering disabled users. XR accessibility depends on establishing appropriate policies and best practices. This paper examines the current state of XR accessibility initiatives in academic libraries by reporting findings from a survey sent to the academic library community from February to May 2021.
Exploring the Computational Recovery of the Typographical Logic of Book Indexes as Paratext for Improving Navigation within Digitized Historical Texts with Semantic Model
Authors: Liu Huapu , MacCall Steven , Lewis Nicole 
Published: October 2021

AbstractThe rapid growth in the number of digital texts has posed challenges for information professionals to make them more navigable and usable. These challenges have prompted researchers to develop different approaches to creating semantic descriptions for these resources aiming at more efficient and effective navigation and granular access to specific textual content. In this poster, we report on ongoing work that utilizes cluster‐oriented machine learning algorithms to recover the logical relationships embedded in the typographical layout of book indexes, structures that are lost when standard page‐level OCR scanning techniques are deployed on the index pages of digitized historical books. Recovering typographical logic would aid in the construction of semantic representation of indexes that can provide granular access to digital texts thus improving textual navigation.
Modeling the Preferences of Demographical Reading History: A Primary Case Study of a Public Library in Shanghai
Authors: Lou Wen , Chen Jingjing 
Published: October 2021

AbstractReading habits are influenced by various aspects, such as personal characteristics, reading history and book characteristics. It remains uncertain that which factor determines reader's choice. In this primary work, we attempt to model the preferences based on readers’ demographical information to examine the impact factors on their reading habits. We selected all the reading information of Shanghai Pudong Library in 2015 as the dataset. By applying the logistical regression and likelihood ratio tests, we found that readers’ stickiness, gender, and books’ publication time significantly influence readers’ preferences. Future work will focus on facilitating the model and expanding the data.
A Structural Topic Model Analysis of Privacy in Mandarin Chinese News: 2010–2019
Authors: Ma Yuanye 
Published: October 2021

AbstractThis poster presents a study that analyzes privacy using a 10‐year privacy news corpus in Mandarin Chinese, using an unsupervised machine learning technique, structural topic modeling (stm). The 13 topics revealed several dimensions for understanding privacy in the Chinese language, including how privacy is concerned, by who, and in what context/domain. This study is one of the first empirically‐rounded explorations of the concept of privacy in the current Chinese language. Findings from this study could be used to further the discussion and investigation to understand privacy as an intercultural information ethics concept.
Towards Identifying, Understanding and Controlling Cumulative Revelations in Social Media
Authors: Nicol Emma , Htait Amal , Azzopardi Leif , Moncur Wendy 
Published: October 2021

AbstractEvery day, people post information about themselves and others on online social networks, making such information accessible within their social circles but also, potentially, way beyond. While the information posted may seem benign or innocuous, small pieces of information, when tied together, can potentially reveal much more about the person than intended. Such cumulative revelations could expose them to risks such as identity theft, fraud or loss of employment. This paper describes findings from interviews about people's online interactions, focusing on their requirements and desires for improved ways to identify, understand and control cumulative revelations arising from their social media profiles that could put them at risk of grave consequences. These findings motivate our future work on how to better raise awareness among social media users of the risks and consequences to which combinations of posts may lead.
Breaking the Information Cocoon: When Do People Actively Seek Conflicting Information?
Authors: Peng Hanqi , Liu Chang 
Published: October 2021

AbstractInfluenced by existing beliefs, people are often biased in favor of information that supports their attitudes, intensifying the information cocoon effect. To break information cocoon and promote open‐minded searches, it is important to guide seekers to approach to conflicting information and formulate critical thinking. This study aimed to examine when and why people actively seek conflicting information using grounded theory. Specifically, we interviewed 13 people who have experiences of actively seeking conflicting information. All the transcript data were coded for analysis. The results demonstrated that context, user characteristics, and motivation were the three main factors that led users to seek conflicting information actively and influenced seekers' preferences of information. Finally, we define this type of search tasks as “attitude tasks,” and call for more attention on this type of tasks.