bluuebunny/crossref_metadata_2025 huggingface dataset:
Research, impact, value and library and information science (RIVAL): Development, implementation and outcomes of a Scottish network for LIS researchers and practitioners
Authors: Hall Hazel , Ryan Bruce
Published: October 2020

The research‐practice gap in Library and Information Science (LIS) is well documented, especially in respect of the difficulties of translating research into practice, and resultant lost opportunities. While many researchers attempt to explain this research‐practice gap, few suggest strategies to address it. The creation of researcher‐practitioner networks, however, is one approach that has been proved empirically to bridge the distance between the two communities. Such a network is currently operating in Scotland, funded by the Royal Society of Edinburgh. Research, Impact, Value and Library and Information Science (RIVAL) is part‐way through its implementation based around four knowledge exchange events for a network membership of 32 from a wide variety of LIS sectors. RIVAL's successful delivery depends in part on the project leads' experience of undertaking, and evaluating the impact of, a UK Arts and Humanities Research Council funded grant: the Developing Research Excellence and Methods (DREaM) project. Already there are indications that RIVAL is delivering value to network members. There is a strong expectation for this to be enhanced, both in the remainder of the funding period and beyond, offering theoretical contributions to the study of social networks, especially in respect of social capital development to support knowledge exchange.
From cooperation to collaboration: Developing and implementing a research‐based framework for information organizations
Authors: Saunders Laura , Hinchliffe Lisa Janicke , Wong Melissa
Published: October 2020

Information professionals are expected to engage in collaboration in developing and delivering programs and services, creating systems, and conducting research, as evidenced by attention to collaboration in various standards and guidelines. However, when assessed against a collaboration spectrum (Himmelman, Collaboration defined: A developmental continuum of change strategies, 2002) many existing collaborative projects lack the characteristics of an integrated partnership, meaning they may not be reaping the full benefits of collaboration, including ability to leverage each other's resources, expertise, and respective audiences. In this session, the presenters will share their Framework for Collaboration (Saunders & Corning, The Journal of Library Administration, 2020, 60), reviewing common barriers to collaboration and discussing approaches for overcoming those barriers. They will share best practices for meaningful collaboration, including identifying community needs and potential partners; aligning vision and goals; and implementing and managing a successful collaboration.
Conceptualizing and studying information creation: From production and processes to makers and making
Authors: Huvila Isto , Douglas Jennifer , Gorichanaz Tim , Koh Kyungwon , Suorsa Anna
Published: October 2020

An emerging body of literature has begun to address the earlier under‐researched topic of information creation. This panel inquires into the state‐of‐the‐art of research on information creation to highlight how different conceptualisations of information creation can foreground various key aspects of how information is made and produced, what types of actors and activities are involved, how information creation can be studied empirically, and what novel insights can be drawn to support practitioners, for instance, in information literacy instruction, information organisation and management, and information systems and services development.
Employing word mover's distance for cross‐lingual plagiarized text detection
Authors: Chang Chia‐Ming , Chang Chia‐Hsuan , Hwang San‐Yih
Published: October 2020

While the blossom of globalization has achieved many successes, cross‐lingual plagiarism, however, has become popular. Detecting plagiarism across languages requires the capability of comparing semantical similarities between texts of different languages. Previous works rely on massive bilingual resources such as comparable corpus, parallel corpus, and even commercial machine translation as references. However, towards domain‐specific applications, collecting such resources is labor‐intensive and impractical. Also, the absence of interpretability of existing methods lead to the difficulty of investigating retrieval results by humans. Hence, it is imperative to have a resource‐light and interpretable method for cross‐lingual plagiarism detection. In this study, we propose a new detection method, called CL‐WMD, which is built upon word embedding techniques. CL‐WMD requires only a small set of translation pairs to constitute a bilingual reference and calculates semantical distances between texts by word mover's distance, which can provide explicable word alignment information between two compared text spans. Our experiments are conducted under a bilingual scientific publication corpus composed of two typologically diverse languages: English and Chinese. The results demonstrate that CL‐WMD has higher accuracy than most existing methods and achieves better or comparable performance when compared to the translation‐based method in paragraph‐level and sentence‐level plagiarism detection tasks.
Mechanical Turk or volunteer participant? Comparing the two samples in the study of intelligent personal assistants
Authors: Lopatovska Irene , Korshakova Elena
Published: October 2020

A challenge in academic and practitioner research is recruiting study participants that match target demographics, possess a desired skillset, and will participate for little to no compensation. An alternative to traditional participant recruitment struggles is crowdsourcing participants through online labor markets, such as Amazon Mechanical Turk (AMT). AMT is a platform that provides the tool for finding and recruiting participants with diverse demographics, skills, and experiences. This paper aims to demystify the use of crowdsourcing, and particularly AMT, by comparing the performance of traditionally recruited volunteers and AMT participants on tasks related to the evaluation of intelligent personal assistants (IPAs such as Amazon Alexa, Google Assistant, Apple Siri, and Microsoft Cortana). The comparison of AMT and non‐AMT samples indicated that while the two samples differed on demographics, their task performance was not significantly different. The paper discusses the costs and benefits of using AMT samples and would be of particular relevance to researchers who employ questionnaires and/or task‐specific data collection methods in their work.
University presses' e‐book dissemination strategies for academic library customers: An exploratory study
Authors: Zhang Mei
Published: October 2020

This work‐in‐progress paper examines university presses' e‐book dissemination strategies by focusing on how presses choose certain ways to distribute their e‐books to academic library customers, and the factors supporting their decisions. The study conducted five one‐on‐one interviews with employees from different university presses in the U.S. The preliminary findings reveal that although all participating university presses provided their e‐books to four main vendors, these presses adopted different strategies to distribute their e‐books to different vendors. Further, this study listed the factors affecting university presses' decision on their e‐book dissemination strategies, including increasing exposure of their e‐books, concerns about adding new vendors, and the vendors' imposition of DRM on e‐books. Then this study, by linking the findings to the framework of cultural commodity, argues that the university presses' dissemination strategies demonstrate their effort to reduce the fragility of their e‐books as a cultural commodity.
Supporting refugees by facilitating the innovation of nonprofit resettlement agencies: A case study
Authors: Freeburg Darin S.
Published: October 2020

This study tested the implementation of the Information for Innovation model (IIM). The IIM posits that to implement innovations and adapt to external change, nonprofits must increase both the inward and outward flow of information. This increased flow comes through experimentation, information‐seeking, and self‐expression. Over 1 year, the researcher implemented the model with a refugee resettlement nonprofit in the Southeastern U.S. A case study design was used, following the approach of Community‐Based Participatory Research (CBPR). The implementation of the IIM followed the structure of Communities of Practice (COP), and participants held several face‐to‐face meetings and engaged in virtual information‐seeking. Results show that increases in information‐seeking improved the nonprofit's confidence in its ability to manage change. Improvements in self‐expression enabled the nonprofit to benefit more fully from the diversity of existing staff. Yet, the IIM's impact on implementation was limited by lack of resources. This study contributes to literature on the expansion of Library and Information Science (LIS) into communities by proposing an evidence‐based approach to working with nonprofits. This study also contributes to literature on the role of LIS in refugee populations, suggesting that these institutions work more directly with the nonprofits whose expertise and funding most directly supports refugees.
Emotions in online debates: Tales from 4Forums and ConvinceMe
Authors: Li Jinfen , Xiao Lu
Published: October 2020

It is increasingly common for people to debate over various topics through online debate forums. While it has been shown that participants' emotional states affect debate processes and outcomes, it is unknown how different types of emotions are represented in online debates and what correlations exist between the emotions and other aspects of the debates such as their debate topic. We conduct a large‐scale analysis of the emotions in two online debate forums, namely, 4Forums and ConvinceMe. Specifically, we first develop an emotion recognition algorithm that uses multiple channels BLSTM with a feedforward attention mechanism, which outperforms the state‐of‐the‐art emotion recognition algorithm. Next, we label the emotions of each comment in the selected 4Forums and ConvinceMe discussions and analyze various aspects of the emotion's influence in the online debates. We observe that certain types of emotions are more likely dependent on the debate topic, and the prevalence of different emotions is independent of the individual discussions. We also observe emotion contagion between a comment and the immediately previous comment. We investigate the emotions of different types of respondents are less likely to express joy when they disagree and more likely to express disgust when they attack or disrespect to others.
The effects of suggested tags and autocomplete features on social tagging behaviors
Authors: Holstrom Chris
Published: October 2020

Many websites employ social tagging to allow users to label and classify information. These tagging user interfaces use a variety of features to support efficient and consistent tag creation, including suggested tags and autocomplete for tags. This study uses a custom‐built tagging interface in a controlled experiment to determine how these features affect social tagging behavior. The study finds that suggested tags do not have a significant effect on the number of tags, number of unique tags, number of typos, or time elapsed per tagged provided. However, autocomplete significantly increases the number and consistency of tags provided, significantly decreases the rate of typos, and significantly decreases the elapsed time per tag provided. These findings for the autocomplete feature align with the priorities and constraints of social tagging folksonomies that support retrieval and site navigation and suggest that autocomplete is an important aid for text entry in social tagging user interfaces.
Analyzing health tweets of LGB and transgender individuals
Authors: Karami Amir , Webb Frank
Published: October 2020

There are millions of LGB and transgender individuals in the world. However, conducting LGBT health‐related studies are labor‐intensive and time‐consuming because of the challenges inherent in studying these hidden populations. Social media sites like Twitter provide a platform for LGBT users to share their health concerns, giving researchers the opportunity to collect and analyze these social comments. This research used a mixed method to examine the linguistic and semantic characteristics of health‐related tweets shared by self‐identified LGBT individuals. Findings uncovered several health‐related topics shared by LGBT users. Further, while LGB and transgender communities are within the LGBT umbrella, we found a significant linguistic difference between the tweets shared by LGB and transgender individuals. These findings show further disparities within an already marginalized group, indicating the need for customized healthcare to improve the health of all people. Our research approach can also inform studies in the areas of informatics, health, and medicine for analyzing the health concerns of not only sexual and gender minorities but also other hidden populations.
“Dear Amy”: Seeking support on YouTube
Authors: Salib Gabrielle , Gorichanaz Tim , Agosto Denise E.
Published: October 2020

Among many other video genres, YouTube is a hub for “how‐to” videos, including advice on how to work through difficult life circumstances. For this pilot study, we investigated a sample of comments in response to two Amy Poehler's Smart Girls' “Ask Me Anything” videos. Geared toward adolescents and emerging adults, “Ask Me Anything” videos respond to viewer questions on social, personal, and professional topics, such as coping with embarrassment, worries about school exams, relationship power dynamics, and general life stress. In our analysis, we identify emerging trends in the language of viewers' response comments and investigate (a) how viewers are responding to the videos, and (b) what such responses could mean for the design of social computing systems and their use for social and emotional support. We find indications of users' emotional support seeking, evidence of adult audience members' seeking to answer younger responders' questions posted in response to the videos, and the use of epistolary forms to express perceived emotional connections with the video host. In future work, we will seek to understand what elements of the videos are invoking such personal connections and explore designs of social computing systems to better support personal connection and intergenerational support online.
Finite and infinite games: An ethnography of institutional logics in research software sustainability
Authors: Weber Nicholas
Published: October 2020

Modern research is inescapably digital, with data and publications most often created, analyzed, and stored electronically, using tools and methods expressed in software. While some of this software is general‐purpose office software, a great deal of it is developed specifically for research, often by researchers themselves. Research software is essential to progress in science, engineering, and all other fields, but it is often not developed, shared, or stored in a sustainable way. The following paper presents findings from an ethnography of two research software projects that have, over the last 10 years, cooperatively organized development efforts to produce important software enabling scientific breakthroughs in both astronomy and macromolecular modeling. The work of these two projects are framed in terms of James Carse's model of finite and infinite games. I argue that by incentivizing institutional governance that resembles the design of an infinite game, funding agencies can increase the sustainability of research software and improve various aspects of data‐driven scientific discovery.
How to undertake ideologically contentious research: Leaning on reflexivity and positionality to address uncomfortable disjuncture's in information research
Authors: Oltmann Shannon M. , Barriage Sarah , Greyson Devon , Vaughn Matthew
Published: October 2020

In this 40‐minute panel, four researchers who study contentious issues will discuss those topics and address how they navigate ideological disagreements with their research participants. Reflexivity and positionality are two analytical tools that are useful in this process of unpacking research. We describe these concepts and position our own research within these spaces.
Considering individual and community contexts within information pedagogy, scholarship, and practice
Authors: Roeschley Ana , Buchanan Sarah A. , Burke Mary , Graf Ann , Zavalina Oksana L.
Published: October 2020

Context—“the complex web of social relations which [the individual] inhabits” (Spratt & Florian, Teaching and Teacher Education, 2015, 49, 89–96, p. 90) touches everything, including individual and group circumstances, positionalities, feelings, experiences, and environments. Context shapes not only how we communicate information in the field and in the classroom, but also several significant processes: searching for information, accessing information, and the interpretation and use of information (Encheva, Journal of Library Administration, 2016, 56, 595–602; Mitchell, Technical Services Quarterly, 2017, 34, 283–296; Yeo et al., The Annals of the American Academy of Political and Social Science, 2015, 658, 172–191). Furthermore, such contexts affect how information scientists teach and conduct their research and how information (in a classroom setting or otherwise) can be delivered to individuals and communities for action. How we, as information scholars and professionals, take individual and community contexts into account will affect our work. Issues of context will be thoroughly interrogated from a number of different perspectives by both the panelists and audience members in this interactive and participation‐based session.
Standing out in the academic LIS job market: An interactive panel not just for doctoral students
Authors: Agarwal Naresh Kumar , Oh Kyong Eun , Williams Rachel D. , Freeburg Darin , Rosenbaum Howard , Kwaśnik Barbara H.
Published: October 2020

This proposal builds on the previous successes of the interactive panels sponsored by the ASIS&T Special Interest Group on Education (SIG ED) at the 2017, 2015, 2013, 2012, and 2011 annual meetings. The all‐new 2020 panel features faculty in various stages of their academic careers, including a relatively new assistant professor, one who has just completed the tenure process, two associate professors, a full professor, and a professor emerita. The panelists are prepared to address audience questions on topics such as the traditional academic job market, alternative career paths including post‐doctoral opportunities, development of personal research agendas, challenges of online instruction (Sithole et al., International Journal of Online Pedagogy and Course Design, 2019, 9, 62–77), as well as the challenges and disruption caused in higher education due to the COVID‐19 situation (Amour, Coronavirus News Roundup for April 21, 2020). The panel discussion will focus around the academic job market and how applicants can present themselves in the best light depending upon the type of position sought. Doctoral students will gain valuable insights on finishing their dissertation, weighing postdoctoral opportunities, and preparing for their first academic position. The panel will be useful not only to doctoral students but also to postdocs, adjuncts, and assistant‐to‐associate‐to‐full professors, as the panelists share their insights and experience through various career stages.
ASIST AM 2020. SIG HFIS panel proposal April 27, 2020
Authors: La Barre Kathryn , Burke Colin , Buckland Michael K. , Gorichanaz Tim
Published: October 2020

A progress report and discussion on the preservation of, and access to, historical resources relating to the history of ASIST and of Information Science and Technology generally and guidance for members interested on opportunities and methods.
Making as imaginative crossroads: Ghanaian makers and the geopolitics of technological progress
Authors: Avle Seyram
Published: October 2020

This paper is about the politics of technological progress as it is being played out among a loose network of Ghanaian makers. It unpacks how the practice of ‘making’ unfolds as a site for positioning the self and the nation within a global imaginary of techno futures. The paper argues, first, that ‘making’ in Ghana is emblematic of a crossroads of imaginative possibilities for technological design and production, and second, that this marks a distinct turn in the politics of technological progress, particularly when situated against ongoing econo‐political negotiations between the Global south, the West, and China.
Identifying data‐focused curriculum in worldwide iSchools: Preliminary data acquisition for Asia‐Pacific and European members
Authors: Jeng Wei , Tsai Fu‐Hsuan , Lee Jian‐Sin
Published: October 2020

This paper reports the data cleansing and labeling procedures for identifying 215 data‐focused courses from 1,627 courses offered in 22 iSchool members as of 2019. This preliminary data acquisition is to serve as a starting point for further conducting regular, greater‐scaled data acquisition in data‐focused curriculum across all the iSchools in the near future. The challenges we encountered preliminary data collection include course catalog unavailability, disambiguation, and lack of data for investigating the evolution of courses. Next steps of this study are to expand our data collection to all the iSchool members and create an interactive data dashboard with periodically automatic data acquisition over time. We anticipate such public datasets and interactive visualizations are beneficial for iSchool educators and researchers who are interested in the development of data‐focused curricula, as well as potential students.
Targeting precision: A hybrid scientific relation extraction pipeline for improved scholarly knowledge organization
Authors: Jiang Ming , D'Souza Jennifer , Auer Sören , Downie J. Stephen
Published: October 2020

Knowledge graphs have been successfully built from unstructured texts in general domains such as newswire by leveraging distant supervision relation signals from linked data repositories such as DBpedia. In contrast, the lack of a comprehensive ontology of scholarly relations makes it difficult to similarly adopt distant supervision to create knowledge graphs over scholarly articles. In light of this difficulty, we propose a hybrid approach to extract scientific concept relations from scholarly publications by: (a) utilizing syntactic rules as a form of distant supervision to link related scientific term pairs; and (b) training a classifier to further identify the relation type per pair. Our system targets a high‐precision performance objective as opposed to high recall, aiming to reduce the noisy results albeit at the cost of extracting fewer relations when building scholarly knowledge graphs over massive‐scale publications. Results on two benchmark datasets show that our hybrid system surpasses the state‐of‐the‐art with an overall 60% F1 score led by the nearly 15% precision boost in identifying related scientific concepts. We further achieved an overall F1 in the range 34.1% to 51.2%, on relation classification, per experimental dataset.
“When someone sees me, I am nothing of the norm”: Examining the discursive role power plays in shaping LGBTQ+ health information practices
Authors: Kitzie Vanessa L. , Wagner Travis L. , Vera A. Nick
Published: October 2020

This paper examines how discursive power shapes LGBTQ+ community health information practices. Informed by analysis of 10 information world maps drawn by SC LGBTQ+ community leaders, our findings indicate that while community can be a valuable construct to reject mainstream discourses of regulation and correction, it inevitably is fraught and not representative of all LGBTQ+ individuals. Findings can inform strategies for community leaders to facilitate more equitable information flow among members by identifying key structural elements impeding this flow at the community level.
Don't judge a journal by its cover?: Appearance of a Journal's website as predictor of blacklisted Open‐Access status
Authors: Liang Lizhen , Acuna Daniel
Published: October 2020

The nature of scientific research has motived an open‐access model of publication supported by article processing fees. Under this rapidly evolving environment and financial incentives, some dubious venues would publish almost anything—for a fee. Many entities keep track of the standards of these new journals, “blacklisting” those deemed problematic. Anecdotal evidence suggests that blacklisted journals tend to have websites with subpar appearance (e.g., old web technologies, unprofessional design). In this work, we systematically explore whether this anecdotal evidence is true. In particular, we evaluate the websites of journals whitelisted and un‐whitelisted by the Directory of Open Access Journals (DOAJ). We use a convolutional neural network to predict whether a journal is whitelisted based on a screenshot of its website and analyze the factors that predict one output vs. the other. Our results show that appearance is indeed a predictive factor, achieving a medium performance (AUC of 0.736). Further, our interpretation suggests that the network considers whitelisting those websites with a table of content, social media links and packed content. Conversely, our model mistakenly whitelists blacklisted journals hosted by Elsevier and blacklists whitelisted websites with serif fonts and non‐Latin characters.
Social media users' behavior of setting limits in information sharing: A heuristic study based on WeChat moments
Authors: Zheng Guangchun , Zhao Zelong
Published: October 2020

Social media has become an important platform for users to share information in recent years. A large number of active users are sharing their daily lives and social issues in various platforms. At the same time, an interesting phenomenon is that functions like "three days visible" and "selected contacts visible" are also popular among users. In order to explore the information sharing behavior from the perspective of why users set these limits, we made a 15‐day observation on 21 college students' sharing behavior on WeChat Moments and conducted in‐depth interviews with 16 of them. The study summarizes the characteristics of users who set different types of limits from the observation. Sixteen factors influencing the behavior of setting limits were identified and categorized into three dimensions: social, psychological and technical.
Live writing: Modeling a creative activity in a virtual small world
Authors: Kizhakkethil Priya
Published: October 2020

Looking at fan fiction writing as a personally meaningful activity, this paper covers the preliminary stage in developing a model to look at this creative activity based on extant document experience literature and models. Initial data analysis points to the importance of the social context in which the activity takes place, highlighting the role that social ties in the form of fellow readers play in the process. Exploratory in nature and coming as a byproduct of data analysis, it is hoped this will aid conceptual development in information and document experience, while adding to studies that look at personally meaningful information activities.
Healthy diet recommendation via Food‐Nutrition‐Recipe Graph mining
Authors: Li Kequan , Jiang Zhuoren , Wang Haijiao , Liu Xiaozhong
Published: October 2020

Good nutrition and balance dietary pattern play vital roles of leading a healthy lifestyle. Prior studies showed that the healthy diet can successfully reduce the risk of chronic diseases (e.g., type 2 diabetes and cancer) and bring other well‐documented benefits. Existing food recommendation models, however, often solely rely on user's feedback (e.g., click and purchase data), which aims to optimize Click‐Through Rate (CTR) but ignores the importance of health needs of users. Intuitively, a healthy diet recommendation requires a comprehensive consideration of different kinds of information, such as nutrition, ingredients and cooking methods. In this study, by collecting the data from FoodData Central (FDC), recipe websites, and scientific literature, we construct a heterogeneous graph, Food‐Nutrition‐Recipe Graph (FNRG), by integrating information of nutrition, food (ingredients), and recipes. A random walk based graph mining approach is proposed to meet the health needs of users. Experiments results show that the proposed method can successfully address the health information needs for people who suffer from chronic diabetes.
Seasonal characterization of diet discussions on Reddit
Authors: Money Victoria , Karami Amir , Turner‐McGrievy Brie , Kharrazi Hadi
Published: October 2020

To monitor public opinions on diet, large survey data is commonly used though costly and time consuming. Social media has become a mainstream channel of communication and has drastically grown in popularity, connecting users to a ready stream of health information. While the literature has provided valuable information on the use of social media for health, a broader perspective informed by different types of social media platforms would be highly beneficial. Diet has been extensively explored on a few mainstream platforms, further informing public health research. However, diet conversations on Reddit have only been studied within a narrow scope, looking at specific sub‐communities. This study aims to characterize diet‐related posts and their seasonal patterns using a mixed method approach. We collected more than 500,000 posts with subsequent comments from Reddit over the course of a year. Our findings show that Reddit users across all sub‐communities primarily discussed health promotion, fitness plans, a healthy lifestyle, diet and fitness progress, food experiences, weight loss, as well as vegan and vegetarian diets. In addition, seasonal differences based on the weight of most topics, were found to be significant (p < .05).
GotFunding: A grant recommendation system based on scientific articles
Authors: Zeng Tong , Acuna Daniel E.
Published: October 2020

Obtaining funding is an important part of becoming a successful scientist. Junior faculty spend a great deal of time finding the right agencies and programs that best match their research profile. But what are the factors that influence the best publication–grant matching? Some universities might employ pre‐award personnel to understand these factors, but not all institutions can afford to hire them. Historical records of publications funded by grants can help us understand the matching process and also help us develop recommendation systems to automate it. In this work, we present GotFunding (Grant recOmmendaTion based on past FUNDING), a recommendation system trained on National Institutes of Healthʼs (NIH) grant–publication records. Our system achieves a high performance (NDCG@1 = 0.945) by casting the problem as learning to rank. By analyzing the features that make predictions effective, our results show that the ranking considers most important (a) the year difference between publication and grant, (b) the amount of information provided in the publication, and (c) the relevance of the publication to the grant. We further discuss the implications and future improvements to this work.
Data management plan scorecard
Authors: Bishop Bradley Wade , Ungvari Judit , Gunderman Hannah , Moulaison‐Sandy Heather
Published: October 2020

Data and how that data are organized, accessed, and used, remain central to the advancement of science, as evidenced through calls for reproducibility and demands to enable re‐use. Data management plans describe the roles, responsibilities, and activities for managing data during and after research. This paper presents the development of a data management plan scorecard. The assessment of data management plans provides one measure to evaluate how data are planned to be shared and a first step down the road towards shareable data. The scorecard provides a widely‐applicable, scalable, and simple tool to assess completeness and quality of 15 data elements commonly required in all data management plans.
Understanding and fighting disinformation and fake news: Towards an information behavior framework
Authors: Agarwal Naresh Kumar , Alsaeedi Farraj
Published: October 2020

Current efforts to fight misinformation, disinformation, and fake news have been isolated and inadequate. Most models of information behavior deal with information, and not misinformation or disinformation per se. We seek to disambiguate the phenomenon by clarifying terms and highlighting efforts towards fighting fake news. Building upon Karlova and Fisher's, Information Research, 2013, 18, 1–17 model, we propose a new information behavior framework. It should guide practitioners and researchers in library and information science and beyond, and other stakeholders in understanding the phenomenon, and fighting against it.
Teachers' and students' attitudes towards information security: A qualitative study
Authors: Reich Nurit , Aharony Noa , Bouhnik Dan
Published: October 2020

The goal of this research study is to examine teenager's and educational staff's attitudes towards the issue of information security (IS). The study focuses on teenagers and on educational staff from high schools from varied socio‐economic groups. The goal of this study is to eventually instigate a cultural change in the area of IS, therefore, it is important to understand the motivations behind end users' actions. The research findings indicate a clear connection between students' and teachers' evaluation of their information sources and the threat they feel by information risks. This, in turn affects their willingness to apply IS measures. In addition, the necessity of integration of IS into the educational curriculum emerged, as it constitutes an indispensable skill in the 21st century.
Performance evaluation of feature selection methods for aircraft hard landing incident Prediction
Authors: Ding Jingjia , Yuan Xiaoqun , Li Hongxu
Published: October 2020

This poster aims to find out a quick and accurate way for feature selection in hard landing prediction. To make the performance evaluation effective, a general evaluation framework is designed. Then seven classic feature selection methods are carried out by applying four classification algorithms, nine comparison metrics on a real QAR dataset with a total of 3,040 instances. At last, TOPSIS is employed for overall performance evaluation. Results indicate that the data‐driven category is preferable in feature selection of hard landing prediction. Moreover, Gradient Boosting Decision Tree combining with K‐Nearest Neighbor classifier on a balanced training dataset outperforms among 56 possible combination models.
Successful trolling on Reddit: A comparison across subreddits in entertainment, health, politics, and religion
Authors: Fichman Pnina , Sharp Samantha
Published: October 2020

Reddit can be perceived as a heaven for trolls, but how much of the site actually contains trolling? How successful are these troll comments on subreddits, and do the types of subreddits affect the success of comments? Based on an analysis of 16,516 comments from 208 posts from 13 subreddits in four categories (entertainment, health, politics, and religion), we found that trolling comments account for less than 1 % of all comments, and most of these trolling comments were not successful, regardless of category. While one out of five trolling comments were successful, only two out of a thousand comments were successful trolling. We also found that politics subreddits attract more trolling than subreddits in the other categories, and health subreddits are less susceptible to successful trolling than other subreddits.
PreKindergarten and kindergarten virtual school programs under COVID‐19: A two‐case comparative study
Authors: Hu Zhan , Lu Wenqing
Published: October 2020

This case study aims to explore and compare two cases of virtual school programs, one asynchronized and one synchronized, regarding their pedagogical design and operationalization. The authors collected data from observations of learning activities and analyses of teaching materials. A comparison was drawn on the benefits and drawbacks of two teaching modes, and the strategies the instructors use to address the limitations.
Good, bad, and practical: Exploring human memory in everyday information behavior
Authors: Lee Lo , Ocepek Melissa G. , Makri Stephann
Published: October 2020

This study investigates how memory affects everyday information behavior. Previous literature generally examined memory as a broad category, missing to consider how the variance in memory influences information behavior. To bridge this gap, we interviewed and observed 10 arts and crafts hobbyists when they navigated a creative shopping space designed to spark serendipity. Findings demonstrate the distinction between memory, including positive, negative, and practical, along with their potential impacts on everyday information behavior. This work provides a novel analysis of memory, shedding new light on the subtlety of memory in information behavior research.
Libraries and archives of tomorrow: How future information professionals perceive AI
Authors: Li Lan , Fleischmann Kenneth R.
Published: October 2020

How do future librarians and archivists envision AI and its role in libraries/archives? The goal of this paper is to begin to answer this question using exploratory findings from interviews with library and archives students. Recommendations include developing courses that combine technical aspects of how to leverage AI and library/archives content, to help students build libraries and archives of tomorrow.
A theoretical analysis of independent business owners' preferences for informal information sources
Authors: Chan Joel , Brier Jonathan , Farhadi Zahra , Lee Myeong , Janzen Shawn , Chi Wei‐Wei , Fellows Andrew , Winter Susan
Published: October 2020

Independent business owners often prefer informal information sources to formal ones such as library collections. Part of these preferences is rational because contextual and application‐oriented information is usually available from informal sources, which are theoretically the best matches for this kind of information. This suggests that, in addition to outreach strategies, efforts to integrate informal sources of business‐relevant information can improve public libraries' ability to support independent business owners' information needs. Through interviews with business information providers and users, we explore the multi‐dimensional space of information needs in independent businesses.
What are the source selection criteria?: Lessons from mothers' health information‐seeking behavior
Authors: Lee Hanseul S.
Published: October 2020

This research investigated mothers' health information source selection behavior, specifically, what criteria they consider important for their source selection. Online surveys were completed by 851 mothers: 255 U.S.‐born mothers, 296 Korean‐born mothers, and 300 Korean immigrant mothers living in the United States. Results indicated that health information perceived to be “accurate/credible”, “easily accessible”, and “active/updated” tended to be used most often. Moreover, when a series of one‐way analysis of variance (ANOVA) tests was conducted, statistical group differences were identified in 9 out of 10 source characteristics (e.g., “accurate/credible”, “active/updated”, “interactive/able to respond” etc.). Implications for information professionals when providing health information services are also discussed.
Validating an extended typology of web credibility assessment
Authors: Choi Wonchan , Luo Manman , Kim Sang‐Yeon
Published: October 2020

This methodology poster introduces an ongoing study seeking to validate an extended typology of web credibility assessments proposed by Choi and Stvilia (2015) using online surveys. The study focuses on health‐related topics as an important subject domain for web credibility assessments. The poster describes the study's theoretical background and methodology, especially the process of developing and testing the online survey questionnaire, which consists of 89 questions in five sections: internet use and experience, health information seeking, web credibility assessment, outcomes of web credibility assessment, and demographic factors. A pretest of the online survey questionnaire was conducted with eight doctoral students, in which each participant answered the questions and provided feedback on the survey design. Pretest results and future research directions are discussed.
Corralling culture as a concept in LIS research
Authors: Salzano Rachel , Hall Hazel , Webster Gemma
Published: October 2020

Individuals' cultural backgrounds influence their use of societal resources, including libraries. A literature search and review was completed on the treatment of culture in library and information science (LIS) in the body of work on information behaviour and use. While much of the literature reviewed cites culture as an important influence, few researchers define culture as a concept, nor do they explore in detail the factors that it comprises. In this body of work culture is primarily used in two ways: (a) to differentiate groups of library users; and (b) to draw attention to questions of integration.
Impact of cultural and religious literacy: Implications for information literacy
Authors: Khader Malak , Allen Jeff , Njeri Millicent , Zimmerman Tara , Rosellini Amy , Eaves Tresia
Published: October 2020

Today, more than ever, there is an abundance of information and points of access that can complicate the information seeking process, even in religious communities and cultures. People are overwhelmed with information and tend to seek information from those they trust; consequently, individuals are oftentimes blindly trusting these sources. It is important, therefore, to create awareness of misinformation in religious communities/cultures, including ways it can be spread, and the role of critical thinking as a defense against it. This study looks to examine the relation of information literacy within religiously enforced cultures.
One‐approach‐fits‐all? Use and evaluation of social media information for different goals
Authors: Kim Kyung‐Sun , Sin Sei‐Ching Joanna
Published: October 2020

The study investigated whether undergraduate students adopt a “one‐size‐fits‐all” approach when using social media to meet different goals (entertainment, information‐seeking/learning, personal identity, and social interaction/ integration). Findings suggest the selective use of platforms for different goals. The perceived usefulness of elements in evaluating social media information also differed across goals, particularly for entertainment. Multiple regression analyses revealed the familiarity with social media information quality issues, self‐efficacy, and gender significantly associated with respondents' tendency to give dissimilar usefulness ratings across goals.
Identifying factors impacting entity sentiment analysis: A case study of sentiment analysis in the context of news reports
Authors: Luo Manman , Mu Xiangming
Published: October 2020

Entity sentiment analysis aims to analyze sentiment for a specific entity. As entity sentiment analysis requires the understanding of entities and associated entities, this paper presents preliminary findings from an exploratory analysis of factors affecting entity sentiment analysis in the news report context using a data set of 8,754 paragraphs. An entity coding schema was developed based on grounded theory. The coding result shows that 29% of paragraphs express sentiment directly, and 24% express indirectly. Negative biased entities (towards target entity) may significantly affect the accuracy of entity sentiment analysis. The findings may shed light on future exploration in improving the accuracy of entity sentiment analysis.
Description of research data in laboratory notebooks: Challenges and opportunities
Authors: Nishida Emi , Ishita Emi , Watanabe Yukiko , Tomiura Yoichi
Published: October 2020

In scientific research, laboratory (lab) notebooks have traditionally been used to record experiments and their results. Lab notebooks also act as an important record of the generation, processing and analysis of data over the research data lifecycle. As research data becomes increasingly digitized and voluminous, it becomes harder to record and describe research data, especially in paper lab notebooks (PLNs). This paper addresses the challenges of recording contemporary research data in lab notebooks and discusses the requirements in lab notebooks for describing research data. Two basic requirements of lab notebooks are the completeness of the data description and the ability to link the experiment records with their corresponding research datasets. Descriptions of research data should also document the provenance of the research data so that the original data can be retrieved. Guidelines for consistent file naming and systematic directory structures for saved research data can support efficient research data retrieval.
Data integration as the major mode of data reuse
Authors: Sakai Yukiko , Miyata Yosuke , Yokoi Keiko , Wang Yuqing , Kurata Keiko
Published: October 2020

Data sharing has been emphasized in scientific research in the era of open science; however, the concept of data sharing is ambiguous, and the real situation of data sharing is unclear. One reason is that most studies focused on researchers' recognition, motivation, and other contributing factors and did not thoroughly discuss the actual practice of data sharing for preparing research articles. To explicitly understand the current status of data sharing, the authors considered and investigated primary reuse, data integration, and data release distinctively as the actual practices of data sharing. A total of 237 articles published in 2018 and registered in the Web of Science global citation database were manually checked. Unlike the scarcity of data reuse (8.0%) or data release (5.1%), existing data were most frequently reused in the form of data integration (20.7%). The result implies that further studies on detailed data reuse are required to clarify the concept of data sharing.
Utilizing HTML‐analysis and computer vision on a corpus of website screenshots to investigate design developments on the web
Authors: Schmidt Thomas , Mosiienko Anastasiia , Faber Raffaela , Herzog Juliane , Wolff Christian
Published: October 2020

We present preliminary results of a project investigating the design development of popular websites between 1996 and 2020 via HTML analysis and basic computer vision methods. We acquired a corpus of website screenshots of the current top 47 popular websites. We crawled a snapshot of every month of these websites via the wayback machine of the Internet Archive platform since the time snapshots are stored to gather 7,953 screenshots and HTML pages. We report upon quantitative analysis results concerning HTML elements, color distributions and visual complexity throughout the years.