Preliminary Conference Agenda

Overview and details of the sessions of this conference. Please select a date or room to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

This agenda is preliminary and subject to change.

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Session Overview
Location: 2110/2111/2112
Date: Monday, 01/Apr/2019
10:30am - 12:00pmPapers 1: Scientific Work and Data Practices
Session Chair: Michael Lesk, Rutgers University

Surfacing Data Change in Scientific Work

D. Paine, L. Ramakrishnan

Lawrence Berkeley National Laboratory, United States of America

Data are essential products of scientific work that move among and through research infrastructures over time. Data constantly changes due to evolving practices and knowledge, requiring improvisational work by scientists to determine the effects on analyses. Today for end users of datasets much of the information about changes, and the processes leading to them, is invisible — embedded elsewhere in the work of a collaboration. Simultaneously scientists use increasing quantities of data, making ad hoc approaches to identifying change difficult to scale effectively. Our research investigates data change by examining how scientists make sense of change in datasets being created and sustained by the collaborative infrastructures they engage with. We examine two forms of change, before examining how trust and project rhythms influence a scientist's notion that the newest available data are the best. We explore the opportunity to design tools and practices to support user examinations of data change and surface key provenance information embedded in research infrastructures.

Understanding Hackathons for Science: Collaboration, Affordances, and Outcomes

E. P. P. Pe-Than, J. D. Herbsleb

Carnegie Mellon University, United States of America

Nowadays, hackathons have become a popular way of bringing people together to engage in brief, intensive collaborative work. Despite being a brief activity, being collocated with team members and focused on a task—radical collocation—could improve collaboration of scientific software teams. Using a mixed-methods study of participants who attended two hackathons at Space Telescope Science Institute, we examined how hackathons can facilitate collaboration in scientific software teams which typically involve members from two different disciplines: science and software engineering. We found that hackathons created a focused interruption-free working environment in which team members were able to assess each other’s skills, focus together on a single project and leverage opportunities to exchange knowledge with other collocated participants, thereby allowing technical work to advance more efficiently. This study suggests “hacking” as a new and productive form of collaborative work in scientific software production.

A comparative study of biological scientists’ data sharing between genome sequence data and lab experiment data

Y. Kim

University of Kentucky, United States of America

This research aims to explore how the institutional pressure, resource, and individual motivation factors all affect biological scientists’ data sharing behaviors in different data types. This research utilized a combined theoretical framework including institutional theory and theory of planned behavior to examine institutional pressure, resource, and individual motivation factors influencing biological scientists’ data sharing intentions between different data types including genome sequence data and lab experiment data. A total of 342 survey responses from biological sciences were employed for a series of statistical analyses including Cronbach’s alpha, factor analysis, hierarchical regression, and t-test. This research shows that biological scientists’ data sharing intentions are led by institutional pressure, resource, and individual motivation factors, and the levels of those factors are significantly different between genome sequence data and lab experiment data. This research shows that biological scientists’ data sharing differs depending on the data they share, and different policies and support needs to be applied to encourage biological scientists’ data sharing of different data types.

1:30pm - 3:00pmPapers 5: Measuring and Tracking Scientific Literature
Session Chair: Peter Darch, University of Illinois at Urbana-Champaign

Dead science: most resources linked in biomedical articles disappear in eight years

T. Zeng1,2, A. Shema1, D. Acuna1

1School of Information Studies, Syracuse University, United States of America; 2School of Information Management, Nanjing University, China

Scientific progress critically depends on disseminating analytic pipelines and datasets that make results reproducible and replicable. Increasingly, researchers make resources available for wider reuse and embed links to them in their published manuscripts. Previous research has shown that these resources become unavailable over time but the extent and causes of this problem in open access publications has not been explored well. By using 1.9 million articles from PubMed Open Access, we estimate that half of all resources become unavailable after 8 years. We find that the number of times a resource has been used, the international (int) and organization (org) domain suffixes, and the number of affiliations are positively related to resources being available. In contrast, we found that the length of the URL, Indian (in), European Union (eu), and Chinese (cn) domain suffixes, and abstract length are negatively related to the decay of a resource. Our results contribute to our understanding of resource sharing in science and provide some guidance to solve resource decay.

Are papers with open data more credible? An analysis of open data availability in retracted PLoS articles

M. Lesk1, J. Bially Mattern2, H. Moulaison Sandy3

1Rutgers, United States of America; 2Villanova, United States of America; 3University of Missouri, United States of America

Open data has been hailed as an important corrective for the credibility crisis in science. This paper makes an initial attempt to measure the relationship between open data and credible research by analyzing the number of retracted articles with attached or open data in an open access science journal. Using Retraction Watch, retracted papers published in PLoS between 2014 and 2018 are identified. Of the 152 total retracted papers, fewer than 15% attached their data. Since about half of the published articles have open data, and so few of the retracted ones do, we put forth the preliminary notion that open data, especially high quality and well-curated data, might imply scientific credibility.

The Spread and Mutation of Science Misinformation

A. Korsunska

Temple University, Philadelphia, PA, USA

As the media environment has shifted towards digitization, we have seen the roles of creating, curating and correcting information shift from professional “gatekeeper” journalists to a broader media industry and the general public. This shift has led to the spread of misinformation. Though political “fake news” is currently a popular area of study, this study investigates an-other related phenomenon: science misinformation. Consistent exposure to science misinformation has been shown to cultivate false beliefs about risks, causes and prevalence of illnesses and disincentivize the public from implementing healthy lifestyle changes. Despite the need for more research, science misinformation dissemination studies are scarce. Through a case study that traces the spread of information about one specific article through hyperlink citations, this study adds valuable insights into the inner workings of media networks, conceptualizations of misinformation spread and methodological approaches to multi-platform misinformation tracing. The case study illustrates the over-reliance of media sources on secondary information and the novel phenomenon of constantly mutating online content. The original misinformant is able to remove misleading in-formation, and as a result, all of the subsequent articles end up referencing misinformation to a source that no longer exists. This ability to update con-tent online breaks the information flow process: news stories no longer rep-resent a snapshot in time but instead living, mutating organisms, making any study of media networks increasingly complex.

Exploring Scholarly Impact Metrics in Receipt of Highly Prestigious Awards

D. J. Lee1, K. Mutya2, B. E. Herbert1, E. V. Mejia1

1University Libraries, Texas A&M University, United States of America; 2Industrial and Systems Engineering Department, Texas A&M University, United States of America

The authoritative data that underlies research information management (RIM) systems supports fine-grained analyses of faculty members’ research practices and output, data-driven decision making, and organizational research management. Administrators at Texas A&M University (TAMU) asked the University Libraries to develop institutional reports that describe faculty research practices and identify their research strengths. The library runs Scholars@TAMU ( based on VIVO, a member-supported, open source, semantic-web software program, as the university’s RIM system. This paper explores the scholarly impact and collaboration practices of senior faculty members in the College of Engineering at TAMU and identifies relationships between their impact metrics and collaboration practices. Full professors were divided into three groups: (1) those who received highly prestigious (HP) awards, (2) those who received prestigious (P) awards, and (3) those who did not receive any awards categorized as either HP or P by the National Research Council. The study’s results showed that the faculty members with HP awards had significantly higher mean ranks for their total citation count, the citation count of their top cited article, their h-index, and their total number of publications than did the faculty members without any HP or P awards. The findings from this study can inform researchers, university administrators, and bibliometric communities about the use of awards as an indicator that corresponds to other research performance indicators. Furthermore, researchers could also use the study’s results to develop a machine-learning model that could identify those faculty who are on track to win HP awards in the future.

3:30pm - 5:00pmPapers 9: Information Behaviors in Academic Environments
Session Chair: Wu Dan, Wuhan University

From Gridiron Gang to Game Plan: Impact of ICTs on Student Athlete Information Seeking Practices, Routines, and Long-Term Goals

V. Grimaldi1, J. Figueroa2, J. Sullivan3, B. Dosono4

1Suffolk University, United States of America; 2Clemson University, United States of America; 3University of Maryland, College Park; 4Syracuse University, United States of America

Our qualitative study explores the lives of college student athletes and their use of information and communication technologies (ICTs) as they plan their transition from student life to life after graduation. While ICTs such as social media, smartphones, and the internet are becoming more ubiquitous on college campuses and embedded within daily routines, student athletes contend with finding the appropriate information at the right time to navigate through critical life choices. In a thematic analysis of 15 interviews with U.S. student athletes, we uncover factors that affect ICT use in both their athletic and academic environments. We discuss ICTs as transition mediaries and present implications for college athletics programs to improve the holistic student athlete experience and the transition beyond college.

Mobile News Processing: University Students’ Reactions to Inclusion/Exclusion-Related News

K. E. Oh, R. Tang

Simmons University, United States of America

This paper presents the results of a diary study involving 49 university students reporting how they consume and react to news via their mobile phones. In their diary entries, participants used 23 pairs of semantic differential scales to express their reactions. Out of 265 political and society news items submitted, 68 were inclusion/exclusion-related news. The most frequent categories of inclusion/exclusion news were related to “ethnicity/race,” “gender/sexual orientation,” and “religion,” and these three groups of news items counted for over 85% of all inclusion/exclusion related news that were submitted. Significant differences were found in participants’ choices of semantic adjectives between inclusion news and exclusion news, as well as between inclusion/exclusion news and general news. Findings provide an insightful understanding of the interests, value judgment, and emotional attachments of university students in the US to inclusion/exclusion and to general news.

Sexual Information Behavior of Filipino University Students

D. A. D. Dorado1, K. L. B. Obille1, R. P. P. Garcia1, B. S. Olgado1,2

1University of the Philippines, Philippines; 2University of California, Irvine

Having a better knowledge of sexual health could lead to having improved programs and projects in educating people who are sexually active, those who are curious about their sexuality, and those who are planning to engage in the sexual experience. Additionally, by learning more about sexual health and having an idea on what it is, it would help in letting people understand the concepts of sexuality, sexual relationships, and its role in creating better and efficient prevention pro-grams for sexually transmitted infections (STIs) or sexually transmitted diseases (STDs), teen pregnancy issues, and other concerns regarding sexual health.

This study aimed to find out the following: the sexual health information needs and seeking behavior of undergraduate students; as well as if user context played a vital role in affecting their sexual health information needs and/or seeking behavior. Through the use of an online survey among undergraduate students of the University of the Philippines Diliman, the study was able to present the sexual health information needs and sexual health information seeking behavior of the undergraduate students. It has also determined that various characteristics of undergraduate students have an association on whether they would seek sexual health information or not.

Date: Tuesday, 02/Apr/2019
10:30am - 12:00pmPapers 13: Social-Media Text Mining and Sentiment Analysis
Session Chair: Peter Organisciak, University of Denver

Impact of Reddit Discussions on Use or Abandonment of Wearables

R. Garg, J. Kim

Syracuse University, United States of America

Discussion platform, Reddit, is the third most visited website in the US. People can post their questions on this platform to get varying opinions from fellow users, which in turn might also influence their behavior and choices. Wearables are becoming widely adopted, yet challenges persist in their effective long term use because of technical and device related, or personal issues. Therefore, by employing sentiment analysis, this paper aims to analyze how decisions of use or abandonment of wearables are influenced by discussions on Reddit. The results are based on the analysis of 6680 posts and their associated 50,867 comments posted between December 2015 - December 2017 on the subreddit (user created groups) on android wear. Our results show that sentiment of the discussion is majorly dictated by the sentiment of the post itself, and people decide to continue using their devices when fellow Redditors offer them workarounds, or the discussion receives majority of positive or fact-driven neutral comments.

Spatiotemporal Analysis on Sentiments and Retweet Patterns of Tweets for Disasters

S. Chen, J. Mao, G. Li

Wuhan University, China, People's Republic of

Twitter provides an important channel for public to share feelings, attitudes and concerns about disasters. In this study, we aim to explore how spatiotemporal factors affect people's sentiment in disaster situations and how the area type, time stage and sentiment of the tweets affect the extent and speed of tweets' diffusion. After analyzing 531,912 geo-tagged tweets about Hurricane Harvey, we found that on-site tweets are more positive than off-site tweets across the time; neutral tweets spread broader and faster than tweets with sentiment propensity; on-site tweets and tweets posted at early stages tend to be more popular. These findings could enable authorities and response organizations to better comprehend people's feelings and behaviors in social media and their changes over time and space. In future, we will analyze the influence of the interactions among sentiment, location and time to retweet behaviors.

Analyzing sentiment and themes in fitness influencers’ Twitter dialogue

B. E. Auxier, C. Buntain, J. Golbeck

University of Maryland College Park, United States of America

Social media allows anyone to distribute content and build an audience. Natural language processing, sentiment analysis, and psycholinguistic text analysis have proven to be powerful tools for characterizing and classifying social media text. Furthermore, the combination text and sentiment analysis have allowed researchers to identify influencers both by their structural roles and the content they produce. In this paper, we investigate fitness-oriented social media influencers. This research set out to understand how fitness influencers (N=92) on Twitter speak to their audiences through the-matic and sentiment analysis of their tweets (N=273,868). Findings suggest sentiment and topics discussed vary between male and female health and fitness influencers on the platform. The analysis also determined no senti-ment differences between self-identified fitness trainers/coaches and influ-encers who do not identify as such. The results have implications for per-sonalization and recommendation algorithms that operate in this space.

Political Popularity Analysis in Social Media

A. Karami, A. Elkouri

University of South Carolina, United States of America

Popularity is a critical success factor for a politician and her/his party to win in elections and implement their plans. Finding the reasons behind the popularity can provide a stable political movement. This research attempts to measure popularity in Twitter using a mixed method. In recent years, Twitter data has provided an excellent opportunity for exploring public opinions by analyzing a large number of tweets. This study has collected and examined 4.5 million tweets related to a US politician, Senator Bernie Sanders. This study investigated eight economic reasons behind the senator's popularity in Twitter. This research has benefits for politicians, informatics experts, and policymakers to explore public opinion. The collected data will also be available for further investigation.

1:30pm - 3:00pmPapers 16: Understanding Online Behaviors and Experiences
Session Chair: Isa Jahnke, University of Missouri

What prompts users to click on news headlines? A clickstream data analysis of the effects of news recency and popularity

T. Jiang1,2, Q. Guo1, Y. Xu1, Y. Zhao1, S. Fu1

1School of Information Management, Wuhan University, China; 2Center for Studies of Information Resources, Wuhan University, China

A new headline nowadays has to compete for readers’ attention and some-times it needs to entice readers to click and read the news article. The peripheral indicators of news headlines would provide visual suggestions for user to decide on which news to read and which to ignore. This study focused on the recency and popularity indicators of online news. For the purpose of revealing the relationships between news recency/popularity and users’ clicking behavior, a 2-month server log file containing 39,990,200 click-stream records from an institutional news site was analyzed in combination with the news recency and popularity information crawled from its homepage. It was found that more recent or more popular news headlines received more clicks. The results have important implications for news providers in creating effective news headlines and in publishing and disseminating news more responsibly. The introduction of unobtrusive clickstream data to user behavior analysis is a major methodological contribution.

Effects of the User-Need State for Online Shopping: Analyzing Search Patterns

H.-K. Yu, I.-C. Wu

National Taiwan Normal University, Taiwan

With the fast growth of e-commerce and the emerging trend of “New Re-tail”—that is, online and offline integration—the important research issues are how to know the best ways to collect and analyze users’ search behaviors online for a streamlined shopping process, and how to set marketing strategies. Accordingly, we proposed a search pattern analytical method to analyze users’ search behavior in the entire shopping process on the target website from the perspective of the users’ need states. We have focused on the recommendation functions (RFs) and the search functions on to evaluate the effectiveness of each RF to support the online shopping process in different user-need states, namely in a goal-oriented or an exploratory-based approach to online shopping. We first adopted zero-order state transition matrices and then used lag sequential analysis (LSA) to derive the significant repeating search patterns. The results show that the goal-oriented shoppers tend to search directly, whereas exploratory shoppers tend to explore the categories of products as their initial RFs. In addition, goal-oriented users have much more simple search paths compared to the exploratory-based users when engaged in online shopping. Furthermore, based on the results of the LSA, there are two typical search patterns for goal-oriented users and one search pattern for the exploratory ones. Interestingly, the results reveal that exploratory-based users are easily stimulated by context even if they have moved to specific stores. The aim of this research is to summarize users’ search paths and patterns with different need states on the website.

How Users Gaze and Experience on Digital Humanities Platform?: A Model of Usability Evaluation

D. Wu, S. Xu

Wuhan University, China, People's Republic of

Digital humanities platform has been developing rapidly. Using eye-tracking in usability evaluation can make a difference in user experience. In this pa-per we propose a gaze-experience model for usability evaluation on digital humanities platform, and select the “Digital Dunhuang” platform as the case study. A user experiment was carried out to verify the application value of the model through a large amount of eye-tracking and user experience data collection and analysis. We found that the features of eye-tracking (such as fixation and saccade) and those of user experience (such as satisfaction, effi-ciency and effectiveness) had correlations. Implications were also put for-ward to improve the usability of digital humanities platform and can be ex-tended to similar platforms.

3:30pm - 5:00pmPapers 19: Information Behaviors on Twitter
Session Chair: Michael Zimmer, UW-Milwaukee School of Information Studies

Understanding Online Trust and Information Behavior Using Demographics and Human Values

N. Verma, K. R. Fleischmann, K. S. Koltai

University of Texas at Austin, United States of America

In the aftermath of the 2016 U.S. Presidential Election, the role of social media in influencing the dissemination of information is a timely and criti-cal issue. To understand how social media-based information, misinfor-mation, and disinformation work in practice, it is critical to identify factors that can predict social media users’ online information behavior. To this end, we designed an experiment to study the influence of the independent variables, demographics, and human values, on the dependent variables, so-cial media users’ observed trust behavior, self-reported trust behavior, and information behavior. We report the statistically significant results of these comparisons; for example, we found that liberals were more likely to trust mainstream media (p < 0.05) and scientific journals (p < 0.05) and to state that the content of the linked pages influenced their trust (p < 0.01) than moderates; for values, we found that participants who more highly valued security were more likely to trust mainstream media articles (p < 0.05), to notice the presence or absence of hyperlinks, and to click on fake news arti-cles (p < 0.05). Ultimately, both demographics and values can be used to predict online trust and information behavior; while demographics are commonly captured or predicted in online marketing, values represent a much less tapped opportunity to predict social media users’ online trust and information behavior.

Categorization and Comparison of Influential Twitter Users and Sources Referenced in Tweets for Two Health-Related Topics

A. Addawood1,2, P. Balakumar1, J. Diesner1

1University of Illinois Urbana-Champaign, United States of America; 2Al Imam Mohammad Ibn Saud Islamic University, Riyadh, Saudi Arabia

The internet’s evolution has had a profound influence on how people ac-quire medical information. The innovation of web 2.0 has been regarded as the primary motivating factor for people who want to access health-related education. In this work, we identify the URL categories that Twitter users incorporate into their messages when engaging in two selected health-related topics (MMR vaccines and healthy diets). Moreover, we identify the categories of influential message authors who engage in these two topics. Finally, we explore the relationship between different user categories and their patterns of URL sharing. Our results show that when it comes to in-fluential users sharing fake news, users discussing vaccine-related topics were more than twice as likely to share a fake news URLs than those dis-cussing healthy diets.

Twitter Activity at Recent LIS Academic Conferences

D. Albertson

University at Buffalo, The State University of New York, United States of America

The present paper reports on different Twitter activities throughout several library and information science (LIS) focused research conferences which took place over the summer of 2018. Current findings show levels of activity and engagement, both overall and at different time-points throughout the conferences. The study provides descriptive findings about Twitter use and ways in which researchers can analyze social media activities as measures of scholarly communication at academic conferences. Opportunities remain for future in-depth studies of social media and its broader implications for scholarly communications from academic conferences.

Date: Wednesday, 03/Apr/2019
10:30am - 12:00pmPapers 22: Digital Tools for Health Management
Session Chair: Zhan Zhang, Pace University

It Only Tells Me How I Slept, Not How to Fix It'': Exploring Sleep Behaviors and Opportunities for Sleep Technology

S. Zhang1, F. Schaub2, Y. Feng1, N. Sadeh1

1Carnegie Mellon University, USA; 2University of Michigan, USA

We present an online survey study examining people's sleep behaviors as well as their strategies and tools to improve sleep health. Findings show that certain demographic features and sleep behaviors may impact sleep quality, and that current sleep technology is not as effective in promoting sleep health as expected. We discuss the importance of understanding sleep behaviors, design insights for future sleep technology, and the value of a holistic approach to sleep technology design.

Do Recovery Apps Even Exist?: Why College Women with Eating Disorders Use (But Not Recommend) Diet and Fitness Apps over Recovery Apps

E. V. Eikey, Y. Chen, K. Zheng

University of California, Irvine, United States of America

Getting individuals to adopt condition-specific apps over general health apps remains an issue. Using eating disorders (EDs) as an example, we explored 1) if users recommend the general diet and fitness apps they repurpose for ED recovery and 2) if they use condition-specific apps intended for recovery. We used semi-structured interviews and four questionnaires to investigate use and perceptions of diet and fitness apps and recovery apps with 24 college women with self-identified and clinically-diagnosed EDs. Using inductive coding, we generated themes to address their lack of use of recovery apps. We found the majority (n=13) would not recommend using general diet and fitness apps for recovery (compared to only 3 who would), yet most participants did not seek out a condition-specific app even when their objective was recovery. Four themes emerged around the non-use of recovery apps: lack of awareness, unpopularity or unfamiliarity, unwillingness, and lack of features or poor usability. In order to improve awareness as well as perceived popularity and familiarity of condition-specific apps, we suggest researchers and clinicians develop approved app lists, primary care clinicians become expert recommenders for evidence-based apps, and clinicians and educators leverage social media and college settings to reach these “hard to reach” populations.

Turning Points: Motivating Intergenerational Families to Engage on Sustainable Health Information Sharing

J. Sandbulte1, J. Beck1, E. K. Choe2, J. M. Carroll1

1The Pennsylvania State University, United States of America; 2University of Maryland, United States of America

Family relationships present a space for provision of support in which the members reciprocate and help one another at times of necessity. Yet, family members face obstacles in providing support to one another because they are unaware that it is needed. In this study, we investigated different motivating factors that influence family member's decision to share (or not share) health information. We conducted focus group discussions with independent living elderly parents (n = 16) and adult children (n = 21). We learned that the change of family member's sharing behaviors was often due to a disruptive moment which we refer to here as ``turning point.'' Based on the concept of ``turning points'', we discuss how those moments could promote sustainable health information sharing within families and are useful tools for designing technology to support family collaboration on health.


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