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Featured researches published by Seungwon Yang.


Government Information Quarterly | 2012

Social media use by government: From the routine to the critical

Andrea L. Kavanaugh; Edward A. Fox; Steven D. Sheetz; Seungwon Yang; Lin Tzy Li; Donald J. Shoemaker; Apostol Natsev; Lexing Xie

Abstract Social media and online services with user-generated content (e.g., Twitter, Facebook, Flickr, YouTube) have made a staggering amount of information (and misinformation) available. Government officials seek to leverage these resources to improve services and communication with citizens. Significant potential exists to identify issues in real time, so emergency managers can monitor and respond to issues concerning public safety. Yet, the sheer volume of social data streams generates substantial noise that must be filtered in order to detect meaningful patterns and trends. Important events can then be identified as spikes in activity, while event meaning and consequences can be deciphered by tracking changes in content and public sentiment. This paper presents findings from a exploratory study we conducted between June and December 2010 with government officials in Arlington, VA (and the greater National Capitol Region around Washington, D.C.), with the broad goal of understanding social media use by government officials as well as community organizations, businesses, and the public at large. A key objective was also to understand social media use specifically for managing crisis situations from the routine (e.g., traffic, weather crises) to the critical (e.g., earthquakes, floods).


international conference on digital government research | 2011

Social media use by government: from the routine to the critical

Andrea L. Kavanaugh; Edward A. Fox; Steven D. Sheetz; Seungwon Yang; Lin Tzy Li; Travis Whalen; Donald J. Shoemaker; Paul Natsev; Lexing Xie

Social media (i.e., Twitter, Facebook, Flickr, YouTube) and other services with user-generated content have made a staggering amount of information (and misinformation) available. Government officials seek to leverage these resources to improve services and communication with citizens. Yet, the sheer volume of social data streams generates substantial noise that must be filtered. Nonetheless, potential exists to identify issues in real time, such that emergency management can monitor and respond to issues concerning public safety. By detecting meaningful patterns and trends in the stream of messages and information flow, events can be identified as spikes in activity, while meaning can be deciphered through changes in content. This paper presents findings from a pilot study we conducted between June and December 2010 with government officials in Arlington, Virginia (and the greater National Capitol Region around Washington, DC) with a view to understanding the use of social media by government officials as well as community organizations, businesses and the public. We are especially interested in understanding social media use in crisis situations (whether severe or fairly common, such as traffic or weather crises).


acm/ieee joint conference on digital libraries | 2006

Curriculum development for digital libraries

Jeffrey Pomerantz; Barbara M. Wildemuth; Seungwon Yang; Edward A. Fox

The Virginia Tech Department of Computer Science (VT CS) and the University of North Carolina at Chapel Hill School of Information and Library Science (UNC SILS) have launched a curriculum development project in the area of digital libraries. Educational resources would be developed based on the ACM/IEEE-CS computing curriculum 2001. Lesson plans and modules would be developed in a variety of areas (that cover the topics of papers and conference sessions in the field), evaluated by experts in those areas, and then pilot tested in CS and LIS courses. An analysis of papers on digital library-related topics from several corpora was performed, to identify the areas in which more and less work has already been performed on these topics; this analysis would guide the initial stages of this curriculum development


visual analytics science and technology | 2010

VizCept: Supporting synchronous collaboration for constructing visualizations in intelligence analysis

Haeyong Chung; Seungwon Yang; Naveed Massjouni; Christopher Andrews; Rahul Kanna; Chris North

In this paper, we present a new web-based visual analytics system, VizCept, which is designed to support fluid, collaborative analysis of large textual intelligence datasets. The main approach of the design is to combine individual workspace and shared visualization in an integrated environment. Collaborating analysts will be able to identify concepts and relationships from the dataset based on keyword searches in their own workspace and collaborate visually with other analysts using visualization tools such as a concept map view and a timeline view. The system allows analysts to parallelize the work by dividing initial sets of concepts, investigating them on their own workspace, and then integrating individual findings automatically on shared visualizations with support for interaction and personal graph layout in real time, in order to develop a unified plot. We highlight several design considerations that promote communication and analytic performance in small team synchronous collaboration. We report the result of a pair of case study applications including collaboration and communication methods, analysis strategies, and user behaviors under a competition setting in the same location at the same time. The results of these demonstrate the tools effectiveness for synchronous collaborative construction and use of visualizations in intelligence data analysis.


learning at scale | 2015

Uncovering Trajectories of Informal Learning in Large Online Communities of Creators

Seungwon Yang; Carlotta Domeniconi; Matt Revelle; Mack Sweeney; Ben U. Gelman; Chris Beckley; Aditya Johri

We analyzed informal learning in Scratch Online -- an online community with over 4.3 million users and 6.7 million user-generated content. Users develop projects, which are graphical interfaces involving manipulation of programming blocks. We investigated two fundamental questions: how can we model informal learning, and what patterns of informal learning emerge. We proceeded in two phases. First, we modeled learning as a trajectory of cumulative programming block usage by long-term users who created at least 50 projects. Second, we applied K-means++ clustering to uncover patterns of learning and corresponding subpopulations. We found four groups of users manifesting four different patterns of learning, ranging from the smallest to the largest improvement. At one end of the spectrum, users learned more and in a faster manner. At the opposite end, users did not show much learning, even after creating dozens of projects. The modeling and clustering of trajectory patterns that enabled us to quantitatively analyze informal learning may be applicable to other similar communities. The results can also support administrators of online communities in implementing customized interventions for specific subpopulations.


international conference on digital government research | 2011

Twitter use during an emergency event: the case of the UT Austin shooting

Lin Tzy Li; Seungwon Yang; Andrea L. Kavanaugh; Edward A. Fox; Steven D. Sheetz; Donald J. Shoemaker; Travis Whalen; Venkat Srinivasan

This poster presents one of our efforts in the context of the Crisis, Tragedy, and Recovery Network (CTRnet) project. One topic studied in this project is the use of social media by government to respond to emergency events in towns and counties. Monitoring social media information for unusual behavior can help identify these events once we can characterize their patterns. As an example, we analyzed the campus shooting in the University of Texas, Austin, on September 28, 2010. In order to study the pattern of communication and the information communicated using social media on that day, we collected publicly available data from Twitter. Collected tweets were analyzed and visualized using the Natural Language Toolkit, word clouds, and graphs. They showed how news and posts related to this event swamped the discussions of other issues.


international conference on asian digital libraries | 2006

Interdisciplinary curriculum development for digital library education

Seungwon Yang; Edward A. Fox; Barbara M. Wildemuth; Jeffrey Pomerantz; Sanghee Oh

The Virginia Tech (VT) Department of Computer Science (CS) and the University of North Carolina at Chapel Hill (UNC-CH) School of Information and Library Science (LIS) are developing curricular materials for digital library (DL) education, appropriate for the CS and LIS communities. Educational modules will be designed, based on input from the project advisory board, Computing Curriculum 2001, the 5S framework, and workshop discussions. These modules will be evaluated, first through expert inspection and, second, through field testing. We are identifying and refining module definitions and scopes, collecting related resources, developing a module template, and creating example modules. These will be presented at the conference. The developed curriculum should contribute to producing well-balanced digital librarians who will graduate from CS or LIS programs.


international conference on asian digital libraries | 2007

Further development of a digital library curriculum: evaluation approaches and new tools

Seungwon Yang; Barbara M. Wildemuth; Seonho Kim; Uma Murthy; Jeffrey Pomerantz; Sanghee Oh; Edward A. Fox

This paper is a follow-up to our ICADL 2006 paper, reporting on our progress over the past year in developing a digital library curriculum. It presents and describes the current curriculum framework, which now includes ten modules and 41 sub-modules. It provides an overview of the curriculum development lifecycle, and our progress through that lifecycle. In particular, it reports on our evaluation of the modules that have been drafted. It concludes with a description of two new technologies - Superimposed Information (SI) to help resource presentation in a module and Visual User model Data Mining (VUDM) to help long-term module upgrade by visualizing the user community and its trends.


acm ieee joint conference on digital libraries | 2011

CTRnet DL for disaster information services

Seungwon Yang; Andrea L. Kavanaugh; Nádia P. Kozievitch; Lin Tzy Li; Venkat Srinivasan; Steven D. Sheetz; Travis Whalen; Donald J. Shoemaker; Ricardo da Silva Torres; Edward A. Fox

We describe our work in collecting, analyzing and visualizing online information (e.g., Web documents, images, tweets), which are to be maintained by the Crisis, Tragedy and Recovery Network (CTRnet) digital library. We have been collecting resources about disaster events, as well as campus and other major shooting events, in collaboration with the Internet Archive (IA). Social media data (e.g., tweets, Facebook data) also have been collected and analyzed. Analyzed results are visualized using graphs and tag clouds. Exploratory content-based image retrieval has been applied in one of our image collections. We explain our CTR ontology development methodology and collaboration with Arlington County, VA and IBM, in a Center for Community Security and Resilience funded project.


acm/ieee joint conference on digital libraries | 2006

Demonstrating the use of a SenseCam in two domains

Seungwon Yang; Ben Congleton; George Luc; Manuel A. Pérez-Quiñones; Edward A. Fox

MyLifeBits is both an application and a framework to manage a personal lifetime of memories. We would demonstrate the use of a small digital library that manages data from two Microsoft SenseCams, used by: 1) students in the Virginia-Maryland Regional College of Veterinary Medicine, and 2) students supported by our assistive technologies office

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Barbara M. Wildemuth

University of North Carolina at Chapel Hill

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Jeffrey Pomerantz

University of North Carolina at Chapel Hill

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Sanghee Oh

Florida State University

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Aditya Johri

George Mason University

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Lin Tzy Li

State University of Campinas

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