TUESDAY, MARCH 18, 2014
Research Presentation by Jeff Hemsley, candidate for LIS Assistant Professor
When: Tuesday, March 18, 2014 11:00 AM – 12:00 PM
Where: Lillooet Room # 301, Irving K. Barber Learning Centre
Description: Title: Interaction of information flows with dynamic networks
Abstract
The diffusion of information can have both positive and negative impacts on commerce, force public officials out of office, and connect people with shared interests. The distributed nature of our digital social networks means that mainstream media and governments have less control over the flow of information and that networks of like-minded individuals can quickly coalesce around issues and grievances to engage in collective action. Current studies have not offered a method for analyzing information flows that can identify those specific flows that are likely to alter network structures.
This dissertation seeks to address these gaps. It proposes a novel approach to measuring changes in network structures and to identifying information flows associated with these changes. This approach is demonstrated using Twitter data drawn from the Occupy Wall Street Movement. The findings from this work will provide network scholars with insight into how information flows are shaped by, and in turn shape, the social networks that connect humans, organizations and institutions. Additionally, methods developed in this research can inform future studies by providing an empirical basis for distinguishing between network-altering flows and non-altering flows.
Bio
Jeff Hemsley is a PhD candidate in the Information School (iSchool) at the University of Washington. His current research looks at information flows in social media networks, with an emphasis on social movements and political events. He builds tools that collect, curate, visualize and analyze big data sets. He combines social network analysis, econometrics techniques, and computational simulation methods in addressing research questions.
Recent research includes the examination of Twitter users’ relationship to place as a factor in the formation of contentious political networks (Hemsley & Eckert, 2014) and the linking behavior of influential political blogs when linking to viral political videos (Nahon & Hemsley, 2013). He is a founding member of the Social Media Lab @ UW, which has received RAPID and INSPIRE awards from NSF, an Amazon Web Services in Education research grant award, and a gift from Microsoft Research to support this research.
Students Meet the Candidates
When: Tuesday, March 18, 2014 5:00 PM – 6:00 PM
Where: Trail Room # 491, Irving K. Barber Learning Centre
Description: Jeff Hemsley is a PhD candidate in the Information School (iSchool) at the University of Washington. His current research looks at information flows in social media networks, with an emphasis on social movements and political events. He builds tools that collect, curate, visualize and analyze big data sets. He combines social network analysis, econometrics techniques, and computational simulation methods in addressing research questions.
THURSDAY, MARCH 20, 2014
Students Meet the Candidates
When: Thursday, March 20, 2014 5:00 PM – 6:00 PM
Where: Room # 155, Irving K. Barber Learning Centre
Description: Jacek Gwizdka, PhD from Toronto in Mechanical and Electrical Engineering. He is currently teaching at the School of Information, University of Texas at Austin, and formerly at Rutgers in their LIS program.
FRIDAY, MARCH 21, 2014
Research Presentation by Dr. Jacek Gwizdka, candidate for LIS Assistant Professor.
When: Friday, March 21, 2014 11:00 AM – 12:00 PM
Where: Dodson Room # 302, Irving K. Barber Learning Centre
Description: Title: Understanding Information Searchers Without Asking Them
Abstract:
Information seeking engages cognitive processes at many levels. Knowing these processes is likely to contribute at a theoretical level to better models of information seeking and at an applied level to improved information retrieval systems. In this talk I will focus on research projects that tackle two questions: What makes information search cognitively difficult? What cognitive processes are involved in relevance judgments? I will describe an eye-tracking-based implicit data collection method that uses eye-movement patterns to model reading and assess a searcher’s cognitive effort. I will present a web search study in which this method was validated and describe its application to implicit assessment of a searcher’s domain knowledge. I will then turn to discussing inferring relevance from eye-movement data. I will present a study that demonstrated differences in reading patterns and in cognitive effort involved in processing documents of varied degrees of relevance. I will conclude by outlining future research plans.
Bio:
Dr. Jacek Gwizdka studies cognitive aspects of human-information interaction. His research is situated at the intersection of interactive-information retrieval (IIR) and human-computer interaction (HCI). Dr. Gwizdka has background in cognitive psychology, human factors engineering, and information systems. His current projects include application of cognitive neuroscience methods to the study of cognitive function engaged in human-information interaction and to implicit assessment of cognitive load. His past research includes pen-based interfaces for information capture, email interfaces for task awareness and examination of effects of search interface and cognitive ability on information finding. Dr. Gwizdka has been affiliated with University of Toronto, Rutgers University and University of Texas at Austin. He conducted research at industrial labs (Xerox PARC, FXPAL, HP Labs). He has served on international conference and workshop committees (e.g., IIiX, ASIST, ACM SIGCHI & SIGIR). He is as an Associate Editor of Interacting with Computers and serves on editorial board of Information Processing & Management. When not busy with teaching or research, he enjoys photography, jazz and skiing.
