{"207801":{"#nid":"207801","#data":{"type":"event","title":"CSE Seminar: Tina Eliassi-Rad","body":[{"value":"\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ESpeaker: \u003C\/strong\u003EProf. Tina Eliassi-Rad, Associate Professor, Dept. of Computer Science, Rutgers University\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EMeasuring Tie Strength in Implicit Social Networks\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u0022Given a set of people and a set of events attended by them, we address the problem of measuring connectedness or tie strength between each pair of persons. The underlying assumption is that attendance at mutual events gives an implicit social network between people. We take an axiomatic approach to this problem. Starting from a list of axioms, which a measure of tie strength must satisfy, we characterize functions that satisfy all the axioms. We then show that there is a range of tie-strength measures that satisfy this characterization.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EA measure of tie strength induces a ranking on the edges of the social network (and on the set of neighbors for every person). We show that for applications where the ranking, and not the absolute value of the tie strength, is the important thing about the measure, the axioms are equivalent to a natural partial order. To settle on a particular measure, we must make a non-obvious decision about extending this partial order to a total order. This decision is best left to particular applications. We also classify existing tie-strength measures according to the axioms that they satisfy; and observe that none of the \u0022\u0022self-referential\u0022\u0022 tie-strength measures satisfy the axioms. In our experiments, we demonstrate the efficacy of our approach; show the completeness and soundness of our axioms, and present Kendall Tau Rank Correlation between various tie-strength measures. Time-permitting, I will discuss the big data issues of measuring tie-strength and applications of our work in the wild (e.g., the WaPo Social Reader).\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EBio: \u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003ETina Eliassi-Rad is an Associate Professor of Computer Science at Rutgers University. Before joining academia, she was a Member of Technical Staff and Principal Investigator at Lawrence Livermore National Laboratory. Tina earned her Ph.D. in Computer Sciences (with a minor in Mathematical Statistics) at the University of Wisconsin-Madison. Within data mining and machine learning, Tina\u0027s research has been applied to the World-Wide Web, text corpora, large-scale scientific simulation data, complex networks, and cyber situational awareness. She has published over 50 peer-reviewed papers (including a best paper runner-up award at ICDM\u002709 and a best interdisciplanary paper award at CIKM\u002712); and has given over 70 invited presentations. Tina is an action editor for the Data Mining and Knowledge Discovery Journal. In 2010, she received an Outstanding Mentor Award from the US DOE Office of Science and a Directorate Gold Award from Lawrence Livermore National Laboratory for work on cyber situational awareness. Visit \u003Ca href=\u0022http:\/\/eliassi.org\u0022 title=\u0022http:\/\/eliassi.org\u0022\u003Ehttp:\/\/eliassi.org\u003C\/a\u003E for more details.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"The topic of the seminar is \u0022Measuring Tie Strength in Implicit Social Networks.\u0022"}],"uid":"27439","created_gmt":"2013-04-19 10:11:19","changed_gmt":"2016-10-08 02:03:21","author":"Lometa Mitchell","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2013-04-26T15:00:00-04:00","event_time_end":"2013-04-26T16:00:00-04:00","event_time_end_last":"2013-04-26T16:00:00-04:00","gmt_time_start":"2013-04-26 19:00:00","gmt_time_end":"2013-04-26 20:00:00","gmt_time_end_last":"2013-04-26 20:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"47223","name":"College of Computing"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Cstrong\u003EHost: \u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EPolo Chau: \u003Ca href=\u0022mailto:polo@gatech.edu\u0022\u003Epolo@gatech.edu\u003C\/a\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}}}