Call for Papers: JCDL 2019 Workshop on Organizing Data, Information, and
Knowledge in Big Data Environments
Deadline: Extensive summary submission due April 5, 2019
This workshop will provide an opportunity for participants – information and computing researchers and professionals who work in the areas of information organization, information retrieval, knowledge management, data mining, and Big Data analytics — to get together and exchange research ideas on organizing access to data, information, and knowledge in Big Data environments. Continue reading
Funding: 2019 LEADS Doctoral Summer Fellowship
Application Deadline Sunday, February 17, 2019 at 11:59 PM (EST).
The Metadata Research Center (MRC) at Drexel University’s College of Computing and Informatics (CCI) invites doctoral students to participate in the LIS Education and Data Science-4-the National Digital Platform (LEADS-4-NDP) program. This is a virtual fellowship program; applicants from any geographic location are eligible for consideration. The deadline for applications is Sunday, February 17 at 11:59 PM (EST). Information on last year’s (2018) LEADS Fellows can be found at: http://cci.drexel.edu/mrc/research/leads/leads-4-ndp-fellows/.
Mangels Lecture – Samuel Sinyangwe, “Using Data to Advance Racial Justice”
February 13, 2019
Mangels lecturer and nationally-recognized activist Samuel Sinyangwe will be visiting the iSchool February 12-14, with the majority of the events occurring on the 13th. Due to the nature of the events, individual RSVPs are required.
Every quarter the Economics Undergraduate Board (EUB) holds a seminar around some academic topic, and this quarter it is about data science. The guest lecturer is a head statistician and economist at Amazon who has been a pioneer of data science as a field.
InfoCamp is an unconference for information and technology professionals in Seattle. Our focus on information invites cross-pollination from all corners of the information world: IA/UX, Data Science, Library Science, Web Development, and beyond!
Tickets and Information: https://www.eventbrite.com/e/infocamp-seattle-2015-tickets-18390506500
Friday, Dec 19, 2015, 7:00 PM
Film: “THE HUMAN FACE OF BIG DATA”
(56 min, Sandy Smolan, 2014)
With the rapid emergence of online devices from cell phones to tablets to PCs, an unstoppable, invisible force is changing human lives in ways from the microscopic to the gargantuan: Big Data, a word that was barely used a few years ago but now governs the day for many of us. This massive gathering and analyzing of data in real time is allowing us to not only address some of humanity’s biggest challenges but is also helping create a new kind of planetary nervous system. The Human Face of Big Data captures the promise and peril of this extraordinary knowledge revolution. Join us following the film for a great discussion. (Event Is Open to the Public. Admission is by Donation.)
UW Data Science Seminar – Jure Leskovec – October 8th, 3:30pm – MGH 389
UW Data Science Seminar: Analysis, Visualization & Discovery
Wednesday October 8, 3:30pm
389 Mary Gates Hall
Can Cascades be Predicted?
Jure Leskovec, Assistant Professor of Computer Science, Stanford University
Social networks play a central role in spreading of information, ideas, behaviors, and products. As such “contagions” diffuse from a person to person they may go “viral,” and large cascades can form. However, a growing body of research has argued that virality and cascades may be inherently unpredictable. Thus, one of the central questions is whether information cascades can be predicted and possibly even engineered. In this talk, I will discuss a framework for predicting cascades and making them go viral.
We study large sample of cascades on Facebook and find strong performance in predicting whether a cascade will continue to grow in the future. The models we develop help us understand how to create viral social media content: by using the right title, for the right community, at the right time.
Jure Leskovec is assistant professor of Computer Science at Stanford University. His research focuses on mining large social and information networks. Problems he investigates are motivated by large scale data, the Web and on-line media. This research has won several awards including a Microsoft Research Faculty Fellowship, the Alfred P. Sloan Fellowship and numerous best paper awards. Leskovec received his bachelor’s degree in computer science from University of Ljubljana, Slovenia, and his PhD in in machine learning from the Carnegie Mellon University and postdoctoral training at Cornell University. You can follow him on Twitter @jure.