Magnetics

Thursday November 24, 2016 at 12:00 p.m. Dr. Anatoliy Gruzd, Associate Professor of Ted Rogers School of Management and Canada Research Chair in Social Media Data Stewardship, will be presenting “Who Are We Studying in Social Media: Bots or Humans?”. Speaker: Dr. Anatoliy Gruzd Associate Professor Ted Rogers School of Management, Ryerson University Canada Research Chair in Social Media Data Stewardship Day & Time: Thursday, November 24, 2016 12:00 p.m. – 1:00 p.m. Location: Room ENG 288, George Vari Centre for Computing and Engineering, 245 Church Street Ryerson University, Toronto, Ontario, M5B 2K3 Map: http://www.ryerson.ca/maps – Look for ENG Organizers: IEEE Toronto Systems Chapter, Alexei Botchkarev IEEE Toronto WIE, Magnetics, Measurement/Instrumentation-Robotics, Computer Science Department of Ryerson University Maryam Davoudpour Registration: Registration is free, but space is limited. Please register via http://tinyurl.com/systemsChapterEvent24 Abstract: Researchers studying various online and computer-mediated communities used to be able to argue that the online is an extension of the offline, and that offline and online are just different slices of real life. But the increasing number of bots in our datasets and the increasing use of algorithmic filtering by social media giants are widening the gap between online and offline, and between computer-mediated and algorithm-driven communication. This in turn makes some online data less reliable, at least for those of us studying human behavior. It also begs the question, if we are using data from social media for modelling, are we modelling human behavior in social media or simply reverse engineering how bots and other algorithms operate? Therefore, there is an urgent need to better understand the nature of bots and algorithmic filtering, and their influence on users’ online interactions, not just from a computational, but also from sociological perspective. This talk will discuss some of the key challenges and possible solutions to detecting social bots in the context of conducting social media research. Biography: Dr. Anatoliy Gruzd is a Canada Research Chair in Social Media Data Stewardship, Associate Professor in the Ted Rogers School of Management at Ryerson University. He is also the Director of the Social Media Lab and a co-editor of a multidisciplinary journal on Big Data and Society published by Sage. Dr. Gruzd’s research initiatives explore how the advent of social media and the growing availability of social big data are changing the ways in which people communicate, collaborate and disseminate information and how these changes impact the social, economic and political norms and structures of modern society. Dr. Gruzd and his lab are also actively developing and evaluating new approaches and tools to support social media data analytics and stewardship. His research and commentaries have been reported across Canada and internationally in various mass media outlets such as Foreign Affairs, Los Angeles Times, Nature.com, The Atlantic, The Globe and Mail, The National Post, The Canadian Press, CBC TV, CBC Radio, CTV and Global TV.

Friday November 18, 2016 at 12:00 p.m. Dr. Andriy Miranskyy, Assistant Professor at the Department of Computer Science, Ryerson University, will be presenting “Operational-Log Analysis for Big Data Systems: Challenges and Solutions”. Speaker: Dr. Andriy Miranskyy Assistant Professor, Department of Computer Science, Ryerson University Day & Time: Friday, November 18, 2016 12:00 p.m. – 1:00 p.m. Location: George Vari Centre for Computing and Engineering Ryerson University Room: ENG 288 245 Church Street, Toronto, Ontario M5B 2K3 Map – http://www.ryerson.ca/maps – Look for ENG Registration: Registration is free, but space is limited. Please register via this link: http://tinyurl.com/systemsEvent Organizers: IEEE Toronto Systems Chapter, Alexei Botchkarev albot@ieee.org IEEE Toronto WIE, Magnetics, Measurement/Instrumentation-Robotics and Computer Science Department of Ryerson University IEEE Toronto WIE Chair: Maryam Davoudpour maryam.davoudpour@ieee.org Abstract: Big data systems (BDSs) are complex, consisting of multiple interacting hardware software components, such as distributed compute nodes, networking, databases, middleware, business intelligence layer, and high availability infrastructure. Any of these components can fail. Finding the failures’ root causes is extremely laborious. Analysis of BDS-generated logs can speed up this process. The logs can also help improve testing processes, detect security breaches, customize operational profiles, and aid with any other tasks requiring runtime-data analysis. However, practical challenges hamper log analysis tools’ adoption. The logs emitted by a BDS can be thought of as big data themselves. When working with large logs, practitioners face seven main issues: scarce storage, unscalable log analysis, inaccurate capture and replay of logs, inadequate log-processing tools, incorrect log classification, a variety of log formats, and inadequate privacy of sensitive data. This talk describes the challenges and practical solutions faced while building and institutionalizing dynamic analysis tools in the industry. Biography: Andriy Miranskyy is an assistant professor at the Department of Computer Science, Ryerson University. His research interests are in the area of mitigating risk in software engineering, focusing on software quality assurance, program comprehension, software requirements, project risk management, Big Data, and Green IT. Andriy received his Ph.D. in Applied Mathematics at the University of Western Ontario. He has 17 years of software engineering experience in information management and pharmaceutical industries. Prior to joining Ryerson, Andriy worked as a software engineer in the IBM Information Management division at the IBM Toronto Software Laboratory; currently, he is the Faculty Fellow of the IBM Centre for Advanced Studies. He has served as Guest Editor for a special edition of IEEE Software as well as organizer, committee member, and reviewer for several software engineering workshops and conferences.