Prof. Mark Last (Data Science Research Center, Ben-Gurion University of the Negev, Israel) will present “20 Years of Analyzing Multilingual Propaganda Content on the Web” at 8pm (UTC+1)/ 3pm EDT / 12 noon Arizona on 14 August. Click here to convert to your local time

Register at https://events.vtools.ieee.org/m/422750

This lecture is organised by Phoenix Computer Society Chapter and co-hosted by: UK and Ireland SSIT Chapter; Connecticut Section Jt Computer Society; SMC and SSIT Chapter; Northwest Florida Section Computer Society and Communications Chapter; Santa Clara Valley Section Computer Society Chapter; Lone Star Section Computer Society Chapter San Antonio; San Fernando Valley Section Jt. Computer Society and Communications Chapter; Orange County Section Computer Society Chapter; San Diego Section Computer Society Chapter; Hawaii Section Chapter, COM19/SP01/C16; IEEE New Jersey Coast Section SIGHT and New Jersey Coast Section Jt. IM and Computer Society Chapter,IM09/C16

Access to online Meeting
Registered participants will be provided with the link prior to the event.

Guest Lecture Focus
From its early years as a global information infrastructure, the Internet, originally designed by and for the US Department of Defense, has been efficiently and effectively misused by various hate groups who often consider the US government their worst enemy. For example, it turned out that WWW played a critical role in the preparation of the 9/11 attacks both as a source of inspirational information and as a safe means of covert communication between the plotters. Shortly after the tragic events of 2001, our binational team of US and Israeli researchers started to explore the online activities of various hate groups. Initially, we developed a prototype of a monitoring system aimed at detecting the frequent visitors of terrorist websites, which may become influenced by terrorist propaganda and eventually develop into what we call today “the lone wolf attackers”. Shortly after, we focused on another, closely related question: what makes terrorist-generated propaganda content in various languages different from unbiased news reports discussing similar topics? Over the years, we developed prototypes of several additional text analysis tools such as text summarization algorithms, which can automatically summarize large amounts of untranslated content in any language, as well as AI tools for automated detection of metaphoric language. After presenting the motivational and ethical foundations of our research, I plan to describe some of our methods and finally, discuss past and future challenges in this important and fascinating domain.