Speaker:Lin Miao
Title: Mining Multilingual
Social Media Content
Abstract:
During the past several years, a large amount of troll accounts has emerged with efforts to manipulate public opinion on social network sites. They are often involved in spreading misinformation, fake news, and propaganda with the intent of distracting and sowing discord. We aim to detect troll tweets in both English and Russian assuming that the tweets are generated by some “troll farm." We reduce this task to the authorship verification problem of determining whether a single tweet is authored by a “troll farm" account or not.
Facing the COVID-19 pandemic, governments have implemented a wide range of policies to contain the spread of the virus. During the pandemic, large amounts of COVID-19-related tweets emerge every day. Real-time processing of daily tweets may offer insights for monitoring public opinion about intervention measures implemented. We conducted a comprehensive analysis of public opinion about COVID-19 lockdown policy in New York State, to understand its relations with COVID-19 statistics and the intervention measures taken by the government.
Bio:
Lin is a Ph.D. student in the Department of Software and Information System Engineering at Ben-Gurion University of the Negev, under the supervision of Prof. Mark Last and Dr. Marina Litvak. Her research is focusing on natural language processing, data mining on social media.
