Data / Engineering / Psychology / Technology
Challenges in combating disinformation on social media
This event is part of the Melbourne Centre for Data Science’s Seminar Series.
The Melbourne Centre for Data Science Seminar Series is an engaging monthly virtual seminar series hosting international experts and covering various focus areas and current research in data science.
This month – “Some Challenges in Combating Disinformation on Social Media”
In recent years, disinformation has become a global phenomenon, particularly so during times of crises such as the pandemic of COVID-19. Disinformation appears in a gamut of types from scams to conspiracy theories, to political campaigns, and to rumours. The wide dissemination of disinformation can have harmful impact on individuals and the society.
Despite the recent progress in detecting fake news, disinformation detection and mitigation remains a defying task due to its scale, complexity, diversity, speed, and costs of fact-checking or annotation, as well as social and psychological factors. In this talk, we look at some lessons learned when exploring strategies of detecting disinformation and fake news and discuss challenges in disinformation research and the pressing need for interdisciplinary research.
This talk is mainly based on Dr. Kai Shu’s doctoral research at ASU. Melbourne Centre for Data Science is pleased to host Dr. Huan Liu, a professor of Computer Science and Engineering at Arizona State University. Before he joined ASU, he worked at Telecom Australia Research Labs and was on the faculty at National University of Singapore. He is a co-author of a text, Social Media Mining: An Introduction, Cambridge University Press and a recent monograph, Detecting Fake News on Social Media, Morgan & Claypool Publishers.
He is a founding organiser of the International Conference Series on Social Computing, Behavioral-Cultural Modeling, and Prediction, and Field Chief Editor of Frontiers in Big Data and its Specialty Chief Editor of Data Mining and Management. He is also a Fellow of ACM, AAAI, AAAS, and IEEE. Dr Liu’s website is http://www.public.asu.edu/~huanliu
Prof Huan Liu- Computer Science & Engineering, Arizona State University
Prof Huan Liu’s research focuses on developing computational methods for data mining, machine learning, and social computing, and designing efficient algorithms to enable effective problem solving ranging from basic research, text/Web mining, bioinformatics, image mining, to real-world applications.
His work includes (i) dealing with high dimensional data via feature selection and feature discretization; (ii) social media mining/social computing, identifying the influentials in the blogosphere, group profiling and interaction; (iii) integrating multiple data sources to overcome ambiguity and uncertainty, (iv) employing domain knowledge for effective mining and information integration, and (v) assisting human experts by developing effective methods of ensemble learning, and active learning with hierarchical classification, subspace clustering, and meta data.