Dr. Richi NayakAcademic Lead: Development and Diversity, School of Computer Science;
Program Leader: Applied Data Science, Centre for Data Science;
Professor, Science and Engineering Faculty, Queensland University of Technology, Australia
Speech Title: Machine Learning Methods Elucidating Good and Bad of Social Media Data
Abstract: The proliferation of social media has created new norms in society. Incidents of abuse, hate, harassment and misogyny are widely spread across the social media platforms. Simultaneously, social media platforms facilitate sharing meaningful ideas and thoughts. In this talk, I will explore the ‘bad’ and ‘good’ of social media and present two novel applications with innovative machine learning methods. The first application will be ‘Twitter Misogynist Abuse Detection’ with a progressive Transfer Learning-based Deep Learning approach. The second application will be ‘Emergent Trend Discovery’ with a rank-centred clustering approach. Outcomes of these applications boost the social media monitoring capability and can assist policymakers and government to focus on key issues.
Biography: Richi Nayak is Leader of the Applied Data Science Program at the Centre of Data Science and Professor at Queensland University of Technology, Brisbane Australia. She has a driving passion to address pressing societal problems by innovating Artificial Intelligence field underpinned by fundamental research in machine learning. Her research has resulted in the development of novel solutions to address industry-specific problems in Marketing, K-12 Education, Agriculture, Digital humanities, and Mining. She has made multiple advances in social media mining, deep neural networks, multi-view learning, matrix/tensor factorization, clustering and recommender systems. She has authored over 180 high-quality refereed publications that have attracted over 3330 citations and a h-index of 30. Her research leadership is recognised by multiple best paper awards and nominations at international conferences, QUT Postgraduate Research Supervision awards, and the 2016 Women in Technology (WiT) Infotech Outstanding Achievement Award in Australia. She holds a PhD in Computer Science from the Queensland University of Technology and a Masters in Engineering from IIT Roorkee.