WEBINAR: Social media Abuse Detection and Trend Prediction using Text Mining

#Social #Media #Text #Mining
Share

The proliferation of social media has created new norms in society. Incidents of abuse, hate, harassment and misogyny are widely spread across 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 text mining 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 to focus on key issues.


  Date and Time

  Location

  Hosts

  Registration


  • Date: 26 May 2021
  • Time: 05:30 PM to 07:00 PM
  • All times are (UTC+10:00) Brisbane
  • Add_To_Calendar_icon Add Event to Calendar
If you are not a robot, please complete the ReCAPTCHA to display virtual attendance info.
  • Contact Event Host
  • Starts 23 April 2021 10:07 AM
  • Ends 26 May 2021 05:35 PM
  • All times are (UTC+10:00) Brisbane
  • No Admission Charge

  Speakers

Dr Richi Nayak Dr Richi Nayak of Queensland University of Technology

Biography:

Richi Nayak is Leader of the Applied Data Science Program at the Centre of Data Science and Associate Professor at Queensland University of Technology, Brisbane Australia. She has a driving passion to address pressing societal problems by innovating Data Analytics technologies underpinned by fundamental research in Data and Text Mining. 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 3400+ citations and  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, India.

Email:

Address:Science and Engineering Faculty, Queensland University of Technology , Brisbane, Australia