PDF versions of challenge papers and posters are located here.
2017 Challenge Problem 1st Place Award |
Thomson Rueters - Authors: Armineh Nourbakhsh, Xiaomo Liu, Quanzhi Li, Sameena Shah |
Title: Mapping the echo-chamber: Detecting and characterizing partisan networks on Twitter |
Videos listed in order:
Automated Fake News Detection Using Text Analysis and Machine Learning, presenter Vivek Singh
Identifying Bots that Spread Fake News, presenter Sumeet Kumar
Mapping the echo-chamber: detecting and characterizing partisan networks on Twitter, presenter Armineh Nourbakhsh
Detecting emotions and evocative text, presenter Ria Baldevia
Towards Developing Methodology to Stem the Tide of Fake News, presenter Kiran Kumar Bandeli
Automated Linguistic Classification of Fake and Real News, presenter Grayson Cupit
Exploring the content of misinformation from multiple perspectives, presenter Dian Hu
Framework for Understanding the Impact of Perspective on Classification of Fake News, presenter Andy Novobilski