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THE 24TH PACIFIC-ASIA CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING |
Fake news is starting to be recognized as a global challenge that poses threats to democratic systems, public health, law and order as well as individual liberty and many other cornerstones of modern life. While the impact of fake news has been studied for many decades, the dangers of fake news rose into prominence over the last few years. Fake news allegedly has influenced electoral outcomes, and its impact in healthcare has been immense with it causing much uptake of alternative magical remedies lead to delayed disease presentation and poorer prognosis. The impact of fake news is both determined by the content of the news as well as by the channel of delivery to the reader, the latter being largely through new media sources such as social media and online websites. It is also notable that the spread and impact of fake news is facilitated by intrinsic human tendencies such as confirmation bias and the demonstrated inability of people to shrug off influence of fake news even after it having been debunked. The data science community has seen an increase in interest around fake news over the last many years, where the mainstream work has focused around identifying fake news within microblogging sites such as Twitter within the political domain. The computer science work in this emerging area has been spread wide and thin across avenues in artificial intelligence, machine learning, data mining, computer vision, multimedia and natural language processing. There has been much work outside computer science, from areas such as journalism, science communication, psychology and politics as well.
This workshop has a number of objectives:
* Avenue for Presenting Research: Provide a forum for presenting research in this emerging area of combating fake news leveraging data science methodologies. * Platform for Discussions: Provide a platform for researchers interested in this area to get together and engage in discussions on how this emerging area could shape up in the future. * Cross-pollination: Encourage researchers from across various parts of computer science, viz., natural language processing, computer vision and artificial intelligence, to share their perspectives and visions on this area, and help computing researchers to realize potential for cross-disciplinary approaches in this area to eliminate any systemic blind spots.
In order to facilitate the above objectives, we will use a non-conventional approach to the organization of this workshop, whereby we will have a mix of research paper presentations, keynote talks and panel discussions. The contributed program in this workshop will be primarily formed by a number of research papers presenting new research on data science for fake news. These would cover data science research for fake news, that could be traditionally be under the following heads in terms of methods: * Graph Analytics * Natural Language Processing * Deep Learning * Computer Vision * Image Processing * Affective Computing * Game Theory * Information Retrieval * Social Media Analytics * Spatio-temporal Data Mining * Unsupervised Learning * Semi-supervised Learning * Supervised Learning * Crowdsourcing and Active Learning We will particularly encourage papers that cover multiple such methodological building blocks in building a technology to combat fake news. We hope that this workshop will provide researchers attending PAKDD 2020 to engage in enriching topical discussions on the emerging area of fake news detection. We also expect to have a high-quality technical program with con- tributed papers which will enhance the PAKDD 2020 proceedings. Given the high interest in this topic, we expect this workshop to be well attended and that it would certainly supplement the PAKDD 2020 technical program. The key organizers would be the co-chairs of this workshop, who will be: * Tanmoy Chakraborty, Indraprastha Institute of Information Technology, tanmoy@iiitd.ac.in * Deepak P, Queen’s University Belfast, deepaksp@acm.org * Cheng Long, Nanyang Technological University, c.long@ntu.edu.sg * Santhosh Kumar, Cochin University of Science and Technology, san@cusat.ac.in
Tentative Program Committee members are as follows:
- Dinesh Garg, IBM Research - India, India
- Srikanta Bedathur, IIT Delhi, India
- Sutanu Chakraborti, IIT Madras, India
- Anna Jurek-Loughrey, Queen’s University Belfast, United Kingdom
- Sahely Bhadra, IIT Palakkad, India
- Joemon Jose, University of Glasgow, United Kingdom
- Xin Huang, Hong Kong Baptist University, Hong Kong
- Yixiang Fang, Guangzhou University, China
- Xin Cao, University of New South Wales, Australia
- Sarana Yi Nutanong, VISTECH, Thailand