Analysing the Extent of Misinformation in Cancer Related Tweets

  • Rakesh Bal Indian Institute of Technology Kharagpur
  • Sayan Sinha Indian Institute of Technology Kharagpur
  • Swastika Dutta Indian Institute of Technology Kharagpur
  • Risabh Joshi Carnegie Mellon University
  • Sayan Ghosh University of North Carolina at Chapel Hill
  • Ritam Dutt Carnegie Mellon University

Abstract

Twitter has become one of the most sought after places to discuss a wide variety of topics, including medically relevant issues such as cancer. This helps spread awareness regarding the various causes, cures and prevention methods of cancer. However, no proper analysis has been performed, which discusses the validity of such claims. In this work, we aim to tackle the misinformation spread in such platforms. We collect and present a dataset regarding tweets which talk specifically about cancer and propose an attention-based deep learning model for automated detection of misinformation along with its spread. We then do a comparative analysis of the linguistic variation in the text corresponding to misinformation and truth. This analysis helps us gather relevant insights on various social aspects related to misinformed tweets.

Published
2020-05-26
How to Cite
Bal, R., Sinha, S., Dutta, S., Joshi, R., Ghosh, S., & Dutt, R. (2020). Analysing the Extent of Misinformation in Cancer Related Tweets. Proceedings of the International AAAI Conference on Web and Social Media, 14(1), 924-928. Retrieved from https://aaai.org/ojs/index.php/ICWSM/article/view/7359