Analysing the Extent of Misinformation in Cancer Related Tweets

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.

NARMADA: Need and Available Resource Managing Assistant for Disasters and Adversities

“…Local volunteers might be provided with a mobile app to help them find nearby needs and availabilities. Misinformation in twitter is common (Bal et al, 2020). The volunteers would also need a facility to confirm that the posted needs and availabilities are indeed genuine, concerning various parameters such as quantity (since at times of disasters, needs may be…”