Understanding the characteristics of real and fake news by using different social analytics techniques
Photo by Markus Winkler from Pexels
The ease of sharing information through online media has arguably benefited society by creating a more informed populace, many of whom were able to directly benefit from the new jobs created in areas such as advertising and IT. At the same time, it has been commonly argued that online media has facilitated sharing of false information (‘fake news’) which has caused more harm than good to robust public discourse. Governments around the world have been confronted with serious questions about how they should address online fake news.
In the Singapore context, the 2020 General Election was significant not only because it came amidst the COVID-19 pandemic, but because it will be the first election since the implementation of the Protection from Online Falsehoods and Manipulation Act (POFMA). POFMA aims to balance online debates by requiring tech companies to publish clarifications to false statements as decided by the Government. This approach has been the subject of intense debate1, particularly the lines between a false statement of fact (which can be dealt with under POFMA) and statement of opinion (which cannot) – which are rarely clear cut.