(Im)balance in the Representation of News? An Extensive Study on a Decade Long Dataset from India

Abstract

(Im)balance in the representation of news has always been a topic of debate in political circles. The concept of balance has often been discussed and studied in the context of the social responsibility theory and the prestige press in the USA. Comprehensive analysis of all these measures across a large dataset of the post-truth era comprising different popular news media houses over a sufficiently long temporal scale in a non-US democratic setting is lacking. For this study, we amass a huge dataset of over four million political articles from India for 9+ years and analyze the extent and quality of coverage given to issues and political parties in the context of contemporary influential events for three leading newspapers. We use several state-of-the-art NLP tools to effectively understand political polarization (if any) manifesting in these articles over time. We also observe that only a few locations are extensively covered across all the news outlets. Cloze tests show that the changing landscape of events get reflected in all the news outlets with border and terrorism issues dominating in around 2010 while economic aspects like unemployment, GST, demonetization, etc. became more dominant in the period 2014–2018.