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(Im)balance in the representation of news has always been a topic of debatein political circles.  The concept of balance has often been discussed and studied in the context ofthe social responsibility theory and the prestige press in the USA. Whilevarious qualitative, as well as quantitative measures of balance, have beensuggested in the literature, a comprehensive analysis of all these measuresacross a large dataset of the post-truth era comprising different popular newsmedia houses and over a sufficiently long temporal scale in a non-US democraticsetting is lacking. We use this concept of balance to measure and understandthe evolution of imbalance in Indian media on various journalistic metrics on amonth-by-month basis. For this study, we amass a huge dataset of over fourmillion political articles from India for 9+ years and analyze the extent andquality of coverage given to issues and political parties in the context ofcontemporary influential events for three leading newspapers. We use severalstate-of-the-art NLP tools to effectively understand political polarization (ifany) manifesting in these articles over time. We find that two out of the threenews outlets are more strongly clustered in their imbalance metrics. We alsoobserve that only a few locations are extensively covered across all the newsoutlets and the situation is only slightly getting better for one of the threenews outlets. Cloze tests show that the changing landscape of events getreflected in all the news outlets with border and terrorism issues dominatingin around 2010 while economic aspects like unemployment, GST, demonetization,etc. became more dominant in the period 2014 -- 2018. Further, cloze testsclearly portray the changing popularity profile of the political parties overtime.

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