  (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. While
various qualitative, as well as quantitative measures of balance, have been
suggested in the literature, a comprehensive analysis of all these measures
across a large dataset of the post-truth era comprising different popular news
media houses and over a sufficiently long temporal scale in a non-US democratic
setting is lacking. We use this concept of balance to measure and understand
the evolution of imbalance in Indian media on various journalistic metrics on a
month-by-month basis. 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 find that two out of the three
news outlets are more strongly clustered in their imbalance metrics. We also
observe that only a few locations are extensively covered across all the news
outlets and the situation is only slightly getting better for one of the three
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. Further, cloze tests
clearly portray the changing popularity profile of the political parties over
time.
