  Independent fact-checking organizations have emerged as the crusaders to
debunk fake news. However, they may not always remain neutral, as they can be
selective in the false news they choose to expose and in how they present the
information. They can deviate from neutrality by being selective in what false
news they debunk and how the information is presented. Prompting the now
popular large language model, GPT-3.5, with journalistic frameworks, we
establish a longitudinal measure (2018-2023) for political neutrality that
looks beyond the left-right spectrum. Specified on a range of -1 to 1 (with
zero being absolute neutrality), we establish the extent of negative portrayal
of political entities that makes a difference in the readers' perception in the
USA and India. Here, we observe an average score of -0.17 and -0.24 in the USA
and India, respectively. The findings indicate how seemingly objective
fact-checking can still carry distorted political views, indirectly and subtly
impacting the perception of consumers of the news.
