  The advancement in technology and accessibility of internet to each
individual is revolutionizing the real time information. The liberty to express
your thoughts without passing through any credibility check is leading to
dissemination of fake content in the ecosystem. It can have disastrous effects
on both individuals and society as a whole. The amplification of fake news is
becoming rampant in India too. Debunked information often gets republished with
a replacement description, claiming it to depict some different incidence. To
curb such fabricated stories, it is necessary to investigate such deduplicates
and false claims made in public. The majority of studies on automatic
fact-checking and fake news detection is restricted to English only. But for a
country like India where only 10% of the literate population speak English,
role of regional languages in spreading falsity cannot be undermined. In this
paper, we introduce FactDRIL: the first large scale multilingual Fact-checking
Dataset for Regional Indian Languages. We collect an exhaustive dataset across
7 months covering 11 low-resource languages. Our propose dataset consists of
9,058 samples belonging to English, 5,155 samples to Hindi and remaining 8,222
samples are distributed across various regional languages, i.e. Bangla,
Marathi, Malayalam, Telugu, Tamil, Oriya, Assamese, Punjabi, Urdu, Sinhala and
Burmese. We also present the detailed characterization of three M's
(multi-lingual, multi-media, multi-domain) in the FactDRIL accompanied with the
complete list of other varied attributes making it a unique dataset to study.
Lastly, we present some potential use cases of the dataset. We expect this
dataset will be a valuable resource and serve as a starting point to fight
proliferation of fake news in low resource languages.
