  A corpus of Hindi news headlines shared on Twitter was created by collecting
tweets of 5 mainstream Hindi news sources for a period of 4 months. 7
independent annotators were recruited to mark the 20 most retweeted news posts
by each of the 5 news sources on its clickbait nature. The clickbait score
hence generated was assessed for its correlation with interactions on the
platform (retweets, favorites, reader replies), tweet word count, and
normalized POS (part-of-speech) tag counts in tweets. A positive correlation
was observed between readers' interactions with tweets and tweets' clickbait
score. Significant correlations were also observed for POS tag counts and
clickbait score. The prevalence of clickbait in mainstream Hindi news media was
found to be similar to its prevalence in English news media. We hope that our
observations would provide a platform for discussions on clickbait in
mainstream Hindi news media.
