Clickbait in Hindi News Media : A Preliminary Study

Vivek Kaushal, Kavita Vemuri


Abstract
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.
Anthology ID:
2020.icon-main.11
Volume:
Proceedings of the 17th International Conference on Natural Language Processing (ICON)
Month:
December
Year:
2020
Address:
Indian Institute of Technology Patna, Patna, India
Editors:
Pushpak Bhattacharyya, Dipti Misra Sharma, Rajeev Sangal
Venue:
ICON
SIG:
Publisher:
NLP Association of India (NLPAI)
Note:
Pages:
85–89
Language:
URL:
https://aclanthology.org/2020.icon-main.11
DOI:
Bibkey:
Cite (ACL):
Vivek Kaushal and Kavita Vemuri. 2020. Clickbait in Hindi News Media : A Preliminary Study. In Proceedings of the 17th International Conference on Natural Language Processing (ICON), pages 85–89, Indian Institute of Technology Patna, Patna, India. NLP Association of India (NLPAI).
Cite (Informal):
Clickbait in Hindi News Media : A Preliminary Study (Kaushal & Vemuri, ICON 2020)
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PDF:
https://aclanthology.org/2020.icon-main.11.pdf