18 citations · 24 across the 7 of their papers we have counts for
6 papers · 1 filter
Domain-aware Self-supervised Pre-training for Label-Efficient Meme Analysis
Shivam Sharma, Mohd Khizir Siddiqui, Md. Shad Akhtar +1
Existing self-supervised learning strategies are constrained to either a limited set of objectives or generic downstream tasks that predominantly target uni-modal applications. Thi…
Detecting and Understanding Harmful Memes: A Survey
Shivam Sharma, Firoj Alam, Md. Shad Akhtar +7
The automatic identification of harmful content online is of major concern for social media platforms, policymakers, and society. Researchers have studied textual, visual, and audi…
DISARM: Detecting the Victims Targeted by Harmful Memes
Shivam Sharma, Md. Shad Akhtar, Preslav Nakov +1
Internet memes have emerged as an increasingly popular means of communication on the Web. Although typically intended to elicit humour, they have been increasingly used to spread h…
Detecting Harmful Memes and Their Targets
Shraman Pramanick, Dimitar Dimitrov, Rituparna Mukherjee +4
Among the various modes of communication in social media, the use of Internet memes has emerged as a powerful means to convey political, psychological, and socio-cultural opinions.…
Fighting an Infodemic: COVID-19 Fake News Dataset
Parth Patwa, Shivam Sharma, Srinivas Pykl +6
Along with COVID-19 pandemic we are also fighting an `infodemic'. Fake news and rumors are rampant on social media. Believing in rumors can cause significant harm. This is further…
On the Benefit of Combining Neural, Statistical and External Features for Fake News Identification
Gaurav Bhatt, Aman Sharma, Shivam Sharma +3
Identifying the veracity of a news article is an interesting problem while automating this process can be a challenging task. Detection of a news article as fake is still an open q…