79 citations · 128 across the 19 of their papers we have counts for
12 papers
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.…
MOMENTA: A Multimodal Framework for Detecting Harmful Memes and Their Targets
Shraman Pramanick, Shivam Sharma, Dimitar Dimitrov +3
Internet memes have become powerful means to transmit political, psychological, and socio-cultural ideas. Although memes are typically humorous, recent days have witnessed an escal…
DESYR: Definition and Syntactic Representation Based Claim Detection on the Web
Megha Sundriyal, Parantak Singh, Md Shad Akhtar +2
The formulation of a claim rests at the core of argument mining. To demarcate between a claim and a non-claim is arduous for both humans and machines, owing to latent linguistic va…
Multi-modal Sarcasm Detection and Humor Classification in Code-mixed Conversations
Manjot Bedi, Shivani Kumar, Md Shad Akhtar +1
Sarcasm detection and humor classification are inherently subtle problems, primarily due to their dependence on the contextual and non-verbal information. Furthermore, existing stu…
HIT: A Hierarchically Fused Deep Attention Network for Robust Code-mixed Language Representation
Ayan Sengupta, Sourabh Kumar Bhattacharjee, Tanmoy Chakraborty +1
Understanding linguistics and morphology of resource-scarce code-mixed texts remains a key challenge in text processing. Although word embedding comes in handy to support downstrea…
Exercise? I thought you said 'Extra Fries': Leveraging Sentence Demarcations and Multi-hop Attention for Meme Affect Analysis
Shraman Pramanick, Md Shad Akhtar, Tanmoy Chakraborty
Today's Internet is awash in memes as they are humorous, satirical, or ironic which make people laugh. According to a survey, 33% of social media users in age bracket [13-35] send…