273 citations · 301 across the 14 of their papers we have counts for
14 papers
MemeMQA: Multimodal Question Answering for Memes via Rationale-Based Inferencing
Siddhant Agarwal, Shivam Sharma, Preslav Nakov +1
Memes have evolved as a prevalent medium for diverse communication, ranging from humour to propaganda. With the rising popularity of image-focused content, there is a growing need…
Emotion-Aware Multimodal Fusion for Meme Emotion Detection
Shivam Sharma, Ramaneswaran S, Md. Shad Akhtar +1
The ever-evolving social media discourse has witnessed an overwhelming use of memes to express opinions or dissent. Besides being misused for spreading malcontent, they are mined b…
Recent Advances in Hate Speech Moderation: Multimodality and the Role of Large Models
Ming Shan Hee, Shivam Sharma, Rui Cao +4
In the evolving landscape of online communication, moderating hate speech (HS) presents an intricate challenge, compounded by the multimodal nature of digital content. This compreh…
MEMEX: Detecting Explanatory Evidence for Memes via Knowledge-Enriched Contextualization
Shivam Sharma, Ramaneswaran S, Udit Arora +2
Memes are a powerful tool for communication over social media. Their affinity for evolving across politics, history, and sociocultural phenomena makes them an ideal communication v…
Characterizing the Entities in Harmful Memes: Who is the Hero, the Villain, the Victim?
Shivam Sharma, Atharva Kulkarni, Tharun Suresh +4
Memes can sway people's opinions over social media as they combine visual and textual information in an easy-to-consume manner. Since memes instantly turn viral, it becomes crucial…
What do you MEME? Generating Explanations for Visual Semantic Role Labelling in Memes
Shivam Sharma, Siddhant Agarwal, Tharun Suresh +3
Memes are powerful means for effective communication on social media. Their effortless amalgamation of viral visuals and compelling messages can have far-reaching implications with…
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…
EXPERT: Public Benchmarks for Dynamic Heterogeneous Academic Graphs
Sameera Horawalavithana, Ellyn Ayton, Anastasiya Usenko +5
Machine learning models that learn from dynamic graphs face nontrivial challenges in learning and inference as both nodes and edges change over time. The existing large-scale graph…
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…
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…