Stance detection on social media is an emerging opinion mining paradigm for various social
and political applications in which sentiment analysis may be sub-optimal. There has been a …

In today's social media-dominated landscape, digital platforms wield substantial influence
over public opinion, particularly during crucial political events such as electoral processes …

Stance detection, which focuses on users' deep attitudes, is an important way to understand
the online public opinion. This paper presents an overview of stance detection. First, we …

Despite recent concerns about undesirable behaviors generated by large language models
(LLMs), including non-factual, biased, and hateful language, we find LLMs are inherent multi …

Stance detection aims to detect the stance toward a corresponding target. Existing works
use the assumption that the target is known in advance, which is often not the case in the …

In the era of digital communication, social media platforms have experienced exponential
growth, becoming primary channels for information exchange. However, this surge has also …

Hate speech represents a pervasive and detrimental form of online discourse, often
manifested through an array of slurs, from hateful tweets to defamatory posts. As such …

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 …

Content moderation is the process of flagging content based on pre-defined platform rules.
There has been a growing need for AI moderators to safeguard users as well as protect the …

We present the findings of the shared task at the CONSTRAINT 2022 Workshop: Hero,
Villain, and Victim: Dissecting harmful memes for Semantic role labeling of entities. The task …