A Multi-task Model for Emotion and Offensive Aided Stance Detection of Climate Change Tweets

authored by: Apoorva Upadhyaya, Marco Fisichella, Wolfgang Nejdl
Abstract: In this work, we address the United Nations Sustainable Development Goal 13: Climate Action by focusing on identifying public attitudes toward climate change on social media platforms such as Twitter. Climate change is threatening the health of the planet and humanity. Public engagement is critical to address climate change. However, climate change conversations on Twitter tend to polarize beliefs, leading to misinformation and fake news that influence public attitudes, often dividing them into climate change believers and deniers. Our paper proposes an approach to classify the attitude of climate change tweets (believe/deny/ambiguous) to identify denier statements on Twitter. Most existing approaches for detecting stances and classifying climate change tweets either overlook deniers' tweets or do not have a suitable architecture. The relevant literature suggests that emotions and higher levels of toxicity are prevalent in climate change Twitter conversations, leading to a delay in appropriate climate action. Therefore, our work focuses on learning stance detection (main task) while exploiting the auxiliary tasks of recognizing emotions and offensive utterances. We propose a multimodal multitasking framework MEMOCLiC that captures the input data using different embedding techniques and attention frameworks, and then incorporates the learned emotional and offensive expressions to obtain an overall representation of the features relevant to the stance of the input tweet. Extensive experiments conducted on a novel curated climate change dataset and two benchmark stance detection datasets (SemEval-2016 and ClimateStance-2022) demonstrate the effectiveness of our approach.
Organisation(s): L3S Research Centre
Type: Conference contribution
Pages: 3948-3958
No. of pages: 11
Publication date: 30.04.2023
Publication status: Published
Peer reviewed: Yes
ASJC Scopus subject areas: Computer Networks and Communications, Software
Sustainable Development Goals: SDG 13 - Climate Action
Electronic version(s): https://doi.org/10.1145/3543507.3583860 (Access: Closed)