MasonPerplexity at ClimateActivism 2024: Integrating Advanced Ensemble Techniques and Data Augmentation for Climate Activism Stance and Hate Event Identification
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Abstract (arXiv)
The task of identifying public opinions on social media, particularly regarding climate activism and the detection of hate events, has emerged as a critical area of research in our rapidly changing world. With a growing number of people voicing either to support or oppose to climate-related issues - understanding these diverse viewpoints has become increasingly vital. Our team, MasonPerplexity, participates in a significant research initiative focused on this subject. We extensively test various models and methods, discovering that our most effective results are achieved through ensemble modeling, enhanced by data augmentation techniques like back-translation. In the specific components of this research task, our team achieved notable positions, ranking 5th, 1st, and 6th in the respective sub-tasks, thereby illustrating the effectiveness of our approach in this important field of study.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 12 of its 22 references that are in the map. First posted on arXiv 3 Feb 2024.
Builds on
12 of 22 references.
References · 12
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
- 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,907
- 2020BERTweet: A pre-trained language model for English Tweetscited by 346
- 2019Predicting the Type and Target of Offensive Posts in Social Mediacited by 268
- 2020HateBERT: Retraining BERT for Abusive Language Detection in Englishcited by 206
- 2017Detecting Hate Speech in Social Mediacited by 42
- 2022T-NER: An All-Round Python Library for Transformer-based Named Entity Recognitioncited by 37
- 2021FBERT: A Neural Transformer for Identifying Offensive Contentcited by 30
- 2022Named Entity Recognition in Twitter: A Dataset and Analysis on Short-Term Temporal Shiftscited by 27
- 2018Detecting Offensive Language in Tweets Using Deep Learningcited by 23
- 2018Stance Detection on Tweets: An SVM-based Approachcited by 8
- 2023nlpBDpatriots at BLP-2023 Task 1: A Two-Step Classification for Violence Inciting Text Detection in Banglacited by 3
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Citing papers per year: 2024: 3.
3 papers.
- 2024MasonTigers at SemEval-2024 Task 8: Performance Analysis of Transformer-based Models on Machine-Generated Text Detectioncited by 1
- 2024Advancing Large Language Models for Spatiotemporal and Semantic Association Mining of Similar Environmental Eventscited by 1
- 2024MasonTigers at SemEval-2024 Task 10: Emotion Discovery and Flip Reasoning in Conversation with Ensemble of Transformers and Promptingcited by 0
- 2024Advancing Large Language Models for Spatiotemporal and Semantic Association Mining of Similar Environmental Events19 Nov 2024
- 2024MasonTigers at SemEval-2024 Task 10: Emotion Discovery and Flip Reasoning in Conversation with Ensemble of Transformers and Prompting30 Jun 2024
- 2024MasonTigers at SemEval-2024 Task 8: Performance Analysis of Transformer-based Models on Machine-Generated Text Detection22 Mar 2024