mlsanityData to 7 Oct 2026

MasonPerplexity at ClimateActivism 2024: Integrating Advanced Ensemble Techniques and Data Augmentation for Climate Activism Stance and Hate Event Identification

arXiv 2402.01976 ↗First posted 3 Feb 2024cs.CLcited by 3

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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

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  2. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,907
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  7. 2022T-NER: An All-Round Python Library for Transformer-based Named Entity Recognitioncited by 37
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  9. 2022Named Entity Recognition in Twitter: A Dataset and Analysis on Short-Term Temporal Shiftscited by 27
  10. 2018Detecting Offensive Language in Tweets Using Deep Learningcited by 23
  11. 2018Stance Detection on Tweets: An SVM-based Approachcited by 8
  12. 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.