Papers by Zeqiang Wang

3 papers
Revealing COVID-19’s Social Dynamics: Diachronic Semantic Analysis of Vaccine and Symptom Discourse on Twitter (2024.findings-emnlp)

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Challenge: Social media data provide a new source for social science and cultural analysis research, but its analysis is challenging due to the semantic shift phenomenon, where word meanings evolve over time.
Approach: They propose an unsupervised dynamic word embedding method to capture longitudinal semantic shifts in social media data without predefined anchor words.
Outcome: The proposed method captures longitudinal semantic shifts in social media data without predefined anchor words and leverages word co-occurrence statistics and dynamic updating to adapt embeddings over time.
DLIR: Spherical Adaptation for Cross-Lingual Knowledge Transfer of Sociological Concepts Alignment (2025.findings-emnlp)

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Challenge: Existing methods for identifying nuanced sociological concepts fail to capture domain-specific subtleties or require extensive parallel data.
Approach: a new approach to aligning nuanced sociological concepts is proposed . a dual-branch LoRA approach captures core semantics and counteracts specific language perturbations.
Outcome: a new approach outperforms baselines on cross-lingual sociological concept retrieval across 10 languages.
YATO: Yet Another deep learning based Text analysis Open toolkit (2023.emnlp-demo)

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Challenge: YATO is an open-source toolkit for text analysis with deep learning . it supports free combinations of three types of widely used features .
Approach: They introduce YATO, an open-source toolkit for text analysis with deep learning.
Outcome: YATO is an open-source toolkit for text analysis with deep learning . the toolkit supports free combinations of three types of widely used features .

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