Decoding Social Sentiment in DAO: A Comparative Analysis of Blockchain Governance Communities
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Abstract (arXiv)
Blockchain technology is leading a revolutionary transformation across diverse industries, with effective governance being critical for the success and sustainability of blockchain projects. Community forums, pivotal in engaging decentralized autonomous organizations (DAOs), significantly impact blockchain governance decisions. Concurrently, Natural Language Processing (NLP), particularly sentiment analysis, provides powerful insights from textual data. While prior research has explored the potential of NLP tools in social media sentiment analysis, there is a gap in understanding the sentiment landscape of blockchain governance communities. The evolving discourse and sentiment dynamics on the forums of top DAOs remain largely unknown. This paper delves deep into the evolving discourse and sentiment dynamics on the public forums of leading DeFi projects: Aave, Uniswap, Curve DAO, Yearn.finance, Merit Circle, and Balancer, focusing primarily on discussions related to governance issues. Our study shows that participants in decentralized communities generally express positive sentiments during Discord discussions. Furthermore, there is a potential interaction between discussion intensity and sentiment dynamics; higher discussion volume may contribute to a more stable sentiment from code analysis. The insights gained from this study are valuable for decision-makers in blockchain governance, underscoring the pivotal role of sentiment analysis in interpreting community emotions and its evolving impact on the landscape of blockchain governance. This research significantly contributes to the interdisciplinary exploration of the intersection of blockchain and society, specifically emphasizing the decentralized blockchain governance ecosystem. We provide our data and code for replicability as open access on GitHub.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 31 Oct 2023.
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Citing papers per year: 2024: 3; 2025: 0; 2026: 2.
5 papers.
- 2024DAM: A Universal Dual Attention Mechanism for Multimodal Timeseries Cryptocurrency Trend Forecastingcited by 2
- 2024Global Public Sentiment on Decentralized Finance: A Spatiotemporal Analysis of Geo-tagged Tweets from 150 Countriescited by 1
- 2024FinML-Chain: A Blockchain-Integrated Dataset for Enhanced Financial Machine Learningcited by 1
- 2026Leveraging Large Language Models for Sentiment Analysis: Multi-Modal Analysis of Decentraland's MANA Tokencited by 0
- 2026Agentic Analysis for Agentic Infrastructure: An LLM-Powered Pipeline for Comparative Governance of DAO and Corporate AI Protocolscited by 0
- 2026Agentic Analysis for Agentic Infrastructure: An LLM-Powered Pipeline for Comparative Governance of DAO and Corporate AI Protocols24 Jun 2026
- 2026Leveraging Large Language Models for Sentiment Analysis: Multi-Modal Analysis of Decentraland's MANA Token4 Apr 2026
- 2024FinML-Chain: A Blockchain-Integrated Dataset for Enhanced Financial Machine Learning25 Nov 2024
- 2024Global Public Sentiment on Decentralized Finance: A Spatiotemporal Analysis of Geo-tagged Tweets from 150 Countries1 Sep 2024
- 2024DAM: A Universal Dual Attention Mechanism for Multimodal Timeseries Cryptocurrency Trend Forecasting1 May 2024