Research Update: Siting Dispute Characterization

Research Update: Siting Dispute Characterization

Research Update: Siting Dispute Characterization

Aug 16, 2023

Understanding Sentiment Towards Renewable Energy Projects: A Comprehensive Study

Our nation's quest to meet its decarbonization goals is facing a surprising challenger: local opposition to large-scale renewable energy projects. A recent report from the Sabin Center for Climate Change Law has brought to light an unexpected number of local ordinances and opposition against renewable energy projects.

Why the Opposition?

While it's easy to dismiss these objections as NIMBYism (Not-In-My-Backyard-ism), our research team at MIT found that these concerns often stem from valid issues. Environmental and aesthetic harm, potential property value decreases, health threats, improper Tribal consultation, and accountability gaps are among the reasons driving opposition.

The Need for a National Database

Despite these widespread issues, there's no openly-accessible national database that documents these opposition reasons or quantifies their impact on our decarbonization goals. This is where our research comes in.

Our Research Approach

To understand the sentiments towards renewable energy projects, we're embarking on a detailed analysis of the scope, scale, and nature of both positive and negative sentiment surrounding utility-scale renewable energy projects in the U.S.

Computational Process: Workflow Created in Oloren Orchestrator

Step 1: Filtering

We're utilizing BrightData’s web scraping SERP API to gather search engine results for both operational and proposed renewable energy projects. These results are then sifted through using GPT-4 AI to determine their relevance to our research.

Step 2: Feature Extraction

Next, we extract prominent features from the relevant textual data, including public materials such as news articles, legal documents, and local proceedings. This gives us a comprehensive summary of each project, including the classification of proponents and opponents, any delays, and occurrences of lawsuits or legal actions.

Step 3: Quantitative Scoring

Finally, using the summaries and metadata, we conduct a quantitative scoring of sentiment for each project. We're also ensuring the accuracy of our AI-generated results through manual verification and statistical validation.

Open-Access Database and the Future

We're not keeping our findings to ourselves. Our plan is to add these case summaries and sentiment scores to an open-access database. We hope this resource will assist a diverse range of stakeholders - developers, policymakers, community members, and academics - in understanding and addressing the opposition to renewable energy projects.

Our project is not just about understanding sentiment, it's also a pioneer in utilizing AI for case-study based qualitative research, potentially revolutionizing social science data collection.

Our goal is to facilitate a smoother transition to renewable energy, by understanding and addressing the very real concerns of the communities these projects affect. With this initiative, we aim to bring everyone on board in our journey towards a sustainable future.