From GenAI to Political Profiling Avatars: A Data-Driven Approach to Crafting Virtual Experts for Voting Advice Applications

Voting advice applications (VAAs) are pivotal web-based tools that guide citizens to align with political parties and candidates that match their preferences. Traditional methods for creating candidate profiles predominantly rely on questionnaire responses, a time-intensive and costly process. To address these challenges, we introduce a data-centric methodology utilizing generative artificial intelligence (GenAI), culminating in creating political avatars. These political avatars are engineered using cutting-edge large language models (LLMs), including GPT-4 and Bard. They are adept at processing and interpreting data primarily sourced from Twitter and leveraging bespoke, self-trained datasets. Integrating advanced AI technology with diverse data sources equips political avatars with unprecedented analytical and predictive capabilities, setting a new standard in political analysis. Unlike traditional methods, political avatars are adept at emulating the responses of real politicians or experts, showcasing a remarkable capacity to interact with VAA surveys. This novel approach presents the potential to either compete with or enhance the insights traditionally obtained from human experts. Another critical aspect of our study is comparing political avatars and previous research employing question-answering (QA) models based on advanced natural language processing (NLP) techniques for political profiling. This comparative analysis reveals that Political Avatars offer a significantly more robust solution for profile construction. While QA models provide structured responses based on specific queries, political avatars bring an element of dynamism and depth, capable of generating nuanced, context-aware responses. This shift from static, questionnaire-based profiling to dynamic, AI-driven avatars marks a substantial leap in political analysis. Generative AI in crafting Political Avatars introduces a transformative element to data analysis. This approach facilitates a layered and more sophisticated interpretation of political stances, moving beyond the limitations of traditional profiling methods. By employing political avatars, our methodology not only streamlines the profiling process but also enriches the quality of insights derived, paving the way for a more nuanced understanding of the political landscape.