Majority Voting

Majority voting, a simple yet powerful aggregation technique, aims to improve decision-making accuracy by combining multiple independent assessments. Current research focuses on its application in diverse fields, including sentiment analysis using large language models, crowdsourcing, and multi-class classification, exploring the impact of model independence and the effectiveness of various weighting schemes. Studies highlight the importance of considering factors like model independence and annotator reliability, revealing that while majority voting often enhances accuracy, its performance is sensitive to the underlying data and the independence of individual votes. This research has implications for improving the reliability of data aggregation in various applications, from automated systems to human-computer interaction.