Who will be evicted from Big Brother Brazil? Forecasting based on social networking

Abstract: The advent of social media has provided individuals with a platform for the expression of opinions and preferences on an extensive range of subjects. The data obtained from social media can be a valuable source of information for the analysis of audience intentions and interests, thereby facilitating the process of informed decision-making and strategy development. One example of human behavior analysis is the examination of popular voting events. In order to address the challenge of forecasting a sequence of events in the context of voting, we propose a novel methodology that employs a data-driven solution, incorporating Twitter/X data and regression models. In this case study, we employed techniques commonly utilized in electoral outcome forecasting, including volumetric and sentiment analysis, to predict the eviction of contestants in Big Brother Brazil. Our experiments resulted in an average absolute error of approximately 11, with an accuracy of 81.25% for predicting evictions and 68.75% for forecasting the classification order.