Social Listening and Public Opinion Sentiment

Impact generated: #SocialListening #SentimentAnalysis #PublicOpinionMonitoring #PoliticalAnalytics #DataDrivenInsights #OnlineSentiment #SocialMediaAnalysis #PoliticalIntelligence

(Q2 2016)

In this project I developed a methodology and led the team that delivered the monitoring, analysis and forecast of public sentiment in Brazil regarding the impeachment of then President Dilma Rousseff. It consisted of the daily collection of public data from social media platforms (Facebook and Twitter), major media editorial articles, and selected politics experts. It also identified the emergence of new influencers in the public arena on this topic. These data sources were then transformed into comprehensive datasets within an on-premise architecture. This infrastructure enabled sentiment analysis, diffusion, and reach assessment, culminating in a positive sentiment score index.

The methodology was subsequently applied to analyze the online interactions of a few hundreds of politicians and powerbrokers, congress representatives and senators, tracking their positions and the pressure exerted by constituents. This provided insights into the political climate and modeled the sentiment among key decision-makers.

The aggregated analyses were delivered to clients daily, offering real-time updates on public opinion. The model's accuracy was validated by its precise predictions across the four voting rounds that ultimately led to President Rousseff's impeachment in 2016. This project demonstrates my ability to design and implement sophisticated social listening and sentiment analysis systems, providing valuable insights in high-stakes political scenarios.