Error Analysis for Political Prediction Software
Twitter serves as both a social network and a news medium with many registered politicians using it to reach out to public and serves as a source of political news and opinion. It has, therefore, become a primary source for polling interest during electoral periods. These factors make it ideal to extract and analyze the language sentiments around a political candidate which can potentially lead to the discernment of the public voting intentions.
In collaboration with Eyesover Technologies, the goal of this project is to analyze the error of the Eyesover Political prediction software, and potentially increase the precision of inferring the voting intent of the general public towards a specific political candidate in an election. Error analysis and the evaluation of the results calculated by the Eyesover software can be provided by employing statistical automated analysis. The forecasting accuracy of the Eyesover system can be evaluated by comparing the calculated results to historical data.
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