Automated political bias classification in news agencies: a word-based feature selection approach

Anonymous

Abstract: This study offers a new solution to the problem of developing political bias classification models in news agencies. Our method uses search engine score functions to develop a measure of the relevance of each word in text scrapped from news websites. With these scores, we train models using existing feature selection methods and a custom feature selection algorithm that we developed. The resulting models are contrasted with each other and neural network-based counterparts. Models trained using our proposed method and custom algorithm outperformed others by achieving macro F1 scores of 0.81 and 0.78 on right-wing and left-wing bias detection respectively.

Paper Type: short