Modeling Credibilty and bias in News articles with content and structure.

Credibility in the News: Do we need to read?


While news media biases and propaganda are a persistent problem for interpreting the true state of world affairs, increasing reliance on the internet as a primary news source has enabled the formation of hyper-partisan echo chambers and an industry where outlets benefit from purveying fake news. The presence of intentionally adversarial news sources challenges linguistic modeling of news article text. While modeling text content of articles is sufficient to identify bias, it is not capable of determining credibility. A structural model based on web links outperforms text models for fake news detection. Analysis of text based methods for bias detection reveals the existence of liberal words and conservative words, but there is no analogue for fake news words versus real news words.

The 2018 ACM Conference on Web Search and Data Mining