How Do Humans Assess the Credibility on Web Blogs: Qualifying and Verifying Human Factors with Machine Learning

Yonggeol Jo, Minwoo Kim, Kyungsik Han

Abstract: The purpose of this paper is to understand the factors involved when a human judges the credibility of information and to develop a classification model for weblogs, a primary source of information for many people. Considering both computational and human-centered approaches, we conducted a user study designed to consider two cognitive procedures--(1) visceral, behavioral and (2) reflective assessments--in the evaluation of information credibility. The results of the 80-participant study highlight that human cognitive processing varies according to an individual's purpose and that humans consider the structures and styles of content in their reflective assessments. We experimentally proved these findings through the development and analysis of classification models using 16,304 real blog posts written by 2,944 bloggers. Our models yield greater accuracy and efficiency than the models with well-known best features identified in prior research