Quantitative Characterization and Identification of the Company-Related Disinformation Channel Among Media

• Main Authors: Yongtian Yu, Guang Yu, Tong Li, Qingli Man, Qiuping Chen
• Format: Article
• Language: English
• Published: IEEE 2020-01-01
• Series: IEEE Access
• Subjects: Disinformation channel; machine learning; media; disinformation; information disorder; online news
• Online Access: https://ieeexplore.ieee.org/document/8984712/

In the Web 2.0 age, mass media disseminates the disinformation of companies and exerts considerable influence. How to manage this trend in a timely and effective fashion in this big data era has become difficult. In this study, we delve into this issue by trying to identify the core disseminators in the dissemination process. We propose the concept of a disinformation channel and quantitatively analyse these company-related disinformation channels among media outlets. By empirically analysing 4,689 disinformation news values and 330 channels in 2018, we reveal that the disinformation values and negative news values are characteristics. We also build automatic identification models to identify these channels from the media combined with machine learning algorithms. Our study sheds light on disinformation, thus providing managers with an empirical basis upon which to analyse the media and help them address the disinformation problem.