Analytical Survey - Transparency in Online Informative Technology

EasyChair Preprint 2491

Abstract

We are predicting the bias (left leaning or right leaning) in online news articles based on text of online articles collected and the publication. The rating (either Left or Right) was assigned by looking at the leaning of the publication as found on mediabiasfactcheck.com. As we know the importance of online news has evolved with the advancement in technology. In order to understand the biasness in online journalism related to text of an article, we used a deep Neural Net to make classifications based on the labelings assigned according to publication. If the political bias of the publisher creeps in and such a correlation is there the AI will be able to learn it. Our training produced a very accurate classification mode. This shows that online media is not as transparent when presenting news. The methodology is described ahead.

Keyphrases: Classification, Online News Articles, journalism, neural net, neural network, polarity

@booklet{EasyChair:2491,
  author    = {Disheak Ahlawat and Divyansh Khare and Divyanshi Tyagi and Gaurav Yadav and Mansi Panwar and Vinod Kumar},
  title     = {Analytical Survey - Transparency in Online Informative Technology},
  howpublished = {EasyChair Preprint 2491},
  year      = {EasyChair, 2020}}