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Analytical Survey - Transparency in Online Informative Technology

EasyChair Preprint no. 2491

5 pagesDate: January 29, 2020


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 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, journalism, neural net, neural network, Online News Articles, polarity

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  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 no. 2491},

  year = {EasyChair, 2020}}
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