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Developing a Natural Language Understanding Model to Characterize Cable News Bias

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Manage episode 419074984 series 3474160
Content provided by HackerNoon. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by HackerNoon or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

This story was originally published on HackerNoon at: https://hackernoon.com/developing-a-natural-language-understanding-model-to-characterize-cable-news-bias.
The increasing trend of political polarization in the U.S. is reflected in media consumption patterns that indicate partisan polarization.
Check more stories related to media at: https://hackernoon.com/c/media. You can also check exclusive content about #media, #media-bias-analysis, #media-bias-in-the-usa, #cable-news-bias, #stance-analysis, #natural-language-processing, #political-polarization, #bias-in-the-news, and more.
This story was written by: @mediabias. Learn more about this writer by checking @mediabias's about page, and for more stories, please visit hackernoon.com.
The increasing trend of political polarization in the U.S. is reflected in media consumption patterns that indicate partisan polarization. We develop an unsupervised machine learning method to characterize the bias of cable news programs without any human input. This method relies on the analysis of what topics are mentioned through Named Entity Recognition and how those topics are discussed through Stance Analysis.

  continue reading

159 episodes

Artwork
iconShare
 
Manage episode 419074984 series 3474160
Content provided by HackerNoon. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by HackerNoon or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

This story was originally published on HackerNoon at: https://hackernoon.com/developing-a-natural-language-understanding-model-to-characterize-cable-news-bias.
The increasing trend of political polarization in the U.S. is reflected in media consumption patterns that indicate partisan polarization.
Check more stories related to media at: https://hackernoon.com/c/media. You can also check exclusive content about #media, #media-bias-analysis, #media-bias-in-the-usa, #cable-news-bias, #stance-analysis, #natural-language-processing, #political-polarization, #bias-in-the-news, and more.
This story was written by: @mediabias. Learn more about this writer by checking @mediabias's about page, and for more stories, please visit hackernoon.com.
The increasing trend of political polarization in the U.S. is reflected in media consumption patterns that indicate partisan polarization. We develop an unsupervised machine learning method to characterize the bias of cable news programs without any human input. This method relies on the analysis of what topics are mentioned through Named Entity Recognition and how those topics are discussed through Stance Analysis.

  continue reading

159 episodes

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