Artwork

Contenido proporcionado por HackerNoon. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente HackerNoon o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.
Player FM : aplicación de podcast
¡Desconecta con la aplicación Player FM !

Concluding Our Characterizing Biases in Cable News Study

14:27
 
Compartir
 

Manage episode 419689486 series 3474160
Contenido proporcionado por HackerNoon. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente HackerNoon o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.

This story was originally published on HackerNoon at: https://hackernoon.com/concluding-our-characterizing-biases-in-cable-news-study.
The primary objective of this paper was to develop a model capable of characterizing the biases of cable news programs given a large volume of text data
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, #media-study, #bias-in-the-news, #us-cable-news-bias, #is-the-news-biased, 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 primary objective of this paper was to develop a model capable of characterizing the biases of cable news programs given a large volume of text data in the form of transcripts. Our focus was on analyzing gatekeeping bias, which pertains to the topics discussed on cable news programs, and writing style bias, which refers to the language used to discuss these topics.

  continue reading

166 episodios

Artwork
iconCompartir
 
Manage episode 419689486 series 3474160
Contenido proporcionado por HackerNoon. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente HackerNoon o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.

This story was originally published on HackerNoon at: https://hackernoon.com/concluding-our-characterizing-biases-in-cable-news-study.
The primary objective of this paper was to develop a model capable of characterizing the biases of cable news programs given a large volume of text data
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, #media-study, #bias-in-the-news, #us-cable-news-bias, #is-the-news-biased, 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 primary objective of this paper was to develop a model capable of characterizing the biases of cable news programs given a large volume of text data in the form of transcripts. Our focus was on analyzing gatekeeping bias, which pertains to the topics discussed on cable news programs, and writing style bias, which refers to the language used to discuss these topics.

  continue reading

166 episodios

כל הפרקים

×
 
Loading …

Bienvenido a Player FM!

Player FM está escaneando la web en busca de podcasts de alta calidad para que los disfrutes en este momento. Es la mejor aplicación de podcast y funciona en Android, iPhone y la web. Regístrate para sincronizar suscripciones a través de dispositivos.

 

Guia de referencia rapida

Escucha este programa mientras exploras
Reproducir