TY - GEN
T1 - Be careful what you read - Evidence of demand-driven media bias
AU - Dong, Hang
AU - Ren, Jie
AU - Nickerson, Jeffrey V.
N1 - Publisher Copyright:
© 2018 Association for Information Systems. All rights reserved.
PY - 2018
Y1 - 2018
N2 - This paper provides empirical evidence for demand-driven media bias. Social media allows mass media professionals to first discover what readers want to read and then please these readers with news articles tailored to reader's desires. To study this phenomenon, a large Chinese dataset involving 4.27 million pieces of stock news and with 43.17 million stock-related microblogs that span two years was examined. Specifically, social media facilitates the generation of homogenous reader beliefs. It also provides a tool to monitor reader beliefs and to help publishers to slant the news items to cater to the readers' aggregate beliefs.
AB - This paper provides empirical evidence for demand-driven media bias. Social media allows mass media professionals to first discover what readers want to read and then please these readers with news articles tailored to reader's desires. To study this phenomenon, a large Chinese dataset involving 4.27 million pieces of stock news and with 43.17 million stock-related microblogs that span two years was examined. Specifically, social media facilitates the generation of homogenous reader beliefs. It also provides a tool to monitor reader beliefs and to help publishers to slant the news items to cater to the readers' aggregate beliefs.
KW - Confirmation bias
KW - Mass media
KW - Media bias
KW - Social media
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M3 - Conference contribution
AN - SCOPUS:85054251707
SN - 9780996683166
T3 - Americas Conference on Information Systems 2018: Digital Disruption, AMCIS 2018
BT - Americas Conference on Information Systems 2018
T2 - 24th Americas Conference on Information Systems 2018: Digital Disruption, AMCIS 2018
Y2 - 16 August 2018 through 18 August 2018
ER -