TY - GEN
T1 - News company's link sharing on Twitter as informative advertising and content signaling
AU - Pak, Chankyung
N1 - Publisher Copyright:
Copyright © 2017 by the Association for Computing Machinery, Inc. (ACM).
PY - 2017/5/6
Y1 - 2017/5/6
N2 - As social media becomes one of the major sources of news, news companies are using it to advertise their individual news articles. This increases news companies' need to consider social media users' limited attention when they compete with a variety of contents generated by the users as well as news stories shared by other news companies. This work explores the implications of media companies' competition for limited attention from users on social media for news diversity. Using an economic model, I suggest a hypothesis that news companies are likely to share news articles with non-controversial topics to signal for their unshared news. To examine this hypothesis, I am analyzing sentiments of news articles that are shared and unshared on Twitter.
AB - As social media becomes one of the major sources of news, news companies are using it to advertise their individual news articles. This increases news companies' need to consider social media users' limited attention when they compete with a variety of contents generated by the users as well as news stories shared by other news companies. This work explores the implications of media companies' competition for limited attention from users on social media for news diversity. Using an economic model, I suggest a hypothesis that news companies are likely to share news articles with non-controversial topics to signal for their unshared news. To examine this hypothesis, I am analyzing sentiments of news articles that are shared and unshared on Twitter.
KW - Competition for limited attention
KW - News
KW - Signaling
KW - Social media
UR - http://www.scopus.com/inward/record.url?scp=85019580964&partnerID=8YFLogxK
U2 - 10.1145/3027063.3027124
DO - 10.1145/3027063.3027124
M3 - Conference contribution
AN - SCOPUS:85019580964
T3 - Conference on Human Factors in Computing Systems - Proceedings
SP - 312
EP - 315
BT - CHI 2017 Extended Abstracts - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems
PB - Association for Computing Machinery
T2 - 2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI EA 2017
Y2 - 6 May 2017 through 11 May 2017
ER -