TY - GEN
T1 - View, like, comment, post
T2 - 13th International AAAI Conference on Web and Social Media, ICWSM 2019
AU - Aldous, Kholoud Khalil
AU - An, Jisun
AU - Jansen, Bernard J.
N1 - Publisher Copyright:
Copyright © 2019, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
PY - 2019
Y1 - 2019
N2 - We evaluate the effects of the topics of social media posts on audiences across five social media platforms (i.e., Facebook, Instagram, Twitter, YouTube, and Reddit) at four levels of user engagement. We collected 3,163,373 social posts from 53 news organizations across five platforms during an 8-month period. We analyzed the differences in news organization platform strategies by focusing on topic variations by organization and the corresponding effect on user engagement at four levels. Findings show that topic distribution varies by platform, although there are some topics that are popular across most platforms. User engagement levels vary both by topics and platforms. Finally, we show that one can predict if an article will be publicly shared to another platform by individuals with precision of approximately 80%. This research has implications for news organizations desiring to increase and to prioritize types of user engagement.
AB - We evaluate the effects of the topics of social media posts on audiences across five social media platforms (i.e., Facebook, Instagram, Twitter, YouTube, and Reddit) at four levels of user engagement. We collected 3,163,373 social posts from 53 news organizations across five platforms during an 8-month period. We analyzed the differences in news organization platform strategies by focusing on topic variations by organization and the corresponding effect on user engagement at four levels. Findings show that topic distribution varies by platform, although there are some topics that are popular across most platforms. User engagement levels vary both by topics and platforms. Finally, we show that one can predict if an article will be publicly shared to another platform by individuals with precision of approximately 80%. This research has implications for news organizations desiring to increase and to prioritize types of user engagement.
UR - https://www.scopus.com/pages/publications/85070358526
M3 - Conference contribution
AN - SCOPUS:85070358526
SN - 9781577358060
T3 - Proceedings of the 13th International Conference on Web and Social Media, ICWSM 2019
SP - 47
EP - 57
BT - Proceedings of the 13th International AAAI Conference on Web and Social Media, ICWSM 2019
PB - Association for the Advancement of Artificial Intelligence
Y2 - 11 June 2019 through 14 June 2019
ER -