Predicting audience engagement across social media platforms in the news domain

• Main Authors: ALDOUS, Kholoud Khalil, AN, Jisun, JANSEN, Bernard J.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2019
• Subjects: audience engagement; news outlets; social media; Artificial Intelligence and Robotics; Numerical Analysis and Scientific Computing; Social Media
• Online Access: https://ink.library.smu.edu.sg/sis_research/6294; https://ink.library.smu.edu.sg/context/sis_research/article/7297/viewcontent/Predicting_Audience_Engagement_Across_Social_Media_Platforms_in_the_News_Domain.pdf
• Institution: Singapore Management University

We analyze cross-platform factors for posts on both single and multiple social media platforms for numerous news outlets to better predict audience engagement, precisely the number of likes and comments. We collect 676,779 social media posts from 53 news outlets during eight months on four social me...