Publication Type
Conference Proceeding Article
Publication Date
5-2013
Abstract
With the advent of social media services, media outlets have started reaching audiences on social-networking sites. On Twitter, users actively follow a wide set of media sources, form interpersonal networks, and propagate interesting stories to their peers. These media subscription and interaction patterns, which had previously been hidden behind media corporations' databases, offer new opportunities to understand media supply and demand on a large scale. Through a map that connects 77 media outlets based on Twitter subscription patterns, we are able to answer a variety of questions: to what extent New York Times and the Wall Street Journal readers overlap? Are they competitors or potential collaborators? Are people who know each other more likely to subscribe to similar outlets?
Keywords
social media, media study, visualization, structural hole
Discipline
Artificial Intelligence and Robotics | Numerical Analysis and Scientific Computing
Research Areas
Data Science and Engineering
Publication
Proceedings of the 5th Annual ACM Web Science Conference
ISBN
9781450318891
Identifier
10.1145/2464464.2464492
Publisher
Association for Computing Machinery
City or Country
Paris, France
Citation
AN, Jisun; QUERCIA, Daniele; CHA, Meeyoung; GUMMADI, Krishna; and CROWCROFT, Jon.
Traditional media seen from social media. (2013). Proceedings of the 5th Annual ACM Web Science Conference.
Available at: https://ink.library.smu.edu.sg/sis_research/6550
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Included in
Artificial Intelligence and Robotics Commons, Numerical Analysis and Scientific Computing Commons