San Francisco Bay Area News Ecology

1. San Francisco Bay Area News Ecology Daniel Ramos CS790G Fall 2010

2. Outline • Introduction • Related Work • Methodology • Conclusion

3. Evolution of News • Keeping current on events has changed radically. • “Mass Media” • Radio, television, newspapers, magazines, books, etc. • “Networked Media” • Based on the Internet. • Collaborative and global in nature.

4. Role of Journalists • Traditional Reporting • Journalists worked mostly alone and locally. • National/International news from other organizations (Associated Press). • Network Media Reporting • Journalists can easily talk to others across the globe. • They can freelance for many news outlets.

5. Project Goals • Use network analysis to characterize a “news ecosystem”. • Traditional news outlets are shrinking. • Start-up news organizations are quickly forming. • Using the San Francisco Bay area. • Transitioning from “mass media” to “networked media”?

6. Tracing Ties • Between news organizations • Between reporters and anybody else • Between users and news organizations • Potentially measure the density of ties

7. Related Work • I. Himelboim, “The International Network Structure of News Media: An Analysis of Hyperlinks Usage in News Web sites” • Analyzed 6,298 foreign news stories. • 223 news web sites. • 73 countries. • Studied use of external hyperlinks.

8. Related Work (Cont.) • Found news sites rarely used external hyperlinks. • Only 6% had one or more. • If they did, it followed patterns based on: • Preferential Attachment Theorem • World System Theory • Conclusions • Journalists trained to not reveal sources. • Distrust for outside sources. • Lead users away from the news site.

9. Related Work (Cont.) • Gordon, Contractor, and Johnson, “Linking Audiences to News and Information: A Network Analysis of Chicago Websites” • Collected a list of 277 “seed sites” • Categorized the sites into: legacy, legacy-affiliated, micropublisher, organization/institution, national brand, and service. • Used a web crawler to examine links.

10. Related Work (Cont.) • Conclusion • Organizations are authorities. • Micropublishers and organizations are hubs. • Organizations are intermediaries and switchboards. • Organizations are most prestigious.

11. Methodology • Use network theory to study three main ties: • News Organization to News Organization • Journalists to the “Community” • Commenters to News Organizations

12. News Organization Ties • Compiled a list of 143 different web sites we feel encompasses our news ecosystem. • Traditional news outlets web sites • Blogs • Other non-traditional (e.g. news aggregators) • Use a web crawler to crawl the seed sites and record all external links to a database. • Each site will be its own network at first.

13. News Organization Ties • Won’t record duplicates, but will record number of references. • News Organization graphs will be generated from the database. • Nodes are websites. • Edges are directional hyperlink references. • Edge weights are number of times linked.

14. News Organization Ties • Categorizing Links • First pass will be try to categorize news sites if they match the seed site list. • Second pass will require manual human coding • Remove all links deemed not a news organization • Merge all independent networks together.

15. News Organization Ties • Metrics • Degree (both in and out) • Determine hubs and authorities. • Betweenness • Determine which sites link otherwise unconnected sites. • Centrality • Determine which sites are important to the network.

16. Journalists to the Community • Determine the linking patterns of reporters who publish on the seed sites. • Traditional writing versus using the web to its full potential. • Use a web crawler to crawl the seed sites and record all external links to a database. • Focus on only a few larger sites. • No standard for bylines of article authors. • Requires site specific crawling rules.

17. Journalists to the Community • Journalist graph will be generated from the database. • Forms a bipartite graph. • Nodes are authors and sites. • Edges are an author linking a site. • Some manual human coding required to remove non-community sites.

18. Journalists to the Community • Metrics • Degree (both for journalists and sites) • Determine which authors cite more often • Determine which sites are referenced most often.

19. Commenters to News Organizations • Determine the patterns of users who comment on stories the seed sites. • How do they interact with news organizations and each other? • Use a web crawler to crawl the seed sites and record all commenters to a database. • Focus on only a few larger sites. • No standard for user comments and accounts. • Requires site specific crawling rules.

20. Commenters to News Organizations • Commenter graph will be generated from the database. • Forms a bipartite graph. • Each site will be its own graph. • Nodes are commenters and news stories. • Edges are a user commenting on a story. • Might require some manual human coding to remove spam & bots.

21. Commenters to News Organizations • Metrics • Degree (both for users and stories) • Determine which users comment most. • Determine which stories garner most attention. • Transform to a 1-mode network leaving users. • Edge weights are how many of the same stories two users commented on. • Do users form clusters and communities?

22. Tools • WebSPHINX • Pajek • GUESS or Gephi

23. Conclusion • Is news media transitioning because of new technologies like it has in the past? • How is the Internet affecting news outlets, journalists, and readers? • Hopefully, network theory and analysis can help find these answers.

24. References • [1] I. Himelboim, "The International Network Structure of News Media: An Analysis of Hyperlinks Usage in News Web sites," Journal of Broadcasting & Electronic Media, Volume 54, Issue 3, pp. 373-390, July 2010. • [2] R. Gordon, N. Contractor, and Z. P. Johnson, "Linking Audiences to News and Information: A Network Analysis of Chicago Websites," unpublished, http://www.cct.org/sites/cct.org/files/CNM_LinkingAudiences1.pdf