1. San Francisco Bay Area News Ecology Hayreddin Ceker

2. Outline Project Description Methodology Macro dimension Meso dimension Micro dimension Problems Conclusion

3. Project Description communication and the expression - TV, Radio - Print publications - Central source - Informative Traditional Media Democratic and decentralized The audience can contribute Community to participation and consumption Networked Media

4. Project Description Use Complex Networks analysis to demonstrate transition from Traditional Media to Networked Media Take snapshots of current ecosystem, San Francisco Bay Area Macro dimension: News-to-news network Meso dimension: Author-to-link network Micro dimension: Commenter network

5. Methodology Macro dimension: News-to-news network http://www.local123gallery.com/ http://www.susanfelterart.com/Welcome.html http://mimiplumb.com/ http://www.berkeleyside.com

6. Macro dimension www.berkeleyside.com www.socketsite.com http://laurendo.wordpress.com/ Different subdomain www.cnn.com/page2.html www.cnn.com/page1.html Same website

7. News-to-news Graph www.cnn.com 7 www.berkeleyside.com 7 http://laurendo.wordpress.com/ 3 www.socketsite.com

8. News-to-news NW Inbound link # Outbound link # Central nodes Corner nodes

9. Degree of leakage Whether the Bay Area is still pointing mainly the websites from the same area Or the Internet has changed the way the local websites behave Categorizing Links Categorize news sites if they match the seed site list News sites out of the box Another implication of degree of leakage is to find out new source-like websites that the news benefit from.

10. Methodology Meso dimension: Author-to-news network

11. Author-to-link NW Bipartite graph Tracey Taylor Lauren Callahan Richard Parks http://mimiplumb.com http://www.fellinirestaurant.net Degree of author Degree of websites - which author linked websites more often - which web sites are referred more frequently

12. Methodology Micro dimension – Commenter Network Are Blackberries best bet for Berkeley in emergencies? Berkeleyans move their money, and small banks benefit

13. Commenter NW Bipartite Graph Links between commenters and news Bruce Nora The Sharkey Blackberry… Banks… 1-node graph How the commenters interact with each other Bruce The Sharkey Nora 2 1

14. Problems in crawling No standard structure of websites Author Comment Commenters Old websites have huge amount of pages Hard to crawl Links to non-existing websites JavaScript Advertisements Media objects

15. 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

16. El Fin Thank you for listening! ¿QUESTIONS?