The focus of my project is on how we can use references to citizen journalism producers in foreign countries to find a community that is discussing about the same things. You can find the slides from last week here. Global Voices is a community of international participants in creating news through blog posts about what is happening in their countries or local communities. Most articles cite sources local to the countries that they are focusing on. We intend to make use of references, such as twitter accounts to identify a broader community that is likely to talk about the same things.

This project is in close relation to the Data Forager. We currently can use a list of twitter accounts to generate the community of people who are followed by them. To exemplify this, we used the Data Forager examples. We build the community that is followed by a set of twitter accounts and use Gephi to visualize the network generated by a basic list of 10 twitter accounts cited in an article. We are able to generate the graph structure from any input that lists twitter accounts.

Possible next steps:

• output the twitter stream of the community generated from an input list of twitter accounts
• identify some metrics to decide what is a better set of twitter accounts that identify the community representative for the discussion in a countries featured in Global Voices. Try to identify from the network structure if the cited accounts are part of different communities.
• build a network of all twitter accounts that are cited in Global Voices in each country. Use this to see if the accounts that are cited in different articles belong to different communities.
• analyze the structure of the network up to 2 nodes distance from the original list of twitter accounts