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Idea: Given a list of "seed users", get all users within N links #1
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I think a breadth-first search from each user, while maintaining the set of members in the overall community, should work. |
How do you stop it at a certain breadth? (e.g. A-B-C-D or three degrees?) Also, how would de-duplication and distance updating works (e.g. W is 1 away from X, 2 away from Y and 3 away from Z, and X to Z are all part of the seed list)? Lastly, how do you export that into JSON or some other data format (dictionary of user-id as key, to list of user-id as value)? regarding visualization https://github.com/jvallyea/Mapping-Social-Media and https://github.com/timbennett/twitter-chat-networks and https://github.com/mgmacias95/TwitterFriends and https://github.com/SadeghHayeri/Twitter-Friend-Connections |
Breath-first search can be used to compute shortest distance from a node in a graph. So, as you traverse the graph you can compute the distance from the starting node and avoid traversing the outgoing edges once you have reached a node with a distance of X units from the source node.
If I understand you correctly about de-duping the members, I think a "set" data-structure will take care of that. I assumed that the final output of the algorithm would be this set which contains the members of the community.
Not sure what exactly you mean here. |
I am using this to scrape a Twitter follow network for Community Detection and Role Similarity/Discovery/Detection. So for every user I need its follow links saved as some kind of file for ease of storage and use in NetworkX or iGraph. |
If I were to have a list of people from a single community, would it be possible to find N-distance connections of those users and save them down into a file (follow list of everyone involved)? That would be useful for community detection.
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