social-networking

I need to design / architect / develop a web based social network type application. Basic functionality: - users create accounts on the system - users agree to "friend" each other - users create content within system - users specifies which friends may view/edit content that they created Surely this core functionality has been created many times before? Are there any best practice patterns out there for how to implement this sort of thing? I'm most interested in how the database for this would look. What would this look like from a SQL perspective (any database)? What would this look like from

I am not sure whether this is the right platform to ask this question. But my problem statement is : I have a book shop & x no of clients (x is huge). A client can tell me whether a book is a good or bad (not recommended). I have a internal logic to club books together , so if a client says a book is bad, he is saying that similar books are bad too and don't show him that. I oblige and hide those books. Clients can also interact among themselves, and have a mutual confidence level between them. A case arises when client A says Book X1 is bad. Hence i blacklist X1,X2,X3,X4 etc. But his friend

Should I use: Community Engine Insoshi LovdByLess RailsSpace Roll-my-own I am looking to quickly get a social network up with support for mobile browsing. While I'm familiar with Ruby & Rails, I am not an expert (have built some basic Rails apps, have written a bunch of Ruby programs for enterprise integration). Thanks, skybison insoshi is quite ok, i used it in a past project. although i can also recommend rolling your own, which is not such a big problem with all the existing gems out there. i can recommend starting with authlogic (authentication) - then paperclip (attachments). all the

I have been searching for an answer to this question but could not find any mention, so I decided to post here. I am trying to see if igraph or any packages provide a simple way to create a "community graph" where each node represents a community in the network and the ties represent ties between the communities. I can get the community detection algorithm to work fine in igraph, but I could not find a way to collapse the results to just show connections between each community. Any assistance would be appreciated. You can simply use the contract.vertices() function. This contracts groups of

LinkedIn has this cool feature in which while visiting some user's profile, LinkedIn prompts how you are connecting to that user through the network. Assuming that the visitor and the profile owner are two nodes of a graph where the nodes represent users and edge represents friendship, a simple solution could be a bfs starting from both the nodes up to certain level and see if there are any intersections. The intersections would be the network link-nodes. Although this sounds neat, the problem is that in order to determine friends of each person, a separate DB query is needed. When the network

The application I'm working on has an activity feed where each user can see their friends' activity (much like Facebook). I'm looking for a moderately scalable way to show a given users' activity stream on the fly. I say 'moderately' because I'm looking to do this with just a database (Postgresql) and maybe memcached. For instance, I want this solution to scale to 200k users each with 100 friends. Currently, there is a master activity table that stores the rendered html for the given activity (Jim added a friend, George installed an application, etc.). This master activity table keeps the

I'm interested in network analysis on large networks with millions of nodes and tens of millions of edges. I want to be able to do things like parse networks from many formats, find connected components, detect communities, and run centrality measures like PageRank. I am attracted to NetworkX because it has a nice api, good documentation, and has been under active development for years. Plus because it is in python, it should be quick to develop with. In a recent presentation (the slides are available on github here ), it was claimed that: Unlike many other tools, NX is designed to handle data