social-networking

Exporting twitter data to Gephi using R

安稳与你 提交于 2019-12-03 08:51:07
I have compiled a dataset consisting of thousands of tweets using R. The dataset basically looks like this: Data <- data.frame( X = c(1,2), text = c("Hello @User1 #hashtag1, hello @User2 and @User3, #hashtag2", "Hello @User2 #hashtag3, hello @User1 and @User3, #hashtag4"), screenname = c("author1", "author2") ) Now I want to export this dataset to a Gephi supported graph format (see Supported Graph Formats - Gephi ) Whenever an "author" mentions a @user in the text, there should be a direct link from the author to the user. In the case above, the results should be like this: author1 -> @User2

Understanding and building a social network algorithm

不打扰是莪最后的温柔 提交于 2019-12-03 07:54:27
问题 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

Social Network in Rails - which framework

最后都变了- 提交于 2019-12-03 07:52:38
问题 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 回答1: 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

generating a community graph in igraph

笑着哭i 提交于 2019-12-03 07:36:51
问题 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

Estimate exponential cutoff in a power law distribution

痴心易碎 提交于 2019-12-03 06:36:20
As I have been doing some social network analysis, I have stumbled upon the problem of fitting a probability distribution on network degree. So, I have a probability distribution P(X >= x) which, from visual inspection, follows a power law with an exponential cutoff rather than a pure power law (a straight line). So, given that the equation for power law distribution with exponential cutoff is: f(x) = x**alpha * exp(beta*x) How might I estimate the parameters alpha and beta using Python? I know scipy.stats.powerlaw package exists and they have a .fit() function but that doesn't seem to do the

How to crawl Facebook based on friendship information?

折月煮酒 提交于 2019-12-03 06:28:10
问题 I'm a graduate student whose research is complex network. I am working on a project that involves analyzing connections between Facebook users. Is it possible to write a crawler for Facebook based on friendship information? I looked around but couldn't find any things useful so far. It seems Facebook isn't fond of such activity. Can I rely on the Facebook API? Update (Jan-08-2010): Thank you very much for the responses. I guess I probably need to contact Facebook directly then. Cheers Update

Efficient way to implement LinkedIn like “How you are connected to” feature?

北城余情 提交于 2019-12-03 04:38:26
问题 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

Finding Connected Components using Hadoop/MapReduce

若如初见. 提交于 2019-12-03 03:53:21
I need to find connected components for a huge dataset. (Graph being Undirected) One obvious choice is MapReduce. But i'm a newbie to MapReduce and am quiet short of time to pick it up and to code it myself. I was just wondering if there is any existing API for the same since it is a very common problem in Social Network Analysis? Or atleast if anyone is aware of any reliable(tried and tested) source using which atleast i can get started with the implementation myself? Thanks I blogged about it for myself: http://codingwiththomas.blogspot.de/2011/04/graph-exploration-with-hadoop-mapreduce.html

Best way for social sharing in Android

三世轮回 提交于 2019-12-03 02:22:33
I've been looking for a way to share information to social networks. I've found 2 possible solutions: Look for installed apps and sent an intent (like android uses in it's gallery) Use the socials network api When looking for quick ways to implements i say use the installed apps for that but if it goes customization and generalization i think the second option is the best. I've a hard time deciding if one outweighs the other or not. So my question is: What is the best approach? One of the ones i suggested or a whole different way? I have worked with the Facebook API and I know that it's a

Delivering activity feed items in a moderately scalable way

穿精又带淫゛_ 提交于 2019-12-03 02:04:54
问题 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