title: group detection in large data sets python
body: <p>I am a newbie in python and have been trying my hands on different problems which introduce me to different modules and functionalities (I find it as a good way of learning).</p>
  
  <p>I have googled around a lot but haven't found anything close to a solution to the problem. </p>
  
  <p>I have a large data set of facebook posts from various groups on facebooks that use it as a medium to mass send the knowledge. </p>
  
  <p>I want to make groups out of these posts which are content-wise same. </p>
  
  <p>For example, one of the posts is "xyz.com is selling free domains. Go register at xyz.com"
  and another is "Everyone needs to register again at xyz.com. Due to server failure, all data has been lost."</p>
  
  <p>These are similar as they both ask to go the group's website and register.</p>
  
  <p>P.S: Just a clarification, if any one of the links would have been abc.com, they wouldn't have been similar. </p>
  
  <p>Priority is to the source and then to the action (action being registering here). </p>
  
  <p>Is there a simple way to do it in python? (a module maybe?)</p>
  
  <p>I know it requires some sort of clustering algorithm ( correct me if I am wrong), my question is can python make this job easier for me somehow? some module or anything?</p>
  
  <p>Any help is much appreciated!</p>