static void Main(string[] args)
{
Console.WriteLine("[START]\tTraining started");
NaiveBayesClassifier sentimentClassifier = new NaiveBayesClassifier();
sentimentClassifier.Train(new TestDataParser("Resources/SentimentTrainingData.txt"));
Console.WriteLine("[END]\tTraining");
Console.WriteLine();
Console.WriteLine("[START]\tFriendlist parsing");
FriendListParser parser = new FriendListParser("Resources/friendships.reviews.txt");
parser.Parse();
File.WriteAllText("graph.csv", parser.Community.ToGraph());
Console.WriteLine("[END]\t\tFriendlist parsing");
Console.WriteLine();
Console.WriteLine("[START]\t\tIdentifying communities");
CommunityIdentifier communityIdentifier = new CommunityIdentifier(parser.Community);
DateTime start = DateTime.Now;
List<Community> subCommunities = communityIdentifier.Identify();
Console.WriteLine("[END]\t\tIdentifying communities");
Console.WriteLine();
Console.WriteLine("[START]\t\tAnalysing communities");
CommunityAnalyzer communityAnalyzer = new CommunityAnalyzer(sentimentClassifier, subCommunities);
string filename = "result.csv";
communityAnalyzer.Analyze(filename);
Console.WriteLine("[END]\t\tAnalysing communities: Results written to {0}", filename);
Console.WriteLine("Identied communities: " + subCommunities.Count);
Console.WriteLine("\nSub communities:");
foreach (var community in subCommunities)
{
Console.WriteLine(community.Size);
community.Dispose();
}
communityAnalyzer.Dispose();
communityIdentifier.Dispose();
sentimentClassifier.Dispose();
Console.WriteLine(DateTime.Now.Subtract(start).ToString("g"));
Console.WriteLine("Finished everything. Press to exit");
Console.ReadLine();
}
public List<Community> Identify(double lastDiff = double.MinValue)
{
List<Community> communities = new List<Community>();
if (_rootCommunity.Users.Count < 2)
return communities;
Console.WriteLine("Root community size: {0}", _rootCommunity.Users.Count);
_eigenvector = CalculateEigenvector();
//Console.WriteLine("Eigenvector:\n\t" + string.Join("\n\t", _eigenvector));
double largestDiff = lastDiff;
int nodeIndexBeforeDiff = -1;
for (int i = 1; i < _eigenvector.Count; i++)
{
double diff = Math.Abs(_eigenvector[i].Value - _eigenvector[i - 1].Value);
if (diff > largestDiff)
{
nodeIndexBeforeDiff = i;
largestDiff = diff;
}
}
Console.WriteLine("Largest diff: " + largestDiff);
if (nodeIndexBeforeDiff > -1) // We did discover subcommunities
{
Community community1 = new Community();
for (int i = 0; i < nodeIndexBeforeDiff; i++)
{
User user = _rootCommunity.Users[_eigenvector[i].Key];
community1.AddUser(user);
}
Community community2 = new Community();
for (int i = nodeIndexBeforeDiff; i < _eigenvector.Count; i++)
{
User user = _rootCommunity.Users[_eigenvector[i].Key];
community2.AddUser(user);
}
Console.WriteLine("Community1: " + community1.Size);
Console.WriteLine("Community2: " + community2.Size);
Console.WriteLine();
if (community1.Size > 1 && community2.Size > 1)
{
lastDiff = largestDiff*0.6;
CommunityIdentifier identifier1 = new CommunityIdentifier(community1);
List<Community> communities1 = identifier1.Identify(lastDiff);
if (communities1.Count > 0)
communities.AddRange(communities1);
else
communities.Add(community1);
CommunityIdentifier identifier2 = new CommunityIdentifier(community2);
List<Community> communities2 = identifier2.Identify(lastDiff);
if (communities2.Count > 0)
communities.AddRange(communities2);
else
communities.Add(community2);
}
}
Console.WriteLine("Communities: {0}\n", communities.Count);
return communities;
}