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Social_network_analysis--Link_prediction

Problem statement:

Given a directed social graph, we have to predict missing links to recommend friends/connnections/followers (Link Prediction in graph).

Data Overview

Dataset from facebook's recruting challenge on kaggle: https://www.kaggle.com/c/FacebookRecruiting
Data contains two columns: source and destination edge pairs in the directed graph.

  • Data columns (total 2 columns):
  • source_node int64
  • destination_node int64

Business objectives and constraints:

  • No low-latency requirements.
  • Predciting the probability of a link is useful so as to recommend the highest probability links to a user.
  • We got to suggest connnections which are most likley to be correct and we should try and not miss out any connnections.

Performance metric for supervised learning:

  1. Both precision and recall are important, hence F1 score is good choice
  2. Confusion matrix
  3. Accuracy can also be checked

How to run the file

First download the data from Data Source then run the file: FB_FriendRecommendation.ipynb.