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sachin09121992/Community-Detection-Using-Attributed-Graphs-and-Sentiment-Analysis
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1) There are 4 python files namely pre_process.py, make_edge_list.py, community_detection.py and sentiment_analysis.py 2) Following are the python modules that are needed: pickle, pandas, numpy, csv, scipy, igraph, gensim, collections, sklearn 3) If the package is not installed, install using pip install <package_name> 4) To reduce the running time, we cached intermediate results into pickle files. Ensure these pickle files are also present in the directory of the code 5) There are mainly three output files: attributes.csv, edge_list.txt, communities.txt 6) Since the data files are larger, we could not upload it. The link to the data set is : https://www.yelp.com/dataset_challenge/dataset 7) Make sure to include the data folder named 'data' in the same directory as the code files.
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This project detects the communities in a social network using attributed graphs, SAC-1 algorithm and sentimental analysis.
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