{"id":30240231,"url":"https://github.com/miladfa7/social-network-analysis-in-python","last_synced_at":"2025-08-28T23:49:08.178Z","repository":{"id":157981429,"uuid":"196202379","full_name":"miladfa7/Social-Network-Analysis-in-Python","owner":"miladfa7","description":"Social Network Facebook Analysis (Python, Networkx)","archived":false,"fork":false,"pushed_at":"2024-09-25T08:31:37.000Z","size":4428,"stargazers_count":36,"open_issues_count":0,"forks_count":8,"subscribers_count":0,"default_branch":"master","last_synced_at":"2025-08-15T04:22:57.991Z","etag":null,"topics":["analysis","big-data","facebook","graph","networkx","networkx-graph","python","social-network"],"latest_commit_sha":null,"homepage":"https://snap.stanford.edu/data/ego-Facebook.html","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/miladfa7.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2019-07-10T12:35:55.000Z","updated_at":"2025-07-09T20:33:59.000Z","dependencies_parsed_at":null,"dependency_job_id":"2a7f37a9-0ad5-47ce-b9a2-56a663c09977","html_url":"https://github.com/miladfa7/Social-Network-Analysis-in-Python","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/miladfa7/Social-Network-Analysis-in-Python","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/miladfa7%2FSocial-Network-Analysis-in-Python","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/miladfa7%2FSocial-Network-Analysis-in-Python/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/miladfa7%2FSocial-Network-Analysis-in-Python/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/miladfa7%2FSocial-Network-Analysis-in-Python/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/miladfa7","download_url":"https://codeload.github.com/miladfa7/Social-Network-Analysis-in-Python/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/miladfa7%2FSocial-Network-Analysis-in-Python/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":272582506,"owners_count":24959419,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-08-28T02:00:10.768Z","response_time":74,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["analysis","big-data","facebook","graph","networkx","networkx-graph","python","social-network"],"created_at":"2025-08-15T04:13:44.632Z","updated_at":"2025-08-28T23:49:08.163Z","avatar_url":"https://github.com/miladfa7.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Social-Network-Analysis-in-Python (facebook)\n\nSocial Network Analysis in Python\nNetworks today are part of our everyday life. Let's learn how to visualize and understand a social network in Python using Networks \u003cbr\u003e\n\n## Dataset information\nThe dataset you are referring to is the Facebook Social Circles Dataset, which is part of a collection of social network datasets. This dataset was collected by analyzing ego networks on Facebook, where an ego network is defined as a focal node (the ego) and all the nodes (friends) connected to it, along with the links (friendships) between these friends. The key aspects of this dataset include:\n\n     - Node Features: Information about individual users, although anonymized.\n     - Circles: Groups of friends, similar to how Facebook allows users to organize friends into different lists.\n     - Ego Networks: Networks centered around a specific user (the ego), including that user's friends and the connections between them.\n\n**Key Statistics:**\n\n    Nodes: 4039 (representing users)\n    Edges: 88234 (representing friendships)\n    Clustering Coefficient: 0.6055 (indicating a relatively high level of clustering)\n    Triangles: 1.61 million (showing the number of friend groups that are fully connected)\n    Diameter: 8 (the longest shortest path between any two nodes)\n    Effective Diameter: 4.7 (90th percentile of the shortest path lengths between nodes)\n    \n\nhttps://snap.stanford.edu/data/ego-Facebook.html \u003cbr\u003e\n![betweenness_centrality](https://user-images.githubusercontent.com/25765644/141525940-b0f12e32-cff6-4d30-bd0f-45fba8d5091d.png)\n\n## Some Social Network Analysis Methods and Examples\n\n**1- Betweenness Centrality**\u003cbr\u003e\nBetweenness centrality is defined as a measure of how often a node lies on the shortest path between all pairs of nodes in a network\n\n```python\npython scripts/betweenness_centrality.py\n```\n**2- Degree Centrality** \u003cbr\u003e\n```python\npython scripts/graph_degree_centrality.py\n```\n\n3- Closeness Centrality \u003cbr\u003e\n4- Eeigenvector Centrality \u003cbr\u003e\n5- Find shortest path \u003cbr\u003e\n6- Find all neighbors the nodes \u003cbr\u003e\n7- Degree Grapg \u003cbr\u003e\n8- K-clique \u003cbr\u003e\n9- K-core \u003cbr\u003e\n10- pagerank \u003cbr\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmiladfa7%2Fsocial-network-analysis-in-python","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmiladfa7%2Fsocial-network-analysis-in-python","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmiladfa7%2Fsocial-network-analysis-in-python/lists"}