Second programming assignment for Social Computing (CSC 555) at NC State, Fall '16. I will try to prove/disprove one hypothesis on a social network graph using Neo4j and calculate certain social network metrics.
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Updated
Oct 4, 2016 - JavaScript
Second programming assignment for Social Computing (CSC 555) at NC State, Fall '16. I will try to prove/disprove one hypothesis on a social network graph using Neo4j and calculate certain social network metrics.
By using Gephi’s modularity class feature, top 3 communities in subscription model were identified. No gender-related communities were detected. Based on centralities and hub measures there was found a list of users with efficient way transmitting information in the network, these top 100 users are recommended to target.
Patent Analysis for F42 Ammunition and Blasting" Technologies
This project predicts community evolution in social networks
[GIW-MII-UGR-2016-17] Caso Práctico de Análisis y Evaluación de Redes en Twitter: "Paraguay 31 Marzo 2017: Incendio en el Congreso"
Creating & analyzing a social network through graphs, using classical algorithms for analyzing relationships, communication patterns, influence, and communities within the social network.
Algorithms for Degree-anonymization of Networks.
A simple unweighted undirected social network graph. It allows users to add and remove nodes and edges, view the social network of a person, and visualize the social network using Graphviz.
Mining Social Network Graphs
This project aims to unite similar Twitter communities by identifying shared interests through Unsupervised Learning Techniques on Graph and Tabular Data.
Mining Github for contributors at the Tensorflow repo and analysis of followship relations.
Projects for Social Gaming course in Technical University of Munich
Social Network Simulator developed in python.
Marvel Social Network
Visualization of the links between subreddits
An analysis on the cascading behavior between Taiwanese Instagram food bloggers, based on Asynchronous Independent Cascade Model (AsIC) and Influence Maximization Model.
The code base for AWARE, a graph representation learning method published at TMLR
A basic Diffusion of Innovation simulation with NetworkX
AI+DA - Social Network Analysis page
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