There are 9 repositories under influence-maximization topic.
XFlow - A Python Library for Graph Flow
Social network analysis code examples for PyCon 2019 talk
Top-K Influential Nodes in Social Networks: A Game Perspective (SIGIR'17)
Source code for blog post at https://hautahi.com/im_greedycelf
Implementation of Influence Maximisation on a graph dataset.
This telegram bot manages an instagram engagement group maintaining a current list of active users
code in article Identifying influential nodes in social networks: A voting approach, link: https://doi.org/10.1016/j.chaos.2021.111309,
Influence Maximization in Near-Linear Time: A Martingale Approach Scala implementation
Python GPU Code for IM Algorithms
Evaluation and improvement of cascade diffusion robustness against node attacks.
Our group capstone project site for UC Berkeley's MIDS W210/Capstone.
We use gpu to accelerate the influence-maximization diffusion, which can make it faster more than 10 times than before
An analysis on the cascading behavior between Taiwanese Instagram food bloggers, based on Asynchronous Independent Cascade Model (AsIC) and Influence Maximization Model.
Influential nodes identification & CELF implementation
in this repo. greedy hill climbing and lazy hill climbing is implemented from scratch with only numpy and scipy library. this project is tested on the facebook101-Princeton dataset.
This repository contains a complimentary code for the article "Content-based Network Influence Probabilities: Extraction and Application". The repository contains trained dataset, solvers for the node immunization problem, code for crawling and downloading VK social network, and script for extracting influence probabilities based on the downloaded data.
Unofficial Python Implementation of "Maximizing the Spread of Influence through a Social Network"
Social Network Analysis
In this repo. , "Cost Effective Lazy Forward Selection" Algorithm is implemented from scratch in python with only numpy library.
Implementation of Complex Networks Algorithms
Course project for CPSC534: Topics in Data Science & Management: Social Networks at UBC 2017
Fast and accurate influence maximization on large networks with pruned monte-carlo simulations
Code for simulations concerning single player Ising Influence Maximisation as well as competitive optimisation structured as a simultaneous or a sequential game.
Solving the influence maximization problem with independent cascade diffusion model.
An efficient and effective GRASP algorithm for the Budget Influence Maximization Problem
Influence Maximization for Partially Observable Networks with Varying Degree Assortativities
Influence Maximization on a graph (social network)