This dataset contains information about 90,269 users and 3,646,662 friendship links between those users. These users belong to the New Orleans Facebook regional network. The...

Ndlib is a Network diffusion library that contains a set of models to simulate disease spreading and opinion dynamics.

Exponential Random Graph Models (ERGMs) have gained increasing popularity over the years. Rooted into statistical physics, the ERGMs framework has been successfully employed...

python library to unify soccer data and algorithms

Instagram is currently the social media platform most associated with online images (and their analysis), but images from other platforms also can be collected and grouped,...

Community Discovery library

Path-aware multi-scale homophily measure for node-attributed complex networks

We provide a method that finds echo chambers in online social networks. The method considers controversial contents and finds users of the network who discuss these contents...

The micro-project has developed a python module for the generation of networks with fractal topologies, in particular Sierpinski graphs for the task involved in T8.4 Complex...

CAsT 2019 data is split into two files one for training and the other one for testing. - Training set: CAsT 2019 conversations from training set and from test set without...

The data module of scikit-mobility provides users with an easy way to: 1) Download ready-to-use mobility data (e.g., trajectories, flows, spatial tessellations, and auxiliary...

Implements a method of transfer learning for feature extraction including both convolutional and fully connected layers of a neural network.

A library to ease the creation and management of social media listening campaigns using the Twitter API v2.

A collection of scripts for the estimation and analysis of a "retweet cascade", i.e., the tree structure describing how the original tweet was spread by retweeters.

The MAMe dataset ia an image classification dataset with remarkable high resolution and variable shape properties. The goal of MAMe is to provide a tool for studying the...

This gaming-related dataset consists of 8932 users (labeled as gamers) engaging in game-related conversations. We have collected (June 2018) their timeline (the most recent 3200...

The aim of LeQua 2022 (the 1st edition of the CLEF “Learning to Quantify” lab) is to allow the comparative evaluation of methods for “learning to quantify” in textual...

This data set comprises a labeled training set, validation samples, and testing samples for ordinal quantification. It appears in our research paper "Ordinal Quantification...

This labeled data set is targeted at ordinal quantification. It appears in our research paper "Ordinal Quantification Through Regularization", which we have published at...