A browser extension that utilizes sentiment analysis to find and highlight constructive comments on various social media platforms that oppose the users worldview in order to encourage them to break out of the echo chambers the internet has allowed us to construct.

Mapping Echo Chambers In Large Networks

Computational Social Science Project: "Algorithmic Bias in Echo Chamber Formation".

Repository to reproduce "Cascade-based Echo Chamber Detection" accepted at CIKM2022

People Recommender Systems in Opinion Dynamics models

Companion repository for the paper "I Want to Break Free! Recommending Friends from Outside the Echo Chamber" accepted at RecSys 2021

Flask web application that facilitates intellectual conversation between users with different backgrounds with a KMeans cluster matching algorithm to help mitigate any bias seen in social media echo chambers.

A parallel algorithm to compute the Random Walk Controversy score of a network.

Network analysis experiment on echo-chamber relative to COVID-19 tweets.

Discretionary Exposure to Political Information

Master Thesis (e4 RCP) - Echo Chamber Detection in Social Media

Code developed for : Darenne, L. (2024). Propositions pour l'identification, la modélisation et la quantification des chambres d’écho : Expérimentation sur un corpus de commentaires YouTube. Master Thesis, Institut National des Langues et Civilisations Orientales.

This project investigates how social media usage relates to political polarization in Germany, using panel data from the German Longitudinal Election Study (GLES). The analysis, conducted in R, includes data wrangling, visualization, and panel regression models to assess the impact of social media activity on shifts in political attitudes over time

Sample codes used in the study of echo-chambers in Mastodon 🌐

Investigating the possibilities of echo chambers in Retrieval Augmented Generation (RAG)

Network analysis experiment on echo-chamber relative to COVID-19 tweets.