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A Model of Online Social Interactions based on Sentiment Analysis and Content Similarity

Related publications (28)

Content Moderation in Online Platforms

A critical role of online platforms like Facebook, Wikipedia, YouTube, Amazon, Doordash, and Tinder is to moderate content. Interventions like banning users or deleting comments are carried out thousands of times daily and can potentially improve our onlin ...

EPFL2024

Caching and Neutrality

Aikaterini Argyraki, Pavlos Nikolopoulos, Muhammad Abdullah

We are used to defining network neutrality as absence of traffic differentiation, like policing or shaping. These mechanisms, however, are often not what determines end-users’ quality of experience (QoE). Most content today is accessed through edge caches, ...

ACM Association for Computing Machinery2023

Referencing in YouTube Knowledge Communication Videos

Daniel Gatica-Perez, Haeeun Kim

In recent years, there has been widespread concern about misinformation and hateful content on social media that are damaging societies. Being one of the most influential social media that practically serves as a newsearch engine, YouTube has accepted crit ...

Assoc Computing Machinery2023

The kinectome: A comprehensive kinematic map of human motion in health and disease

Enrico Amico, Emahnuel Troisi Lopez, Antonella Romano

Human voluntary movement stems from the coordinated activations in space and time of many musculoskeletal segments. However, the current methodological approaches to study human movement are still limited to the evaluation of the synergies among a few body ...

WILEY2022

Investigating cognitive ability using action-based models of structural brain networks

Enrico Amico

Recent developments in network neuroscience have highlighted the importance of developing techniques for analysing and modelling brain networks. A particularly powerful approach for studying complex neural systems is to formulate generative models that use ...

OXFORD UNIV PRESS2022

Opinion Formation over Adaptive Networks

Virginia Bordignon

An adaptive network consists of multiple communicating agents, equipped with sensing and learning abilities that allow them to extract meaningful information from measurements. The objective of the network is to solve a global inference problem in a decent ...

EPFL2022

Turning crowds into communities: The collectives of online citizen science

Jérôme Baudry

Over the past two decades, a number of digital platforms have been developed with the aim of engaging citizens in scientific research projects. The success of these platforms depends in no small part on their ability to attract and retain participants, tur ...

2022

True scale-free networks hidden by finite size effects

Andrea Rinaldo, Samir Suweis, Amos Maritan

We analyze about 200 naturally occurring networks with distinct dynamical origins to formally test whether the commonly assumed hypothesis of an underlying scale-free structure is generally viable. This has recently been questioned on the basis of statisti ...

National Academy of Sciences2021

NICEpath: Finding metabolic pathways in large networks through atom-conserving substrate-product pairs

Vassily Hatzimanikatis, Jasmin Maria Hafner

Motivation: Finding biosynthetic pathways is essential for metabolic engineering of organisms to produce chemicals, biodegradation prediction of pollutants and drugs, and for the elucidation of bioproduction pathways of secondary metabolites. A key step in ...

OXFORD UNIV PRESS2021

Systematic model reduction captures the dynamics of extrinsic noise in biochemical subnetworks

Barbara Bravi

We consider the general problem of describing the dynamics of subnetworks of larger biochemical reaction networks, e.g., protein interaction networks involving complex formation and dissociation reactions. We propose the use of model reduction strategies t ...

AMER INST PHYSICS2020

Local Tomography of Large Networks Under the Low-Observability Regime

Ali H. Sayed, Augusto José Rabelo Almeida Santos

This article studies the problem of reconstructing the topology of a network of interacting agents via observations of the state-evolution of the agents. We focus on the large-scale network setting with the additional constraint of partial observations, wh ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Morphology and morphodynamics of braided rivers: an experimental investigation

Daniel Vito Papa

Braided rivers form some of the most fascinating fluvial patterns found on Earth. They are identifiable by their unique morphology of complex networks of intertwined channels that spread across wide floodplains. Detailed knowledge of their dynamics is need ...

EPFL2020

Tracing Teacher Collaborative Learning and Innovation Adoption: a Case Study in an Inquiry Learning Platform

Denis Gillet, Luis Pablo Prieto Santos, Maria Jesus Rodriguez Triana

Social processes play an important role in teachers' ongoing professional learning: through interactions with peers and experts to solve problems or co-create materials, teachers internalize knowledge developed in their communities. However, these social p ...

International Society of Learning Sciences2019

Statistical Physics Methods for Community Detection

Chun Lam Chan

This thesis is devoted to information-theoretic aspects of community detection. The importance of community detection is due to the massive amount of scientific data today that describes relationships between items from a network, e.g., a social network. I ...

EPFL2019

Percolation and Internet Science

Emanuele Massaro

Percolation, in its most general interpretation, refers to the “flow” of something (a physical agent, data or information) in a network, possibly accompanied by some nonlinear dynamical processes on the network nodes (sometimes denoted reaction–diffusion s ...

2019

Discovering Interaction Patterns in Online Learning Environments : A Learning Analytics Research

Mina Shirvani Boroujeni

The increasing amount of data collected in online learning environments provides unique opportunities to better understand the learning processes in different educational settings. Learning analytics research aims at understanding and optimizing learning a ...

EPFL2018

The morning commute in urban areas with heterogeneous trip lengths

Nikolaos Geroliminis, Raphael Ali Francis Lamotte

This paper investigates the equilibrium properties of the morning commute problem at the network level with heterogeneous trip lengths. Congestion is modeled with a Macroscopic Fundamental Diagram relating the space-mean speed of a network to the vehicular ...

2018

Slow dynamics in structured neural network models

Samuel Pavio Muscinelli

Humans and some other animals are able to perform tasks that require coordination of movements across multiple temporal scales, ranging from hundreds of milliseconds to several seconds. The fast timescale at which neurons naturally operate, on the order of ...

EPFL2018

From recommender systems to spatio-temporal dynamics with network science

Kirell Maël Benzi

Networks are data structures that are fundamental for capturing and analyzing complex interactions between objects. While they have been used for decades to solve problems in virtually all scientific fields, their usage for data analysis in real-world prac ...

EPFL2017

Alignment and Assembly : Inferring Networks from Noisy Observations

Lyudmila Yartseva

Over recent years, many large network datasets become available, giving rise to novel and valuable applications of data mining and machine learning techniques. These datasets include social networks, the structure of the Internet, and protein-interaction n ...

EPFL2017