Publications associées à Call me Guru: user categories and large-scale behavior in YouTube

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Caching and Neutrality

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 ...

New York2023

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 ...

NATL ACAD SCIENCES2021

Clusters of science and health related Twitter users become more isolated during the COVID-19 pandemic

Marcel Salathé, Martin Müller

COVID-19 represents the most severe global crisis to date whose public conversation can be studied in real time. To do so, we use a data set of over 350 million tweets and retweets posted by over 26 million English speaking Twitter users from January 13 to ...

NATURE PORTFOLIO2021

Design choices for Central Bank Digital Currency

Bryan Alexander Ford, Fan Zhang, Srdan Capkun, Ari Juels

Central banks around the world are exploring and in some cases even piloting central bank digital currencies (CBDCs). CBDCs promise to realize a broad range of new capabilities, including direct government disbursements to citizens, frictionless consumer p ...

Brookings Institution2020

Spikyball Sampling: Exploring Large Networks via an Inhomogeneous Filtered Diffusion

Nicolas Aspert, Volodymyr Miz, Benjamin Ricaud

Studying real-world networks such as social networks or web networks is a challenge. These networks often combine a complex, highly connected structure together with a large size. We propose a new approach for large scale networks that is able to automatic ...

2020

Investigating users' eye movement behavior in critiquing-based recommender systems

Pearl Pu Faltings, Li Chen, Feng Wang

Recommender systems have increasingly become popular in various web environments (such as e-commerce and social media) for automatically generating items that match to individual users' personal interests. Among different types of recommender systems that ...

Ios Press2017

EHR: a Sensing Technology Readiness Model for Lifestyle Changes

Pearl Pu Faltings, Yu Chen, Danni Le, Zerrin Yumak

Interest in developing user-centered sensing technologies for personalized behavior change has gained significant momentum. However, very little research work has been done to understand issues relative to user readiness and adoption of the sensing technol ...

Springer2017

Call me Guru: user categories and large-scale behavior in YouTube

Graph Chatbot

Chattez avec Graph Search

Caching and Neutrality

Referencing in YouTube Knowledge Communication Videos

Dynamic Personalized Ranking

True scale-free networks hidden by finite size effects

Clusters of science and health related Twitter users become more isolated during the COVID-19 pandemic

Design choices for Central Bank Digital Currency

Spikyball Sampling: Exploring Large Networks via an Inhomogeneous Filtered Diffusion

Investigating users' eye movement behavior in critiquing-based recommender systems

From recommender systems to spatio-temporal dynamics with network science

EHR: a Sensing Technology Readiness Model for Lifestyle Changes

Caching and Neutrality

Referencing in YouTube Knowledge Communication Videos

Dynamic Personalized Ranking

Clusters of science and health related Twitter users become more isolated during the COVID-19 pandemic

Investigating users' eye movement behavior in critiquing-based recommender systems

True scale-free networks hidden by finite size effects

Design choices for Central Bank Digital Currency

Spikyball Sampling: Exploring Large Networks via an Inhomogeneous Filtered Diffusion

From recommender systems to spatio-temporal dynamics with network science

EHR: a Sensing Technology Readiness Model for Lifestyle Changes