Modeling Communication Asymmetry and Algorithmic Personalization in Online Social Networks

Autor: Franco Galante, Luca Vassio, Michele Garetto, Emilio Leonardi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::adeb2dc767b55cb12b72d48c48fd2998
https://doi.org/10.2139/ssrn.4357183

Reconciling the Quality vs Popularity Dichotomy in Online Cultural Markets

Autor: Rossano Gaeta, Michele Garetto, Giancarlo Ruffo, Alessandro Flammini

We propose a simple model of an idealized online cultural market in which $N$ items, endowed with a hidden quality metric, are recommended to users by a ranking algorithm possibly biased by the current items' popularity. Our goal is to better underst

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::28cdb73f5261357eb809bcf37c251ae4
http://arxiv.org/abs/2204.13536

Mining and modelling temporal dynamics of followers' engagement on online social networks

Autor: Luca Vassio, Michele Garetto, Emilio Leonardi, Carla Fabiana Chiasserini

Publikováno v: Social network analysis and mining. 12(1)

A relevant fraction of human interactions occurs on online social networks. In this context, the freshness of content plays an important role, with content popularity rapidly vanishing over time. We therefore investigate how influencers’ generated

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1d012a38414f71cd0bcfca19d3191efd
https://pubmed.ncbi.nlm.nih.gov/35937770

Content placement in networks of similarity caches

Autor: Giovanni Neglia, Emilio Leonardi, Michele Garetto

Publikováno v: Computer Networks
Computer Networks, Elsevier, 2021, 201, pp.108570. ⟨10.1016/j.comnet.2021.108570⟩
Computer Networks, 2021, 201, pp.108570. ⟨10.1016/j.comnet.2021.108570⟩

Similarity caching systems have recently attracted the attention of the scientific community, as they can be profitably used in many application contexts, like multimedia retrieval, advertising, object recognition, recommender systems and online cont

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0cb4b2db0d59d3cb773cd49196c2f8ff
https://hal.inria.fr/hal-03499870/document

GRADES: Gradient Descent for Similarity Caching

Autor: Anirudh Sabnis, Emilio Leonardi, Ramesh Sitaraman, Tareq SI SALEM, Michele Garetto, Giovanni Neglia

Publikováno v: IEEE International Conference on Computer Communications (INFOCOM 2021)
IEEE International Conference on Computer Communications (INFOCOM 2021), May 2021, Virtual Conference, United States
IEEE INFOCOM 2021-IEEE Conference on Computer Communication
INFOCOM
IEEE/ACM Transactions on Networking
IEEE/ACM Transactions on Networking, 2022, pp.1-12. ⟨10.1109/TNET.2022.3187044⟩
INFOCOM 2021-IEEE International Conference on Computer Communications
INFOCOM 2021-IEEE International Conference on Computer Communications, May 2021, Virtual Conference, United States. ⟨10.1109/INFOCOM42981.2021.9488757⟩

International audience; A similarity cache can reply to a query for an object with similar objects stored locally. In some applications of similarity caches, queries and objects are naturally represented as points in a continuous space. This is for e

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::85b8a306903ea7104952eb51445646f1
https://hal.archives-ouvertes.fr/hal-03484133/document