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Endorsement deduction and ranking in social networks

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posted on 2025-05-10, 11:51 authored by Herbert Pérez-Rosés, Francesc Sebé, Josep Maria Ribó
Some social networks, such as LinkedIn and ResearchGate, allow user endorsements for specific skills. In this way, for each skill we get a directed graph where the nodes correspond to users’ profiles and the arcs represent endorsement relations. From the number and quality of the endorsements received, an authority score can be assigned to each profile. In this paper we propose an authority score computation method that takes into account the relations existing among different skills. Our method is based on enriching the information contained in the digraph of endorsements corresponding to a specific skill, and then applying a ranking method admitting weighted digraphs, such as PageRank. We describe the method, and test it on a synthetic network of 1493 nodes, fitted with endorsements.

History

Journal title

Computer Communications

Volume

73

Issue

January 2016, Part B

Pagination

200-210

Publisher

Elsevier

Language

  • en, English

College/Research Centre

Faculty of Engineering and Built Environment

School

School of Electrical Engineering and Computer Science

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