Trust investigation in communities using feature learning

Thiago Baesso Procaci, Sean W.M. Siqueira, Bernardo Pereira Nunes

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Online Q&A communities play a key role in informal learning. This paper reports on an investigation in Q&A communities aiming at bringing a new perspective to the problem of detecting trustworthy users through feature learning methods. These users write useful posts and contribute to the community growth, thus to knowledge dissemination. We propose two feature learning methods and demonstrate that they outperform the state of the as well as are competitive with works that addressed the same problem via hand-engineering process.

Original languageEnglish
Title of host publicationProceedings - IEEE 19th International Conference on Advanced Learning Technologies, ICALT 2019
EditorsMaiga Chang, Demetrios G Sampson, Ronghuai Huang, Alex Sandro Gomes, Nian-Shing Chen, Ig Ibert Bittencourt, Kinshuk Kinshuk, Diego Dermeval, Ibsen Mateus Bittencourt
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages212-216
Number of pages5
ISBN (Electronic)9781728134857
DOIs
Publication statusPublished - Jul 2019
Externally publishedYes
Event19th IEEE International Conference on Advanced Learning Technologies, ICALT 2019 - Maceio, Brazil
Duration: 15 Jul 201918 Jul 2019

Publication series

NameProceedings - IEEE 19th International Conference on Advanced Learning Technologies, ICALT 2019

Conference

Conference19th IEEE International Conference on Advanced Learning Technologies, ICALT 2019
Country/TerritoryBrazil
CityMaceio
Period15/07/1918/07/19

Fingerprint

Dive into the research topics of 'Trust investigation in communities using feature learning'. Together they form a unique fingerprint.

Cite this