{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,14]],"date-time":"2026-02-14T10:23:00Z","timestamp":1771064580942,"version":"3.50.1"},"reference-count":43,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2024,6,25]],"date-time":"2024-06-25T00:00:00Z","timestamp":1719273600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Internet"],"abstract":"<jats:p>This paper introduces the INFLUTRUST framework that is designed to address challenges in trust-based influencer marketing campaigns on Online Social Networks (OSNs). The INFLUTRUST framework enables the influencers to autonomously select products across the OSN platforms for advertisement by employing a reinforcement learning algorithm. The Stochastic Learning Automata reinforcement algorithm considers the OSN platforms\u2019 provided monetary rewards, the influencers\u2019 advertising profit, and the influencers\u2019 trust levels towards the OSN platforms to enable the influencers to autonomously select an OSN platform. The trust model for the influencers incorporates direct and indirect trust, which are derived from past interactions and social ties among the influencers and the OSN platforms, respectively. The OSN platforms allocate rewards through a multilateral bargaining model that supports competition among the influencers. Simulation-based results validate the INFLUTRUST framework\u2019s effectiveness across diverse scenarios, with the scalability analysis demonstrating its robustness. Comparative evaluations highlight the INFLUTRUST framework\u2019s superiority in considering trust levels and reward allocation fairness, benefiting both the influencers and the OSN platforms.<\/jats:p>","DOI":"10.3390\/fi16070222","type":"journal-article","created":{"date-parts":[[2024,6,25]],"date-time":"2024-06-25T10:10:07Z","timestamp":1719310207000},"page":"222","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["INFLUTRUST: Trust-Based Influencer Marketing Campaigns in Online Social Networks"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-4823-3443","authenticated-orcid":false,"given":"Adedamola","family":"Adesokan","sequence":"first","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM 87131-0001, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1802-484X","authenticated-orcid":false,"given":"Aisha B","family":"Rahman","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM 87131-0001, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1322-1876","authenticated-orcid":false,"given":"Eirini Eleni","family":"Tsiropoulou","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM 87131-0001, USA"}]}],"member":"1968","published-online":{"date-parts":[[2024,6,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Yang, M., Seklouli, A.S., Zhang, H., Ren, L., Yu, X., and Ouzrout, Y. 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