{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T22:25:50Z","timestamp":1783376750095,"version":"3.54.6"},"reference-count":70,"publisher":"Association for Computing Machinery (ACM)","issue":"5","license":[{"start":{"date-parts":[[2024,10,31]],"date-time":"2024-10-31T00:00:00Z","timestamp":1730332800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"NSF","award":["2107450"],"award-info":[{"award-number":["2107450"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Intell. Syst. Technol."],"published-print":{"date-parts":[[2024,10,31]]},"abstract":"<jats:p>\n            As online social networks (OSNs) become more prevalent, a new paradigm for problem-solving through crowd-sourcing has emerged. By leveraging the OSN platforms, users can post a problem to be solved and then form a team to collaborate and solve the problem. A common concern in OSNs is how to form effective collaborative teams, as various tasks are completed through online collaborative networks. A team\u2019s diversity in expertise has received high attention to producing high team performance in developing team formation (TF) algorithms. However, the effect of team diversity on performance under different types of tasks has not been extensively studied. Another important issue is how to balance the need to preserve individuals\u2019 privacy with the need to maximize performance through active collaboration, as these two goals may conflict with each other. This research has not been actively studied in the literature. In this work, we develop a TF algorithm in the context of OSNs that can maximize team performance and preserve team members\u2019 privacy under different types of tasks. Our proposed PRivAcy-Diversity-Aware TF framework, called\n            <jats:monospace>PRADA-TF<\/jats:monospace>\n            , is based on trust relationships between users in OSNs where trust is measured based on a user\u2019s expertise and privacy preference levels. The PRADA-TF algorithm considers the team members\u2019 domain expertise, privacy preferences, and the team\u2019s expertise diversity in the process of TF. Our approach employs game-theoretic principles\n            <jats:italic>Mechanism Design<\/jats:italic>\n            to motivate self-interested individuals within a TF context, positioning the mechanism designer as the pivotal team leader responsible for assembling the team. We use two real-world datasets (i.e., Netscience and IMDb) to generate different semi-synthetic datasets for constructing trust networks using a belief model (i.e., Subjective Logic) and identifying trustworthy users as candidate team members. We evaluate the effectiveness of our proposed\n            <jats:monospace>PRADA-TF<\/jats:monospace>\n            scheme in four variants against three baseline methods in the literature. Our analysis focuses on three performance metrics for studying OSNs: social welfare, privacy loss, and team diversity.\n          <\/jats:p>","DOI":"10.1145\/3670411","type":"journal-article","created":{"date-parts":[[2024,6,5]],"date-time":"2024-06-05T14:21:12Z","timestamp":1717597272000},"page":"1-32","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Privacy-Preserving and Diversity-Aware Trust-based Team Formation in Online Social Networks"],"prefix":"10.1145","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1784-9417","authenticated-orcid":false,"given":"Yash","family":"Mahajan","sequence":"first","affiliation":[{"name":"Virginia Tech, Falls Church, VA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5908-4662","authenticated-orcid":false,"given":"Jin-Hee","family":"Cho","sequence":"additional","affiliation":[{"name":"Virginia Tech, Falls Church, VA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1657-6728","authenticated-orcid":false,"given":"Ing-Ray","family":"Chen","sequence":"additional","affiliation":[{"name":"Virginia Tech, Falls Church, VA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2024,11,6]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"crossref","first-page":"839","DOI":"10.1145\/2187836.2187950","volume-title":"Proceedings of the 21st international conference on World Wide Web","author":"Anagnostopoulos Aris","year":"2012","unstructured":"Aris Anagnostopoulos, Luca Becchetti, Carlos Castillo, Aristides Gionis, and Stefano Leonardi. 2012. 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