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Are the most popular users always trustworthy? The case of Yelp.

, and . Electron. Commer. Res. Appl., (2016)

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Exploiting the Error Correction Mechanism in QR Codes for Secret Sharing., , , , , and . ACISP (1), volume 9722 of Lecture Notes in Computer Science, page 409-425. Springer, (2016)Are the most popular users always trustworthy? The case of Yelp., and . Electron. Commer. Res. Appl., (2016)Malicious Web Domain Identification using Online Credibility and Performance Data by Considering the Class Imbalance Issue., , , , and . CoRR, (2018)A distributed mechanism for secure collaboration in digital ecosystems., , and . MEDES, page 33-39. ACM, (2011)Design of a Technology-Enhanced Pedagogical Framework for a Systems and Networking Administration course incorporating a Virtual Laboratory., , , , , , and . FIE, page 1-5. IEEE, (2018)Identifying malicious web domains using machine learning techniques with online credibility and performance data., , , , and . CEC, page 5186-5194. IEEE, (2016)Determining Trustworthiness and Quality of Mobile Applications., , and . MOBILWARE, volume 65 of Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, page 192-206. Springer, (2012)A survey on the usability and effectiveness of web-based trust rating systems., , and . ICIS, page 455-460. IEEE Computer Society, (2013)TIDE: measuring and evaluating trustworthiness and credibility of enterprises in digital ecosystem., , and . MEDES, page 9-16. ACM, (2011)A Distributed Secure Mechanism for Resource Protection in a Digital Ecosystem Environment., , and . J. Information Security, 3 (1): 25-38 (2012)