Abstract
We propose a users’ stance and credibility based social-sensor cloud service trust model. We represent social media data streams, i.e., image meta-data and related posted information, as social-sensor cloud services. We use the textual features of the social-sensor cloud services, i.e., comments, and meta-data, e.g., spatio-temporal information, to gather the trust-rate of the services and the credibility of users’ comments. The analytical results present the performance of the proposed model.
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AYLIEN Text Analysis - https://aylien.com/text-api/.
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JWNL - JavaWordNet Library - Dev Guide”, http://jwordnet.sourceforge.net/handbook.html.
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Acknowledgement
This research was partly made possible by NPRP 9-224-1-049 grant from the Qatar National Research Fund (a member of The Qatar Foundation) and DP1501 00149 and LE180100158 grants from Australian Research Council. The statements made herein are solely the responsibility of the authors.
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Aamir, T., Dong, H., Bouguettaya, A. (2018). Stance and Credibility Based Trust in Social-Sensor Cloud Services. In: Hacid, H., Cellary, W., Wang, H., Paik, HY., Zhou, R. (eds) Web Information Systems Engineering – WISE 2018. WISE 2018. Lecture Notes in Computer Science(), vol 11234. Springer, Cham. https://doi.org/10.1007/978-3-030-02925-8_13
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DOI: https://doi.org/10.1007/978-3-030-02925-8_13
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