SMART: A Tool for Trust and Reputation Management in Social Media

Nishant Saurabh; Manuel Herold; Hamid Mohammadi Fard; Radu Prodan

doi:10.1007/978-3-031-06156-1_33

SMART: A Tool for Trust and Reputation Management in Social Media

Nishant Saurabh^*, Manuel Herold, Hamid Mohammadi Fard, Radu Prodan

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Abstract

Social media platforms are becoming increasingly popular and essential for next-generation connectivity. However, the emergence of social media also poses critical trust challenges due to the vast amount of created and propagated content. This paper proposes a data-driven tool called SMART for trust and reputation management based on community engagement and rescaled sigmoid model. SMART’s integrated design adopts a set of expert systems with a unique inference logic for trust estimation to compute weighted trust ratings of social media content. SMART further utilizes the trust ratings to compute user reputation and represent them using a sigmoid curve that prevents infinite accumulation of reputation ratings by a user. We demonstrate the SMART tool prototype using a pilot social media application and highlight its user-friendly interfaces for trustworthy content exploration.

Original language	English
Title of host publication	Euro-Par 2021
Subtitle of host publication	Parallel Processing Workshops - Euro-Par 2021 International Workshops, 2021, Revised Selected Papers
Editors	Ricardo Chaves, Dora B. Heras, Aleksandar Ilic, Didem Unat, Rosa M. Badia, Andrea Bracciali, Patrick Diehl, Anshu Dubey, Oh Sangyoon, Stephen L. Scott, Laura Ricci
Publisher	Springer
Pages	417-427
Number of pages	11
ISBN (Print)	9783031061554
DOIs	https://doi.org/10.1007/978-3-031-06156-1_33
Publication status	Published - 2022
Externally published	Yes
Event	27th International Conference on Parallel and Distributed Computing, Euro-Par 2021 - Virtual, Online Duration: 30 Aug 2021 → 31 Aug 2021

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13098 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	27th International Conference on Parallel and Distributed Computing, Euro-Par 2021
City	Virtual, Online
Period	30/08/21 → 31/08/21

Bibliographical note

Funding Information:
ARTICONF receives funding from the European Union’s Horizon 2020 research and innovation program under grant agreement number 825134.

Publisher Copyright:
© 2022, Springer Nature Switzerland AG.

Funding

This work received funding from the European Union’s Horizon 2020 research and innovation programme, grant agreement 825134, “Smart Social Media Ecosytstem in a Blockchain Federated Environment (ARTICONF)”.

Keywords

Community engagement
Reputation
Sigmoid model
Social media
Trust

Access to Document

10.1007/978-3-031-06156-1_33

Cite this

Saurabh, N., Herold, M., Fard, H. M., & Prodan, R. (2022). SMART: A Tool for Trust and Reputation Management in Social Media. In R. Chaves, D. B. Heras, A. Ilic, D. Unat, R. M. Badia, A. Bracciali, P. Diehl, A. Dubey, O. Sangyoon, S. L. Scott, & L. Ricci (Eds.), Euro-Par 2021: Parallel Processing Workshops - Euro-Par 2021 International Workshops, 2021, Revised Selected Papers (pp. 417-427). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13098 LNCS). Springer. https://doi.org/10.1007/978-3-031-06156-1_33

Saurabh, Nishant ; Herold, Manuel ; Fard, Hamid Mohammadi et al. / SMART : A Tool for Trust and Reputation Management in Social Media. Euro-Par 2021: Parallel Processing Workshops - Euro-Par 2021 International Workshops, 2021, Revised Selected Papers. editor / Ricardo Chaves ; Dora B. Heras ; Aleksandar Ilic ; Didem Unat ; Rosa M. Badia ; Andrea Bracciali ; Patrick Diehl ; Anshu Dubey ; Oh Sangyoon ; Stephen L. Scott ; Laura Ricci. Springer, 2022. pp. 417-427 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Social media platforms are becoming increasingly popular and essential for next-generation connectivity. However, the emergence of social media also poses critical trust challenges due to the vast amount of created and propagated content. This paper proposes a data-driven tool called SMART for trust and reputation management based on community engagement and rescaled sigmoid model. SMART{\textquoteright}s integrated design adopts a set of expert systems with a unique inference logic for trust estimation to compute weighted trust ratings of social media content. SMART further utilizes the trust ratings to compute user reputation and represent them using a sigmoid curve that prevents infinite accumulation of reputation ratings by a user. We demonstrate the SMART tool prototype using a pilot social media application and highlight its user-friendly interfaces for trustworthy content exploration.",

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note = "Funding Information: ARTICONF receives funding from the European Union{\textquoteright}s Horizon 2020 research and innovation program under grant agreement number 825134. Publisher Copyright: {\textcopyright} 2022, Springer Nature Switzerland AG.; 27th International Conference on Parallel and Distributed Computing, Euro-Par 2021 ; Conference date: 30-08-2021 Through 31-08-2021",

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Saurabh, N, Herold, M, Fard, HM & Prodan, R 2022, SMART: A Tool for Trust and Reputation Management in Social Media. in R Chaves, D B. Heras, A Ilic, D Unat, RM Badia, A Bracciali, P Diehl, A Dubey, O Sangyoon, S L. Scott & L Ricci (eds), Euro-Par 2021: Parallel Processing Workshops - Euro-Par 2021 International Workshops, 2021, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13098 LNCS, Springer, pp. 417-427, 27th International Conference on Parallel and Distributed Computing, Euro-Par 2021, Virtual, Online, 30/08/21. https://doi.org/10.1007/978-3-031-06156-1_33

SMART: A Tool for Trust and Reputation Management in Social Media. / Saurabh, Nishant; Herold, Manuel; Fard, Hamid Mohammadi et al.
Euro-Par 2021: Parallel Processing Workshops - Euro-Par 2021 International Workshops, 2021, Revised Selected Papers. ed. / Ricardo Chaves; Dora B. Heras; Aleksandar Ilic; Didem Unat; Rosa M. Badia; Andrea Bracciali; Patrick Diehl; Anshu Dubey; Oh Sangyoon; Stephen L. Scott; Laura Ricci. Springer, 2022. p. 417-427 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13098 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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AB - Social media platforms are becoming increasingly popular and essential for next-generation connectivity. However, the emergence of social media also poses critical trust challenges due to the vast amount of created and propagated content. This paper proposes a data-driven tool called SMART for trust and reputation management based on community engagement and rescaled sigmoid model. SMART’s integrated design adopts a set of expert systems with a unique inference logic for trust estimation to compute weighted trust ratings of social media content. SMART further utilizes the trust ratings to compute user reputation and represent them using a sigmoid curve that prevents infinite accumulation of reputation ratings by a user. We demonstrate the SMART tool prototype using a pilot social media application and highlight its user-friendly interfaces for trustworthy content exploration.

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Saurabh N, Herold M, Fard HM, Prodan R. SMART: A Tool for Trust and Reputation Management in Social Media. In Chaves R, B. Heras D, Ilic A, Unat D, Badia RM, Bracciali A, Diehl P, Dubey A, Sangyoon O, L. Scott S, Ricci L, editors, Euro-Par 2021: Parallel Processing Workshops - Euro-Par 2021 International Workshops, 2021, Revised Selected Papers. Springer. 2022. p. 417-427. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-06156-1_33