MOGPlay: A Decentralized Crowd Journalism Application for Democratic News Production
Publication date
2022
Authors
Lima, Ines Rito
Marinho, Claudia
Filipe, V.L.S.
Ulisses, Alexandre
Saurabh, Nishant
Chakravorty, Antorweep
Zhao, Zhiming
Hristov, Atanas
Prodan, Radu
Editors
An, Jisun
Charalampos, Chelmis
Magdy, Walid
Advisors
Supervisors
Document Type
Part of book
Metadata
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License
taverne
Abstract
Media production and consumption behaviors are changing in response to new technologies and demands, giving birth to a new generation of social applications. Among them, crowd journalism represents a novel way of constructing democratic and trustworthy news relying on ordinary citizens arriving at breaking news locations and capturing relevant videos using their smartphones. The ARTICONF project [1] proposes a trustworthy, resilient, and globally sustainable toolset for developing decentralized applications (DApps). Leveraging the ARTICONF tools, we introduce a new DApp for crowd journalism called MOGPlay. MOGPlay collects and manages audio-visual content generated by citizens and provides a secure blockchain platform that rewards all stakeholders involved in professional news production. Besides live streaming, MOGPlay offers a marketplace for audio-visual content trading among citizens and free journalists with an internal token ecosystem. We discuss the functionality and implementation of the MOGPlay DApp and illustrate three pilot crowd journalism live scenarios that validate the prototype.
Keywords
citizen-generated content, Crowd journalism, decentralized app, marketplace, social media, Taverne, Artificial Intelligence, Computer Networks and Communications, Information Systems, Information Systems and Management, Communication
Citation
Lima, I R, Marinho, C, Filipe, V, Ulisses, A, Saurabh, N, Chakravorty, A, Zhao, Z, Hristov, A & Prodan, R 2022, MOGPlay : A Decentralized Crowd Journalism Application for Democratic News Production. in J An, C Charalampos & W Magdy (eds), Proceedings: IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). IEEE, pp. 462-469, 14th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2022, Virtual, Online, Turkey, 10/11/22. https://doi.org/10.1109/ASONAM55673.2022.10068697, conference