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A Semantic Preprocessing Framework for Breaking News Detection to Support Future Drone Journalism Services

Author

Listed:
  • Michail Niarchos

    (School of Journalism & Mass Communication, Aristotle University of Thessaloniki, 54636 Thessaloniki, Greece)

  • Marina Eirini Stamatiadou

    (School of Journalism & Mass Communication, Aristotle University of Thessaloniki, 54636 Thessaloniki, Greece)

  • Charalampos Dimoulas

    (School of Journalism & Mass Communication, Aristotle University of Thessaloniki, 54636 Thessaloniki, Greece)

  • Andreas Veglis

    (School of Journalism & Mass Communication, Aristotle University of Thessaloniki, 54636 Thessaloniki, Greece)

  • Andreas Symeonidis

    (School of Journalism & Mass Communication, Aristotle University of Thessaloniki, 54636 Thessaloniki, Greece)

Abstract

Nowadays, news coverage implies the existence of video footage and sound, from which arises the need for fast reflexes by media organizations. Social media and mobile journalists assist in fulfilling this requirement, but quick on-site presence is not always feasible. In the past few years, Unmanned Aerial Vehicles (UAVs), and specifically drones, have evolved to accessible recreational and business tools. Drones could help journalists and news organizations capture and share breaking news stories. Media corporations and individual professionals are waiting for the appropriate flight regulation and data handling framework to enable their usage to become widespread. Drone journalism services upgrade the usage of drones in day-to-day news reporting operations, offering multiple benefits. This paper proposes a system for operating an individual drone or a set of drones, aiming to mediate real-time breaking news coverage. Apart from the definition of the system requirements and the architecture design of the whole system, the current work focuses on data retrieval and the semantics preprocessing framework that will be the basis of the final implementation. The ultimate goal of this project is to implement a whole system that will utilize data retrieved from news media organizations, social media, and mobile journalists to provide alerts, geolocation inference, and flight planning.

Suggested Citation

  • Michail Niarchos & Marina Eirini Stamatiadou & Charalampos Dimoulas & Andreas Veglis & Andreas Symeonidis, 2022. "A Semantic Preprocessing Framework for Breaking News Detection to Support Future Drone Journalism Services," Future Internet, MDPI, vol. 14(1), pages 1-19, January.
    • Handle: RePEc:gam:jftint:v:14:y:2022:i:1:p:26-:d:721713
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    References listed on IDEAS

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    1. Jonas Harvard, 2020. "Post-Hype Uses of Drones in News Reporting: Revealing the Site and Presenting Scope," Media and Communication, Cogitatio Press, vol. 8(3), pages 85-92.
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    Cited by:

    1. Charalampos A. Dimoulas & Andreas Veglis, 2023. "Theory and Applications of Web 3.0 in the Media Sector," Future Internet, MDPI, vol. 15(5), pages 1-10, April.
    2. Faris A. Almalki & Maha Aljohani & Merfat Algethami & Ben Othman Soufiene, 2022. "Incorporating Drone and AI to Empower Smart Journalism via Optimizing a Propagation Model," Sustainability, MDPI, vol. 14(7), pages 1-24, March.

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    1. Jonas Harvard & Mats Hyvönen & Ingela Wadbring, 2020. "Journalism from Above: Drones and the Media in Critical Perspective," Media and Communication, Cogitatio Press, vol. 8(3), pages 60-63.

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