Post-Hype Uses of Drones in News Reporting: Revealing the Site and Presenting Scope

Harvard, Jonas

doi:10.17645/mac.v8i3.3199

Cited by 8 publications

(4 citation statements)

References 20 publications

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“…In recent years, the news media industry has been significantly disrupted by the potential of technology-driven approaches across its entire value chain, including the creation, production, and distribution of news products and services (Hernandez Serrano, Greenhill, and Graham 2015). As a result, the impact of these computational resources can be seen in different news products, such as immersive and drone journalisms (Harvard 2020;Kang et al 2019), analytics (Ferrer-Conill andNelson and Tandoc 2018), automation (Lewis et al 2019;Linden 2017), artificial intelligence (Diakopoulos 2020;Jamil 2020), and data journalism (Coddington 2015;Hermida and Young 2019). Inevitably, the future of journalism and its business models seem to be dependent on the deployment of technology in news media organizations (Pavlik 2013;Örnebring 2010).…”

Section: Introductionmentioning

confidence: 99%

Data Journalism Beyond Technological Determinism

de-Lima-Santos

Mesquita

2021

Journalism Studies

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Innovation in journalism became an important element to determine the current and future direction of the profession. Through incremental and cumulative transformations over time, because of many obstacles faced inside the newsrooms, journalism has suffered from significant and fundamental changes, including the deployment of data journalism. In Latin America, the practice has seen an increasing expansion in the last years. Nevertheless, there are important technological gaps that limit its development. The present study draws upon literature on data journalism, media management, and sociology, aiming to contribute theoretically to data journalism research. Our findings show that beyond the technological approach, practitioners are relying on data evangelists, collaboration, and audience-centered innovation to produce data storytelling in their newsrooms. On the other hand, these alliances form "homophily" and "endogamy" features that limit the dissemination of the practice, which must consider the potential implications for the social distance of the audiences. It argues that Latin American professionals are distancing themselves from technological determinism to embrace a more audience-centric innovation in newsrooms. Finally, it also states that it is important to take into account those limitations, as they pose obstacles for data journalism innovation research knowledge. The article concludes with an agenda for future research.

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Section: Introductionmentioning

confidence: 99%

Data Journalism Beyond Technological Determinism

de-Lima-Santos

Mesquita

2021

Journalism Studies

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“…In recent years, news media has been greatly disrupted by the potential of technologically driven approaches in the creation, production, and distribution of news products and services (Hernandez Serrano et al 2015;Örnebring 2010). This can be seen in novel news products and practices such as data journalism (Coddington 2015;Hermida and Young 2019), immersive and drone journalism (Harvard 2020;Kang et al 2019), analytics (Nelson and Tandoc 2018;Ferrer-Conill and Tandoc 2018), and automation (Linden 2017b;Lewis et al 2019).…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence in News Media: Current Perceptions and Future Outlook

de-Lima-Santos

Ceron

2021

Journalism and Media

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In recent years, news media has been greatly disrupted by the potential of technologically driven approaches in the creation, production, and distribution of news products and services. Artificial intelligence (AI) has emerged from the realm of science fiction and has become a very real tool that can aid society in addressing many issues, including the challenges faced by the news industry. The ubiquity of computing has become apparent and has demonstrated the different approaches that can be achieved using AI. We analyzed the news industry’s AI adoption based on the seven subfields of AI: (i) machine learning; (ii) computer vision (CV); (iii) speech recognition; (iv) natural language processing (NLP); (v) planning, scheduling, and optimization; (vi) expert systems; and (vii) robotics. Our findings suggest that three subfields are being developed more in the news media: machine learning, computer vision, and planning, scheduling, and optimization. Other areas have not been fully deployed in the journalistic field. Most AI news projects rely on funds from tech companies such as Google. This limits AI’s potential to a small number of players in the news industry. We made conclusions by providing examples of how these subfields are being developed in journalism and presented an agenda for future research.

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“…In recent years, news media have been hugely disrupted by the potential of technological-driven approaches in the creation, production, and distribution of news products and services (Hernandez Serrano, Greenhill, and Graham 2015;Örnebring 2010), which can be seen in novel news products and practices: data journalism (Coddington 2015;Hermida and Young 2019), immersive and drone journalisms (Harvard 2020;Kang et al 2019), analytics (Nelson and Tandoc 2018;Ferrer-Conill and Tandoc 2018), and automation (Linden 2017b;Lewis, Guzman, and Schmidt 2019).…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence in News Media: Current Perceptions and Future Outlook

de-Lima-Santos¹,

Ceron²

2021

Preprint

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In recent years, news media have been hugely disrupted by the potential of technological-driven approaches in the creation, production, and distribution of news products and services. Artificial intelligence (AI) has emerged from the realm of science fiction and has become a very real tool that can aid society in addressing many issues, including the challenges faced by the news industry. The ubiquity of computing has become apparent and has shown the different approaches that can be achieved using AI. We analyzed the news industry AI adoption based on the seven subfields emanated from AI: (i) machine learning; (ii) computer vision (CV); (iii) speech recognition; (iv) natural language processing (NLP); (v) planning, scheduling, and optimization; (vi) expert systems; and (vii) robotics. Our findings suggest that three subfields are being more developed in the news media: machine learning, planning, scheduling &amp; optimization, and computer vision. Other areas are still not fully deployed in the journalistic field. Most of the AI news projects rely on funds from tech companies, such as Google. This limits the potential of AI in the news industry to a small number of players. We conclude by providing examples of how these subfields are being developed in journalism and present an agenda for future research.

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Post-Hype Uses of Drones in News Reporting: Revealing the Site and Presenting Scope

Cited by 8 publications

References 20 publications

Data Journalism Beyond Technological Determinism

Data Journalism Beyond Technological Determinism

Artificial Intelligence in News Media: Current Perceptions and Future Outlook

Artificial Intelligence in News Media: Current Perceptions and Future Outlook

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