Browsing by Subject "news automation"

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  • Linden, Tommy Carl-Gustav (2017)
    Software-generated news, sometimes called “robot journalism,” has recently given rise to concerns that the automation of news will make journalists redundant. These arguments follow a deterministic line of thinking. Algorithms choose information for users but are also the construct of social process and practice. The aim of this essay is to explore “the algorithmic turn” (Napoli, 2014a) in news production. Based on case studies from three separate news outlets it is found that the impact of automated news is, first, increased efficiency and job satisfaction with automation of monotonous and error-prone routine tasks; second, automation of journalism routine tasks resulting in losses of journalist jobs; and third, new forms of work that require computational thinking
  • Haapanen, Lauri; Leppänen, Leo (2020)
    The amount of available digital data is increasing at a tremendous rate. These data, however, are of limited use unless converted into a user-friendly form. We took on this task and built a natural language generation (NLG) driven system that generates journalistic news stories about elections without human intervention. In this paper, after presenting an overview of stateof-the-art technologies in NLG, we explain systematically how we identified and then recontextualized the determinant aspects of the genre of an online news story in the algorithm of our NLG software. In the discussion, we introduce the key results of a user test we carried out and some improvements that these results suggest. Then, after relating the news items that our NLG system generates to general aspects of genres and their evolution, we conclude by questioning the idea that journalistic NLG systems should mimic journalism written by humans. Instead, we suggest that developmental work in the field of news automation should aim to create a new genre based on the inherent strengths of NLG. Finally, we present a few suggestions as to what this genre could include.
  • Sirén-Heikel, Stefanie; Leppänen, Leo; Lindén, Carl-Gustav; Bäck, Asta (2019)
    News automation is an emerging field within journalism, with the potential to transform newswork. Increasing access to data, combined with developing technology, will allow further inquiries into automated journalism. Producing news text using NLG (natural language generation) is currently largely undertaken in specific, predictable news domains, such as sports or finance. This interdisciplinary study investigates how elite media representatives from Finland, Europe and the US imagine the affordances of this emerging technology for their organization. Our analysis shows how the affordances of news automation are imagined as providing efficiency, increasing output and aiding in reallocating resources to pursue quality journalism. The affordances are, however, constrained by such factors as access to structured data, the quality of automation and a lack of relevant skills. In its current form, automated text generation is seen as providing only limited benefits to news organizations that are already imagining further possibilities of automation.
  • Kjellman, Martin (Helsingin yliopisto, 2021)
    This thesis examines how representatives of service providers for news automation perceive a) journalists and news organisations and b) the service providers’ relationship to these. By introducing new technology (natural language generation, i.e. the transformation of data into everyday language) that influences both the production and business models of news media, news automation represents a type of media innovation. The service providers represent actors peripheral to journalism. The theoretical framework takes hybrid media logics as its starting point, meaning that the power dynamics of news production are thought to be influenced by the field-specific logics of the actors involved. The hybridity metaphor is deepened by using a typology for journalistic strangers that takes into account the different roles peripheral actors adopt in relation to journalists and news organisations. Journalism is understood throughout as a professional ideology encountered by service providers who work with news organisations. Semi-structured interviews were conducted with representatives from companies that create natural language generation software used to produce journalistic text based on data. Participants were asked about their experiences working with news media and the interviews (N=6) were analysed phenomenologically. The findings form three distinct but interrelated dimensions of how the service providers perceive news media and journalism: an area that sorely needs innovators (potential) but lacks resources in terms of knowledge, money and will to innovate (obstacles), but one that they can ultimately learn from and collaborate with (solutions). Their own relationship to journalism and news media is not fixed to one single role. Instead, they alternate between challenging news media (explicit interloping) and inhabiting a supportive role (implicit interloping). This thesis serves as an exploration into how service providers for news automation affect the power dynamics of news production. It does so by unveiling how journalists and news organisations are perceived, and by adding further understanding to previous research on actors peripheral to journalism. In order to further untangle how service providers for news automation shift the balance of power shaping news production, future research should attempt to unify the way traditional news media actors and service providers perceive each other and their collaborations.