Julian Maitra
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Maitra
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  • Publication
    News Organizations’ Use of Native Videos on Facebook: Tweaking the Journalistic Field One Algorithm Change at a Time
    Tandoc, Edson C.
    ;
    Maitra, Julian
    Guided by field theory, this paper explores the influence of the technological field on the journalistic field by examining how news organizations responded to Facebook’s algorithm tweak, announced in June 2014, that prioritized videos directly uploaded on the social media platform. In announcing the tweak, Facebook did not just change its own internal rules, but also imposed them on users, including news organizations traditionally governed by journalism’s own set of rules. Based on large scale data collected from 232 Facebook Pages operated by major news organizations in the United States, this study found that most news organizations complied with Facebook’s updated rules on Native Videos by significantly increasing their social video production, opening up the journalistic field to the influence of an agent external to journalism.
    Type: conference paper
    URL: https://convention2.allacademic.com/one/ica/ica17/
    URI: https://www.alexandria.unisg.ch/handle/20.500.14171/116524
  • Publication
    Mapping social media news in Europe: A comparative actor-network investigation of authors, articles, publishers and platforms in France, Germany, Italy, Spain, and the UK
    ( 2018-11-01)
    Maitra, Julian
    ;
    Tandoc, Edson C.
    Guided by actor-network theory, this study analyzes the news ecosystem as a complex network of users, news stories, journalists, publishers, and platforms in five major European countries. The study consists of an empirical and theoretical part. It develops an empirically-based model of the journalistic network of digital artifacts (e.g. news articles), humans (e.g. users, journalists) and non-human actants (e.g. news feeds). The aim is to better understand the changing role of European legacy news outlets that operate in an environment increasingly dominated by platform technologies (Bell & Owen, 2017; Kleis Nielsen & Ganter, 2017). In the empirical part, a quantitative analysis of news shared on social media platforms was performed. The objective was to obtain a representative sample of online news articles published by major European media organizations and their corresponding social media interactions. The sample consists of online news articles (n = 198.921) published between March 2017 – February 2018. It includes data from 20 legacy publishers and broadcasters from France, Germany, Italy, Spain, and the UK. Examples are BBC News, El Paìs, La Repubblica, Bild and France24. For each organization, up to 10.000 most shared online articles were extracted using commercial social media analytics software (BuzzSumo) that queries public data APIs (application programming interfaces). Article variables include the URL, title and the number of shares on Facebook, Twitter, LinkedIn, and Pinterest. Further variables are text length (word count) and author name. These data were used to perform a comparative analysis across countries, social media platforms, and organization types to draw a representative image of the European social news network. The empirical results suggest significant differences in social media interaction patterns across nations, especially Germany and the UK, as well as platforms. Moreover, the downward trend of social media interactions with news content – primarily induced by tweaks to the Facebook News Feed that favor other content (Newman, 2018) – can be reproduced. Methodologically, the empirical part uses descriptive statistics, correlation analysis as well as keyword-based content analysis. In the theoretical part of the paper, insights from ANT-studies of journalism (i.e. Lewis & Westlund, 2015; Schudson, 2015; Turner, 2005) are used to critically assess the empirical findings. For example, the number of social media interactions some (viral) articles have generated while others remain unsuccessful are explained as a result of differences in material agency. Furthermore, the downward trend in social interactions tweaks to the Facebook News Feed have created, can similarly be understood as the result of a behavioral change of a powerful algorithmic actant (Lewis & Westlund, 2015). Such a non-anthropocentric view on the digital news ecosystem, we argue, may also help overcome problems of inscrutability of the black-box-nature of algorithmically-driven tech platforms that continue to disrupt journalism.
    Type: conference paper
    URI: https://www.alexandria.unisg.ch/handle/20.500.14171/99890
  • Publication
    Audience Measurement
    (John Wiley & Sons, Inc., 2019-04-29)
    Tandoc, Edson C.
    ;
    Maitra, Julian
    ;
    Vos, Tim P.
    ;
    Hanusch, Folker
    ;
    Dimitrakopoulou, Dimitra
    ;
    Geertsema-Sligh, Margaretha
    ;
    Sehl, Annika
    Audience measurement refers to the goal‐oriented process of collecting, analyzing, reporting, and interpreting data about the size, composition, behavior, characteristics, and preferences of individuals interacting with particular media brands or products. Traditional tools include focus group interviews, circulation audits, media diaries, surveys, and people meters. These were usually conducted by ratings or audit firms. But the rise of digital journalism also led to new tools, such as web and social media analytics, conducted by news organizations themselves or by third‐party applications, such as Facebook. Unlike traditional tools, analytics are (a) faster to collect; (b) automatic, as both deliberate and incidental feedback are recorded; (c) more inclusive, as data come from a much larger number of the audience; and (d) more comprehensive. Thus, audience measurement has evolved from a state when data points were few and collection was expensive to a situation of abundant data and low‐cost analytics, presenting new challenges.
    Type: book section
    URL: https://onlinelibrary.wiley.com/doi/10.1002/9781118841570.iejs0047
    DOI: 10.1002/9781118841570.iejs0047
    URI: https://www.alexandria.unisg.ch/handle/20.500.14171/98710
  • Publication
    Analysing news values in the age of analytics
    (Palgrave MacMillan, 2021)
    Tandoc, Edson C.
    ;
    Cheng, Lydia
    ;
    Maitra, Julian
    ;
    Temmerman, Martina
    ;
    Mast, Jelle
    News values are based in part on journalists’ beliefs about the audience, which were, at least in the past, mostly based on journalists’ own imaginations of the actual audience. Now, with web analytics, journalists’ beliefs about the audience can be informed and influenced by a wealth of accessible and quantifiable audience data. Still, journalists must balance audience preferences with their news judgement and the norms that guide their news work. This chapter argues that to maintain editorial autonomy in the face of increasing influence from the audience, journalists might be tweaking their assessment of news values to reflect more of what they know about audience preferences.
    Type: forthcoming
    Journal: News values from an audience perspective
    URL: https://www.palgrave.com/gp/book/9783030450458
    DOI: 10.1007/978-3-030-45046-5
    URI: https://www.alexandria.unisg.ch/handle/20.500.14171/111387
    Scopus© Citations 4