The Form of Content Personalisation at Mainstream, Transatlantic News Outlets: 2010–2016

Kunert, Jessica; Thurman, Neil

doi:10.1080/17512786.2019.1567271

Cited by 24 publications

(10 citation statements)

References 23 publications

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“…More and more online news services provide news to users in a personalized manner (Kunert & Thurman, 2019;Thurman & Schifferes, 2012). Simply put, a personalization system first collects personal data of users and constructs user profiles.…”

Section: Introductionmentioning

confidence: 99%

The personal information sphere: An integral approach to privacy and related information and communication rights

Eskens

2020

Asso for Info Science & Tech

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Data protection laws, including the European Union General Data Protection Regulation, regulate aspects of online personalization. However, the data protection lens is too narrow to analyze personalization. To define conditions for personalization, we should understand data protection in its larger fundamental rights context, starting with the closely connected right to privacy. If the right to privacy is considered along with other European fundamental rights that protect information and communication flows, namely, communications confidentiality; the right to receive information; and freedom of expression, opinion, and thought, these rights are observed to enable what I call a “personal information sphere” for each person. This notion highlights how privacy interferences affect other fundamental rights. The personal information sphere is grounded in European case law and is thus not just an academic affair. The essence of the personal information sphere is control, yet with a different meaning than mere control as guaranteed by data protection law. The personal information sphere is about people controlling how they situate themselves in information and communication networks. It follows that, to respect privacy and related rights, online personalization providers should actively involve users in the personalization process and enable them to use personalization for personal goals.

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Section: Introductionmentioning

confidence: 99%

The personal information sphere: An integral approach to privacy and related information and communication rights

Eskens

2020

Asso for Info Science & Tech

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“…Catering for audience tastes based on implicit or explicit user information can also increase the value for automated news, for example based on location, as suggested by Plattner and Orel (2019). However, as Kunert and Thurman (2019) found in their longitudinal study, most news organizations remain committed to exposing their audience to a diversity in news stories, reaffirming the prevailing framing of quality journalism.…”

Section: Introductionmentioning

confidence: 73%

“…The complexity of journalistic bias has gained a new dimension with digitalization. The shift towards mobile and the changes in audience behavior has increased the role of the audience, affecting news values and journalistic work (Harcup & O'Neill, 2016;Kunert & Thurman, 2019). Personalization, in effect a form of bias, has become a strategy for media organizations and platforms for creating customer value.…”

Section: Introductionmentioning

confidence: 99%

Automated Journalism as a Source of and a Diagnostic Device for Bias in Reporting

Leppänen

Tuulonen

Sirén-Heikel

2020

MaC

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In this article we consider automated journalism from the perspective of bias in news text. We describe how systems for automated journalism could be biased in terms of both the information content and the lexical choices in the text, and what mechanisms allow human biases to affect automated journalism even if the data the system operates on is considered neutral. Hence, we sketch out three distinct scenarios differentiated by the technical transparency of the systems and the level of cooperation of the system operator, affecting the choice of methods for investigating bias. We identify methods for diagnostics in each of the scenarios and note that one of the scenarios is largely identical to investigating bias in non-automatically produced texts. As a solution to this last scenario, we suggest the construction of a simple news generation system, which could enable a type of analysis-by-proxy. Instead of analyzing the system, to which the access is limited, one would generate an approximation of the system which can be accessed and analyzed freely. If successful, this method could also be applied to analysis of human-written texts. This would make automated journalism not only a target of bias diagnostics, but also a diagnostic device for identifying bias in human-written news.

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“…News recommendations are widespread, not only on large social media platforms but also in journalistic media (Kunert & Thurman, 2019). In a fragmented and rich information environment, algorithm-based recommender systems help users find relevant content (Bernstein et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…As social media and news aggregators nowadays have become a common way of accessing news, news organizations face pressure to offer a similar user experience to meet users' expectations (Nielsen, 2016). Implementing news recommendation algorithms on their web pages and mobile applications has thus become an integral part of their revenue strategies (Bodó, 2019;Kunert & Thurman, 2019). At the same time, not all news companies may be able, or want, to employ the "datahungry" personalization strategies of the recommendation systems developed by large tech platforms.…”

Section: Introductionmentioning

confidence: 99%

One Recommender Fits All? An Exploration of User Satisfaction With Text-Based News Recommender Systems

Wieland¹,

Nordheim²,

Königslöw³

2021

MaC

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Journalistic media increasingly address changing user behaviour online by implementing algorithmic recommendations on their pages. While social media extensively rely on user data for personalized recommendations, journalistic media may choose to aim to improve the user experience based on textual features such as thematic similarity. From a societal viewpoint, these recommendations should be as diverse as possible. Users, however, tend to prefer recommendations that enable “serendipity”—the perception of an item as a welcome surprise that strikes just the right balance between more similarly useful but still novel content. By conducting a representative online survey with n = 588 respondents, we investigate how users evaluate algorithmic news recommendations (recommendation satisfaction, as well as perceived novelty and unexpectedness) based on different similarity settings and how individual dispositions (news interest, civic information norm, need for cognitive closure, etc.) may affect these evaluations. The core piece of our survey is a self-programmed recommendation system that accesses a database of vectorized news articles. Respondents search for a personally relevant keyword and select a suitable article, after which another article is recommended automatically, at random, using one of three similarity settings. Our findings show that users prefer recommendations of the most similar articles, which are at the same time perceived as novel, but not necessarily unexpected. However, user evaluations will differ depending on personal characteristics such as formal education, the civic information norm, and the need for cognitive closure.

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The Form of Content Personalisation at Mainstream, Transatlantic News Outlets: 2010–2016

Cited by 24 publications

References 23 publications

The personal information sphere: An integral approach to privacy and related information and communication rights

The personal information sphere: An integral approach to privacy and related information and communication rights

Automated Journalism as a Source of and a Diagnostic Device for Bias in Reporting

One Recommender Fits All? An Exploration of User Satisfaction With Text-Based News Recommender Systems

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