[Commlist] Call for papers: Vol. 26 Nº 49 | Building the Algorithmic Audience

*Call for papers* Vol. 26 Nº 49 | Building the Algorithmic Audience |
Until April 30, 2026
*The Call for papers for the Media & Journalism on Building the
Algorithmic Audience: Shifting Paradigms in Communications, Media, and
Democracy is open from January 22 to April 30, 2026
*Thematic editors: Berta García Orosa, Inês Amaral & Noel Pascual Presa*

The topic of this call for papers seeks to gather original,
interdisciplinary, and empirically grounded research that explores how
audiences are constructed within digital public spheres. The
development of technologies such as artificial intelligence or big
data has not only transformed the production, distribution, and
circulation of information, but also redefined the ways in which
audiences are imagined and constructed. In its early stages
(approximately 20 years ago), the continuous analysis of big data
allowed for real-time audience insights and, subsequently, the
prediction of audience behaviour, as exemplified by the Cambridge
Analytica case. However, the focus has now shifted towards
constructing audiences before messages are even produced, particularly
in the context of electoral campaigns.
While there is a growing academic interest in the effects of media
automation and personalisation, there has yet to be a convergence of
studies that systematically examine the epistemological, political,
ethical, and communicative implications of this new relationship
between algorithms and audiences. This gap is even more striking when
considering the far-reaching nature of the phenomenon, which spans
across journalism, political communication, digital culture, and
platform governance.
In this fourth wave of digital communication, algorithms not only
predict audience behaviours but also influence and shape them, giving
rise to what has been termed the “algorithmic audience” (Riemer &
Peter, 2021). This process of datafication has led to new methods of
classification, personalisation, and micro-segmentation of audiences,
profoundly transforming the logic of political mediation.
This scenario marks a paradigm shift: while traditional scientific
episteme conceived of audiences through ascribed categories such as
class, gender, or ideology, the new algorithmic paradigm is grounded
in behavioural data, adopting a performative logic that dissolves
fixed classifications (Fisher & Mehozay, 2019).
However, this transformation is far from neutral. The new ways of
constructing algorithmic audiences present democratic risks: automated
biases (Kordzadeh & Ghasemaghaei, 2021), opacity in content selection
(Livingstone, 2019), challenges to  informational plurality and
freedom of expression (Riemer & Peter, 2021), and growing inequality
in voice representation (Jones, 2023; Zarouali et al., 2021). The
construction of new public spheres requires critical and urgent
analysis.
These changes are affecting public discourse, with journalism at the
forefront of the transformation. The growing reliance on algorithms is
reshaping the profession, giving rise to what has been termed
“automated journalism” or “robot journalism”, driven by the automation
and personalisation of news content (Carlson, 2015; Clerwall, 2014).
Although this personalisation offers opportunities to strengthen the
relationship with audiences (Ford & Hutchinson, 2019), it also
introduces challenges, as public trust in the media may be undermined
by the perceived risks inherent to these dynamics(Livingstone, 2019;
Sehl & Eder, 2023). These new tools have far-reaching implications,
both professionally and socially: from threats to freedom of
expression and the need for new policies on content authorship, to the
impact on the legitimacy of journalistic judgement and the
reconfiguration of audiences (Carlson, 2018; Fisher & Mehozay, 2019;
Montal & Reich,2016; Riemer & Peter, 2021).
From an identity perspective, the relationship with audiences remains
central. However, the emphasis has shifted: personalised and
individualised messaging have lost prominence, giving way to a more
community-centred discourse. Inpractice, community is constructed
around paid subscriptions and access to exclusive features and
content. Narratives are constructed around this group of members or
subscribers to persuade them of their relevance to the survival and
quality of the media’s journalistic practice.
At the same time, users often perceive algorithmic content selection
based on their consumption behaviour in a positive light (Thurman,
2018). This personalisation is accompanied by increasing
categorisation and micro-segmentation, allowing for more granular and
precise user classification (Beauvisage et al., 2024). Nonetheless,
this positive perception and micro-segmentation do not protect users
from the risks inherent to algorithmic governance, often carefully
designed around opaque or hidden interests (Jones, 2023; Reynolds &
Hallinan, 2024).

*This Call for Papers aims to:*
• Explore epistemological transformations in the conceptualisation of 
audiences
• Analyse emerging journalistic and communicative practices within
algorithmic logics
• Examine the democratic, ethical, and regulatory implications of
algorithm-mediated personalisation
• Propose innovative methodologies for investigating hyper-segmented
and opaque audiences
• Foster interdisciplinary dialogue bridging political communication,
digital sociology, platform economics, and critical theory

*Proposed Topics:*
• Political audiences and datafication
• Automated journalism and personalized news delivery
• Algorithmic biases and polarisation
• Algorithmic transparency and accountability
• Ideological segmentation and targeting strategies
• Civic participation in automated media environments
• Ethics, privacy, and data governance
• New forms of audience agency and performativity
• Youth audiences and platform culture
• Regional and comparative case studies
• Content automation
• Ethical and privacy implications of datafication
• The role of journalism in algorithmic communication
• Risks and opportunities of hyper-personalization
• Transformation of media consumption habits
• Informational plurality
• Echo chambers and information bubbles
• Polarisation and algorithmic bias
• Impact of algorithms on agenda setting
• Transformation of media power
• Trust in sources of algorithmic information
• Disinformation and fake news
• Transparency and regulatory mechanisms
• Audiences and engagement
• Media literacy
• New audiences and youth audiences
• Astroturfing campaigns

*Important Dates*
Deadline for submitting articles: from January 22 to April 30, 2026
Publication period: continuous edition (September to December 2026)

*About the journal*
Media & Journalism [Media & Jornalismo] (RMJ)
<https://impactum-journals.uc.pt/mj> s a NOVA Institute of
Communication publication of the NOVA University of Lisbon, published
by Coimbra  University Press, and funded by the Foundation for Science
and Technology (FCT). The journal has a rigorous scientific
arbitration system. It is indexed in different platforms and databases
of scientific journals, both nationally and internationally, like WoS,
SCOPUS, EBSCO – Academic Search Premier, DOAJ – Directory of Open
Access Journals, Elektronischen Zeitschriftenbibliothek, SciELO. Since
2024 it has been published continuously (online-first).
Each paper is sent to two reviewers, who are invited in advance to
evaluate it based on the criteria of quality, originality, and
relevance in line with the aim and theme of the specific issue of the
journal.
Articles can be submitted in English, Spanish, and Portuguese.

*Submission Instructions*
Manuscripts must be submitted through the journal’s website
(https://impactum-journals.uc.pt/mj). Once accessing RMJ for the first
time, registration is required to submit the article and track the
editorial process. We recommend reviewing the Author Guidelines,
Submission Conditions, and the journal's Editorial Policy.

The authors do not need to pay any article-processing charge (APC)
If you have questions, please contact the assistant editorial:
Patrícia Contreiras (patriciacontreiras /at/ fcsh.unl.pt)
<malito:(patriciacontreiras / at / fcsh.unl.pt)

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