scholarly journals The Soap Box as a Black Box: Regulating Transparency in Social Media Recommender Systems

2020 ◽  
Author(s):  
Paddy Leerssen
Keyword(s):  
Social Media ◽  
Recommender Systems ◽  
Black Box

scholarly journals The Soap Box as a Black Box: Regulating transparency in social media recommender systems

2020 ◽  
Author(s):  
Paddy Leerssen
Keyword(s):  
Social Media ◽  
Open Access ◽  
Recommender Systems ◽  
Final Section ◽  
Black Box ◽  
Added Value ◽  
Law And Technology ◽  
Disclosure Rules ◽  
Public Disclosures ◽  
Government Auditing

NOW AVAILABLE IN OPEN ACCESS AT THE EUROPEAN JOURNAL OF LAW AND TECHNOLOGY: https://ejlt.org/index.php/ejlt/article/view/786 Social media recommender systems play a central role in determining what content is seen online, and what remains hidden. As a point of control for media governance, they are subject to intense controversy and, increasingly, regulation by European policymakers. A recurring theme in such efforts is transparency, but this is an ambiguous concept that can be implemented in various ways depending on the types of accountability one envisages. This paper maps and critiques the various efforts at regulating social media recommendation transparency in Europe, and the types of accountability they pursue. This paper identifies three different categories of disclosure rules in recent policymaking: (1) user-facing disclaimers, (2) government auditing and (3) data-sharing partnerships with academia and civil society. Despite their limitations and pitfalls, it is argued, each of these approaches has a potential added value for media governance as part of a tiered, variegated landscape of transparency rules. However, an important element is missing: public disclosures. Given the deeply political and value-laden context of media governance, it is argued, this field cannot rely exclusively on technocratic, institutionalized forms of transparency emphasized in current proposals. The final section articulates the distinct benefits of public disclosures as a supplement to existing transparency measures, and suggests starting points for their design and regulation.

scholarly journals Mining Semantic Knowledge Graphs to Add Explainability to Black Box Recommender Systems

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 110563-110579 ◽  
Author(s):  
Mohammed Alshammari ◽  
Olfa Nasraoui ◽  
Scott Sanders
Keyword(s):  
Recommender Systems ◽  
Semantic Knowledge ◽  
Black Box ◽  
Knowledge Graphs

New technique to alleviate the cold start problem in recommender systems using information from social media and random decision forests

2020 ◽  
Vol 536 ◽  
pp. 156-170 ◽  
Author(s):  
J. Herce-Zelaya ◽  
C. Porcel ◽  
J. Bernabé-Moreno ◽  
A. Tejeda-Lorente ◽  
E. Herrera-Viedma
Keyword(s):  
Social Media ◽  
Recommender Systems ◽  
Cold Start ◽  
New Technique ◽  
Random Decision Forests ◽  
Cold Start Problem

“Twitter, the most brilliant tough love editor you’ll ever have.” Reading and writing socially during the Twitter Fiction Festival

First Monday ◽  
2016 ◽  
Author(s):  
Joachim Vlieghe ◽  
Kelly L. Page ◽  
Kris Rutten
Keyword(s):  
Social Media ◽  
Social Experience ◽  
Social Practices ◽  
Black Box ◽  
Literary Works ◽  
Reading And Writing ◽  
Communication Practice ◽  
Secondary Sources ◽  
Media Environments

The communication practice of tweeting has fostered numerous literary experiments, like Teju Cole’s series “Small fates” and Jennifer Egan’s novel “Black box”. In late 2012, these experiments culminated in an event that focused on such literary experiments: the first Twitter Fiction Festival. In this paper, we explore how people who participated in the festival use tweeting to embrace and enact writing and reading literature as a social experience. The study includes a participant-centered inquiry based on two one-hour Twitter discussions with 14 participants from the Twitter Fiction Festival as well as analyses of their online literary works and secondary sources related to the festival. We show that festival participants self-identify based on their creative and social practices as artists rather than with traditional labels such as writer or author and are therefore drawn to social media environments.

Social Media: How One City Opens the Evidence Black Box

2016 ◽  
Vol 77 (4) ◽  
pp. 486-488 ◽  
Author(s):  
Warren Kagarise ◽  
Staci M. Zavattaro
Keyword(s):  
Social Media ◽  
Black Box

CIRCLE 2020

2020 ◽  
Vol 54 (2) ◽  
pp. 1-9
Author(s):  
Iván Cantador ◽  
Max Chevalier ◽  
Massimo Melucci ◽  
Josiane Mothe
Keyword(s):  
Social Media ◽  
Information Retrieval ◽  
Recommender Systems ◽  
Research Work ◽  
User Profiling ◽  
Joint Conference ◽  
Information Retrieval Evaluation ◽  
Wide Range

The Joint Conference of the Information Retrieval Communities in Europe (CIRCLE 2020) is the first joint conference of the French, Italian, Spanish, and Swiss information retrieval communities. Although these communities had conceived the CIRCLE conference as a meeting and networking venue, because of the COVID-19 pandemic, they had to make the conference as fully virtual event. Nonetheless, the three days of conference gathered interesting studies and research work on a wide range of topics on information retrieval, such as topic and document modelling, query and ranking refinement, information retrieval in e-government, social media, recommender systems, information retrieval evaluation, indexing and annotation, user profiling and interaction, frameworks and systems, and semantic extraction.

scholarly journals Thinking Outside the Black-Box: The Case for “Algorithmic Sovereignty” in Social Media

2020 ◽  
Vol 6 (2) ◽  
pp. 205630512091561
Author(s):  
Urbano Reviglio ◽  
Claudio Agosti
Keyword(s):  
Social Media ◽  
Critical Analysis ◽  
Black Box ◽  
Public Institutions ◽  
Data Driven ◽  
Behavioral Modification ◽  
The Third ◽  
Social Negotiation ◽  
Potential Applications

This article is an interdisciplinary critical analysis of personalization systems and the gatekeeping role of current mainstream social media. The first section presents a literature review of data-driven personalization and its challenges in social media. The second section sheds light on increasing concerns regarding algorithms’ ability to overtly persuade—and covertly manipulate—users for the sake of engagement, introducing the emergence of the exclusive ownership of behavioral modification through hyper-nudging techniques. The third section empirically analyzes users’ expectations and behaviors regarding such data-driven personalization to frame a conceptualization of users’ agency. The fourth section introduces the concept of “algorithmic sovereignty.” Current projects that aim to grant this algorithmic sovereignty highlight some potential applications. Together this novel theoretical framework and empirical applications suggest that, to preserve trust, social media should open their personalization algorithms to a social negotiation as the first step toward a more sustainable social media landscape. To decentralize the immense power of mainstream social media, guarantee a democratic oversight, and mitigate the unintended undesirable consequences of their algorithmic curation, public institutions and civil society could help in developing and researching public algorithms, fostering a collective awareness so as to eventually ensure a fair and accountable “algorithmic sovereignty.”

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