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Social media platforms have increasingly become an important way for news organizations to distribute content to their audiences. As news organizations relinquish control over distribution, they may feel the need to optimize their content to align with platform logics to ensure economic sustainability. However, the opaque and often proprietary nature of platform algorithms makes it hard for news organizations to truly know what kinds of content are preferred and will perform well. Invoking the concept of algorithmic ‘folk theories,’ this article presents a study of in-depth, semi-structured interviews with 18 U.S.-based news journalists and editors to understand how they make sense of social media algorithms, and to what extent this influences editorial decision making. Our findings suggest that while journalists’ understandings of platform algorithms create new considerations for gatekeeping practices, the extent to which it influences those practices is often negotiated against traditional journalistic conceptions of newsworthiness and journalistic autonomy.
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Datavoidant: An AI System for Addressing Data Voids on Social Media
The limited information (data voids) on political topics relevant to underrepresented communities has facilitated the spread of disinformation. Independent journalists who combat disinformation in underrepresented communities have reported feeling overwhelmed because they lack the tools necessary to make sense of the information they monitor to address the data voids. In this paper, we present a system to identify and address political data voids within underrepresented communities. Armed with an interview study indicating that independent news media has the potential of addressing these data voids, we designed the intelligent system: Datavoidant. Datavoidant introduces a novel design space that focuses on providing independent journalists with a collective understanding of data voids to then facilitate generating content to cover the voids. We performed a user interface evaluation with independent news media journalists (N=22). Journalists reported that Datavoidant's features allowed them to more rapidly and easily have a sense of what was taking place in the information ecosystem to address the data voids; they also reported feeling more confident about the content they created and the unique perspectives they proposed to cover the voids. We finish by discussing how Datavoidant enables a new design space where individuals can collaboratively make sense of their information ecosystem, and can proactively devise strategies for uniquely contributing information to their ecosystem, and together prevent disinformation.
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- Award ID(s):
- 2203212
- PAR ID:
- 10344073
- Date Published:
- Journal Name:
- Computer supported cooperative work CSCW
- ISSN:
- 1573-7551
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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