How Instagram's moderation rules are made

Harm Through the “#RizzCam”: Smart Glasses, Ambient Capture and Invisible Harassment

In online safety research, harassment is commonly understood as involving overt and unwanted acts that create a hostile environment for individuals or groups. Smart glasses, or wearable digital devices that are often indistinguishable from ordinary eyewear but can record video, audio and location data in real time, enable new forms of online harassment and gender-based harms that may not be recognised by current online safety or platform governance frameworks. Drawing on an interpretive content analysis of 350 point-of-view Instagram videos posted by individuals self-associated with the pick-up artistry (PUA) community, we examine how smart glasses can be used to harass women through what we call ambient capture. Ambient capture includes clandestine recording of people and social interactions within public, semi-private and private spaces. We argue this can constitute harassment when it is targeted at women and shared online without their consent. In our study, we found videos using ambient capture practices to harass women that had gone undetected by Instagram’s content moderation systems. These findings suggest online safety regimes and content moderation approaches should be assessed to ensure they account for the more invisible forms of harassment introduced by smart glasses and other wearable technologies.

Social Media Is Now Parasocial Media

When practitioners used the term “social media” to describe the internet tools that emerged in the mid-aughts, they were giving a name to the kinds of platforms and protocols that allowed people to socialize with friends and communities of interest by using digital technologies. Twenty years later, users of social media are far more likely to scroll than post – and the content that they consume is often strategically produced and algorithmically curated. In this essay, I argue that the very essence of social media has changed. To more effectively interrogate what we are witnessing, we need to stop presuming that these tools are “social media” and begin recognizing that they are now “parasocial media.” Doing so raises new questions about digitally mediated sociality, not to mention the politics and governance of these platforms.

Shifts in U.S. Social Media Use, 2020–2024: Decline, Fragmentation, and Enduring Polarization

The social media ecosystem appears to be in flux. Twitter’s rebranding to X has come to symbolize a broader reorganization of online publics – political reshuffling, user attrition, and uncertainty over the role of legacy platforms. Simultaneously, the shift from text-based, networked feeds toward algorithmically curated, short-form video has accelerated, with TikTok setting the pace for the wider ecosystem [18, 14, 16]. At the same time, everyday communication increasingly migrates from large, open networks to semi-private spaces such as group chats and messaging apps. Commentators describe a digital public sphere in transition: smaller, more fragmented, less dominated by traditional social networking sites, and rise of more broadcast-oriented forms of media – with some even suggesting that we are seeing the beginning of the end of the social media era.

The Future of Sex Work Slams Up Against Big Tech

As influencers peddle more sexually explicit content, Big Tech's biggest platforms—Facebook, Instagram, and Twitter—are increasing restrictions.

Towards a Post-Social Media Studies

For two decades, "social media" has been the master lens through which scholars have understood digital communication—an era defined by user-generated content, networked publics, and participatory culture. That era is drawing to a close. This paper argues that three interrelated dynamics are dissolving the social media paradigm: an algorithmic shift from social-graph-based to interest-based recommendation, which is remaking the active "user" into a passive "viewer"; the generative AI revolution, which is replacing user-generated content with synthetic media and decoupling platforms from any dependence on human participation; and an exodus from public platforms toward private, closed spaces. Together, these dynamics are giving rise to three distinct post-social formations: algorithmically governed broadcasting platforms, semi-private spheres and micro-communities, and AI-mediated communication as a new media form in its own right. Understanding this transformation demands a fundamental reorientation of the field—new conceptual tools that move beyond networked publics and participatory culture, new methods suited to synthetic and ephemeral media environments, and renewed attention to the political stakes of communication systems that no longer require human participation.

Towards a Post-Social Media Studies

For two decades, "social media" has been the master lens through which scholars have understood digital communication—an era defined by user-generated content, networked publics, and participatory culture. That era is drawing to a close. This paper argues that three interrelated dynamics are dissolving the social media paradigm: an algorithmic shift from social-graph-based to interest-based recommendation, which is remaking the active "user" into a passive "viewer"; the generative AI revolution, which is replacing user-generated content with synthetic media and decoupling platforms from any dependence on human participation; and an exodus from public platforms toward private, closed spaces. Together, these dynamics are giving rise to three distinct post-social formations: algorithmically governed broadcasting platforms, semi-private spheres and micro-communities, and AI-mediated communication as a new media form in its own right. Understanding this transformation demands a fundamental reorientation of the field—new conceptual tools that move beyond networked publics and participatory culture, new methods suited to synthetic and ephemeral media environments, and renewed attention to the political stakes of communication systems that no longer require human participation.

Custodians of the Internet

A revealing and gripping investigation into how social media platforms police what we post online—and the large societal impact of these decisions Most use...

Understanding Decentralized Social Feed Curation on Mastodon

Amid rising concerns over moderation, algorithmic control, and platform governance on centralized social media, people are increasingly turning to decentralized alternatives like Mastodon to regain control over their feeds. This shift offers new opportunities to understand how people perceive and curate their feeds. We conducted a two-part study with 21 Mastodon users: first, interviews exploring how they perceive and manage their feeds; and second, a design probe study using BRAIDS.SOCIAL, a web-based feed curation prototype informed by the first part of our initial findings. We learned how seamful design can increase people's trust in algorithmic curation, and surfaced trade-offs people navigate between machine learning-based and rule-based filtering approaches. We also identify a core design tension in decentralized platforms: whether to support personalization through new applications or extensions layered atop existing ones.

The Fediverse and Content Creation: Monetization

Sure, we have open source, federated replacements for Instagram, Tiktok, and YouTube. How do we get creators to use this stuff? One consideration involves the ability to pay for things.

Let's fund the open social web

A pro-social approach to building better platforms

The Case for a Public Social Media Platform - JSTOR Daily

Artist and writer Joshua Citarella explores why corporate platforms corrode democracy—and what a postal-service-style digital commons could do differently.

Building A Prosocial Media Ecosystem | NOEMA

There’s never been a better time to make social media what it always should have been: a tool to strengthen rather than strip-mine the social fabric.

Beyond the hashtag: Circumventing content moderation on social media

Social media companies make important decisions about what counts as “problematic” content and how they will remove it. Some choose to moderate hashtags, blocking the results for certain tag searches and issuing public service announcements (PSAs) when users search for troubling terms. The hashtag has thus become an indicator of where problematic content can be found, but this has produced limited understandings of how such content actually circulates. Using pro-eating disorder (pro-ED) communities as a case study, this article explores the practices of circumventing hashtag moderation in online pro-ED communities. It shows how (1) untagged pro-ED content can be found without using the hashtag as a search mechanism; (2) users are evading hashtag and other forms of platform policing, devising signals to identify themselves as “pro-ED”; and (3) platforms’ recommendation systems recirculate pro-ED content, revealing the limitations of hashtag logics in social media content moderation.

Community by Design

Social media empower distributed content creation by algorithmically harnessing "the social fabric" (explicit and implicit signals of association) to serve this content. While this overcomes the bottlenecks and biases of traditional gatekeepers, many believe it has unsustainably eroded the very social fabric it depends on by maximizing engagement for advertising revenue. This paper participates in open and ongoing considerations to translate social and political values and conventions, specifically social cohesion, into platform design. We propose an alternative platform model that includes the social fabric an explicit output as well as input. Citizens are members of communities defined by explicit affiliation or clusters of shared attitudes. Both have internal divisions, as citizens are members of intersecting communities, which are themselves internally diverse. Each is understood to value content that bridge (viz. achieve consensus across) and balance (viz. represent fairly) this internal diversity, consistent with the principles of the Hutchins Commission (1947). Content is labeled with social provenance, indicating for which community or citizen it is bridging or balancing. Subscription payments allow citizens and communities to increase the algorithmic weight on the content they value in the content serving algorithm. Advertisers may, with consent of citizen or community counterparties, target them in exchange for payment or increase in that party's algorithmic weight. Underserved and emerging communities and citizens are optimally subsidized/supported to develop into paying participants. Content creators and communities that curate content are rewarded for their contributions with algorithmic weight and/or revenue. We discuss applications to productivity (e.g. LinkedIn), political (e.g. X), and cultural (e.g. TikTok) platforms.