How the Platform-Creator Dyadic Relationship Reconfigures Internet Communication Power in the Boom of Generative AI Visual Media Creation

Platformed Publics: Algorithms, Affordances, and the Recomposition of Authority

Communicating Digital Creative Labour under Algorithmic Governance in Platform Economies

Purpose: On platforms like TikTok and Instagram, a creator's livelihood depends entirely on being seen. This study investigates how platform algorithms restrict digital creators through official corporate rules. We explore how tech companies use institutional communications to exert structural and symbolic power over digital content creators.   Methods: Using critical discourse analysis, we examined official platform rulebooks, including algorithm policies, community guidelines, and moderation manuals. By analyzing the specific language within these documents, we traced how corporate wording subtly dictates the power balance between platforms and creators.   Findings: Platforms strategically use passive voice, moral framing, and dense technical jargon to obscure authority while steering creator behavior. By framing visibility as both a reward and a constant risk, platforms force creators into internalized surveillance. Creators consequently mold their content and personalities to fit underlying algorithmic logic.   Originality: Previous research often treats algorithms as opaque technical black boxes, frequently and completely overlooking the institutional texts mediating this control. This study fills that gap by introducing linguistic algorithmic governmentality. We demonstrate that platform guidelines are disciplinary technologies translating cold code into behavioral norms. Theoretically, this extends Foucaultian governmentality and the critical political economy of communication into the platform era. It proves digital power is enforced through strategic corporate language, reshaping how we understand digital subjectivity and creative labor governance within contemporary digital media ecosystems.

Cross-cultural Communication Mechanisms and Cultural Meaning-Making on Digital Platforms

What happens to the cultural connotations of songs, gestures, jokes, political symbols, etc., when they leave their original contexts of production and spread across digital platforms? Most existing studies have addressed only part of this problem. Research on representation examines the construction of cultural difference; research on participation traces users' remixing and discussion of content; platform studies explains how data, ranking and governance structure visibility. Treating these processes as independent, however, cannot explain the changes that occur during circulation. This conceptual paper proposes a trajectory-based framework linking three dimensions of platform-mediated meaning-making: the representation and translation of cultural materials, their participatory and affective recirculation, and the infrastructural allocation of attention. The framework is recursive rather than sequential. Translation invites responses; those responses generate signals for recommendation systems; the resulting pattern of visibility affects subsequent translations and representations. This framework can explain why the same circulation can produce creative hybridity and mutual recognition while also enabling decontextualisation, appropriation and unequal interpretive authority. The article puts forward analytical questions for tracing who determines the "legibility" of culture, whose interpretations spread, and how platforms reinforce certain meanings while marginalising others. It presents comparative and longitudinal research designs that can test these relationships across multiple languages, communities and platform environments.

Behind the “AI slop”: exploring the AI-generated viral short video production in China

This study shows AI enables a cohort of “Internet entrepreneurs” to enter cultural production, driven by a “money hustling culture” that encourages formerly idle and low-skilled individuals to pursue rapid monetisation.

From digital ecosystems to intelligent maturity: how AI tools reshape the form and content of digital communication

The integration of artificial intelligence (AI) tools into the communication industry is reshaping how messages are formed, distributed, and understood. Moving beyond earlier claims of digital transformation, this paper argues that the industry is now entering a phase of intelligence maturity, where AI systems increasingly mediate both the channels and content of communication. Based on a structured literature review of 85 peer-reviewed sources published between 2020 and 2026, the analysis shows that AI has shifted from a tactical support tool to a strategic actor within socio-technical systems. In content creation, generative AI has lowered production barriers, enabled personalization at scale, and challenged traditional notions of authorship and authenticity. At the same time, these developments raise socio-ethical concerns, including a widening AI divide, algorithmic bias, and the spread of synthetic media. Rather than replacing human roles, the paper finds that the industry is moving toward a co-intelligence model, where AI handles computationally intensive tasks and humans retain strategic direction, ethical oversight, and cultural judgment. The paper contributes a systematic conceptualization of co-intelligence that distinguishes it from existing constructs such as hybrid intelligence, intelligence augmentation, and human-in-the-loop systems by specifying its organizational and governance dimensions. Successful co-intelligence depends on leadership, data culture, and governance frameworks. The paper therefore conceptualizes co-intelligence as the combination of AI's analytical capacity with human empathy, ethics, and strategic insight.

Trust the messenger, then the message: unpacking the cross-route logic of danmaku engagement

Contemporary video repositories increasingly overlay real-time, user-generated metadata in the form of danmaku (bullet comments) onto linear content, creating a complex retrieval environment defined by the tension between collaborative sensemaking and cognitive overload. This study examines this human information interaction dynamic, analyzing how observable creator-related source cues, Content value (CV) signals and peer feedback are associated with engagement within information-dense streams. Leveraging large-scale behavioral trace data from 261 informational videos and over 130,000 time-anchored comments on Bilibili, the study employs a multi-method approach combining partial least squares structural equation modeling, partial least squares multi-group analysis and BERTopic modeling to triangulate structural engagement associations with semantic discourse patterns. The analysis identifies association patterns consistent with a sequential cross-route account in which peripheral source cues function as heuristic filters that are linked to CV signals and subsequent feedback interaction. Crucially, this pattern is context-contingent: high-efficacy information environments show stronger content-oriented engagement, whereas low-efficacy contexts show stronger associations with peripheral source heuristics and social signals. The research refines dual-process theories within digital information management by specifying a measurable, sequential association pattern for observable engagement under information density. It distinguishes Audience Conversion Efficacy as a critical moderator, offering evidence-based strategies for adaptive interface design that align information presentation with content utility.