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Abstract The ever-growing influence of recommendation algorithms has positioned media platforms as potent guiders of information, raising pertinent discussions on the ethical dimensions of algorithmic recommendation technology. A pressing concern in contemporary academic research is aiding media corporations to uphold their social responsibility and scrutinize the new ethical dilemmas arising from emerging technologies. This study employs affordance theory and media social responsibility theory to examine the influence of affordance as the independent variables, perceived value as the mediating variable, and Chinese cultural perception as the moderating variable on users’ perception of media social responsibility when engaging with recommendation algorithms, based on a questionnaire survey and regression data analysis.
The study reveals that under the mediating effect of perceived value, a higher users’ perception of content and algorithm affordance from algorithmic recommendations results in a more favorable perception of media’s fulfillment of social responsibility. The most significant affected aspect is brand image responsibility, followed by positive guidance and network environment responsibility. Content affordance impacts users’ perception of media social responsibility more profoundly than algorithm affordance. Among these, the integrity of content affordance and the accountability of algorithm affordance have the most significant impact, while the transparency of algorithm affordance plays a negligible role. Chinese cultural perception can effectively moderate users’ perception of media brand image and network environment responsibility, but it fails to simulate positive guidance responsibility directly.
Firstly, this study introduces a technology-driven model for perceiving media social responsibility from the user’s perspective, anchored in affordance theory. In the era of algorithmic recommendations, media gatekeeping power, concealed by algorithms, strays and yet finds its way back to rationality. As developers and managers of algorithms, media entities must not only abide by traditional norms, including authenticity, integrity, and continuity, but they must also address new ethical issues arising from emerging technologies, such as novelty, diversity, fairness, and accountability. Considering the various dimensions of affordance can provide focused guidance for the implementation of media social responsibility.
Secondly, algorithm affordance primarily impacts how users perceive media social responsibility in relation to accountability and fairness, rather than being influenced by the degree of transparency. Users are particularly concerned about the algorithm’s responsibility mechanisms, its ability to be held accountable for potential negative consequences of the technology, including the negative impact of pushed content and arising ethical issues. Accuracy and fairness also draw significant attention; users expect the algorithm to be unbiased, non-discriminatory, and precisely reasonable while arranging content. The issue of transparency, as perceived by users, can be redirected towards enhancing algorithmic logic. When users gain an understanding of how algorithmic recommendation systems operate, their demand for transparency tends to diminish.
Thirdly, this paper uncovers a potential mechanism within Chinese culture that enhances users’ positive perception of media fulfilling its social responsibility. Instead of solely focusing on promoting Chinese culture for political obedience and public responsibility, media entities should recognize that Chinese culture provides an essential nourishment for constructing a robust brand image and fostering a positive and healthy online community. Media content management should transition from solely prioritizing commercial value and profits to actively recognizing the corporate utility and social value offered by Chinese culture, thus advocating a proactive approach towards change.
Finally, the mechanisms by which content affordance and algorithm affordance impact users’ perception of media social responsibility differ. This paper addresses two key concerns. First, the media’s algorithmic logic should prioritize providing high-quality content to users rather than merely chasing traffic. Second, in an era of superficial reading, integrating the cultural superiority of past elite content production models and guiding users towards deeper cultural engagement pose a fresh challenge for the study of media social responsibility.
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Published: 18 August 2023
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