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Serendipity by Design? How to Turn from Diversity Exposure to Diversity Experience to Face Filter Bubbles in Social Media

机译:设计的偶然性?如何从多元化经历转变为多元化经历,如何面对社交媒体中的过滤器泡沫

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Personalization of online content creates filter bubbles and reinforces echo chambers. These are driven not only by natural human behaviours but also by design choices and efficiency-driven recommender systems. The traditional media policy goal of exposing citizens to diverse information to protect pluralism has not found its concrete application on social media. As the usage of social media as a news source increases, as well as personalization' sophistication and group polarization, there is a need for preventing audience fragmentation. The paper suggests serendipity as a potential design principle and, eventually, policy goal. Indeed, serendipity - considered both as a capability and a process of seeking and processing unexpected and valuable information -requires diverse information as a precondition and it causes cognitive diversity. Serendipity as a design principle might encompass fundamental phases of production and consumption of information, representing a positive freedom valuable from an epistemological, psychological and political perspective. With serendipity being both limited and cultivated in the digital environment, the research reveals a theoretical trade-off between relevance and serendipity (or unknown relevance) that might be tackled with serendipity-driven recommender systems and structural and informational nudging. Such approach could turn the media policy goal of exposing users to diverse information towards an experience of diversity that comes through an architecture for serendipity.
机译:在线内容的个性化设置会产生气泡并增强回声室。这些不仅受人类自然行为的影响,还受设计选择和效率驱动的推荐系统的影响。传统的媒体政策目标是向公民提供多样化的信息以保护多元化,但尚未在社交媒体上具体应用。随着社交媒体作为新闻来源的使用以及个性化的复杂性和群体分化的增加,需要防止受众分散。本文建议将偶然性作为潜在的设计原则,并最终将其作为政策目标。的确,偶然性-被认为是寻找和处理意想不到的有价值信息的能力和过程,它需要多种多样的信息作为前提,并且会引起认知上的多样性。偶然性是一种设计原则,可能包含信息生产和消费的基本阶段,从认识论,心理和政治角度来看,代表着宝贵的积极自由。由于偶然性在数字环境中受到了限制和培养,这项研究揭示了相关性和偶然性(或未知相关性)之间的理论折衷,可以通过偶然性驱动的推荐系统以及结构性和信息性捏合来解决。这种方法可以使媒体政策目标(使用户接触各种信息)转向通过偶然性体系结构获得的多样性体验。

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