The social Internet of Things (SIoT) shares large amounts of data that are then processed by other Internet of Thing (IoT) devices, which results in the generation, collection, and treatment of databases to be analyzed afterwards with Big Data techniques. This paradigm has given rise to users' concerns about their privacy, particularly with regard to whether users have to use a smart handling (self-establishment and self-management) in order to correctly install the SIoT, ensuring the privacy of the SIot-generated content and data. In this context, the present study aims to identify and explore the main perspectives that define user privacy in the SIoT; our ultimate goal is to accumulate new knowledge on the adoption and use of the concept of privacy “by default” in the scientific literature. To this end, we undertake a literature review of the main contributions on the topic of privacy in SIoT and Big Data processing. Based on the results, we formulate the following five areas of application of SIoT, including 29 key points relative to the concept of privacy “by default”: (i) SIoT data collection and privacy; (ii) SIoT security; (iii) threats for SIoT devices; (iv) SIoT devices mandatory functions; and (v) SIoT and Big Data processing and analytics. In addition, we outline six research propositions and discuss six challenges for the SIoT industry. The results are theorized for the future development of research on SIoT privacy by “default” and Big Data processing.

社交物联网 (SIoT) 共享大量数据，然后由其他物联网 (IoT) 设备处理，从而生成、收集和处理数据库，然后使用大数据技术进行分析。这种范式引起了用户对其隐私的担忧，特别是关于用户是否必须使用智能处理（自我建立和自我管理）才能正确安装 SIoT，确保 SIot 生成的隐私内容和数据。在此背景下，本研究旨在确定和探索在 SIoT 中定义用户隐私的主要观点；我们的最终目标是积累关于科学文献中“默认”隐私概念的采用和使用的新知识。为此，我们对 SIoT 和大数据处理中隐私主题的主要贡献进行了文献综述。基于这些结果，我们制定了以下五个 SIoT 应用领域，包括与“默认”隐私概念相关的 29 个关键点： (i) SIoT 数据收集和隐私；(ii) SIoT 安全；(iii) SIoT 设备的威胁；(iv) SIoT 设备的强制性功能；(v) SIoT 和大数据处理和分析。此外，我们概述了六个研究命题并讨论了 SIoT 行业的六个挑战。结果为“默认”和大数据处理的 SIoT 隐私研究的未来发展提供了理论依据。包括与“默认”隐私概念相关的 29 个关键点：(i) SIoT 数据收集和隐私；(ii) SIoT 安全；(iii) SIoT 设备的威胁；(iv) SIoT 设备的强制性功能；(v) SIoT 和大数据处理和分析。此外，我们概述了六个研究命题并讨论了 SIoT 行业的六个挑战。结果为“默认”和大数据处理的 SIoT 隐私研究的未来发展提供了理论依据。包括与“默认”隐私概念相关的 29 个关键点：(i) SIoT 数据收集和隐私；(ii) SIoT 安全；(iii) SIoT 设备的威胁；(iv) SIoT 设备的强制性功能；(v) SIoT 和大数据处理和分析。此外，我们概述了六个研究命题并讨论了 SIoT 行业的六个挑战。结果为“默认”和大数据处理的 SIoT 隐私研究的未来发展提供了理论依据。