Evidently, online voice of customers (VoC) expressed in social media has emerged as quality data for researchers who are willing to conduct customer-driven business intelligence (BI) research. Nevertheless, to the best of authors’ knowledge, there is still a dearth of studies that deal with such remarkable research stream and address various open data (e.g., social media, intellectual property) from a BI research perspective. Therefore, this study has attempted to evaluate the applicability of social media data in BI research and provide a systematic review on the primary research articles in the domain. This study compared social media data with the other open data (e.g., gray literature, public government data) in terms of data content, collection, updatability and structure, which are determined through a thorough discussion with experts. Next, this study selected 57 social media-based BI research articles from the Web of Science (WoS) database and analyzed them with three research questions about the data, methodologies, and results to understand this research domain. Our findings are expected to inform the existing researchers in the research domain about the future research directions, enable newcomers to understand the overall process of analyzing social media data, and provide the practitioners with social media analysis approaches suitable for their environment.

显然，社交媒体上表达的客户在线声音（VoC）已经成为愿意进行客户驱动的商业智能（BI）研究的研究人员的高质量数据。然而，据作者所知，仍然缺乏用于处理如此出色的研究流并从BI研究角度解决各种开放数据（例如社交媒体，知识产权）的研究。因此，本研究试图评估社交媒体数据在BI研究中的适用性，并对该领域的主要研究文章进行系统的综述。这项研究将社交媒体数据与其他开放数据（例如灰色文献，公共政府数据）在数据内容，收集，可更新性和结构方面进行了比较，这些数据是通过与专家进行全面讨论而确定的。下一个，这项研究从Web of Science（WoS）数据库中选择了57篇基于社交媒体的BI研究文章，并对它们进行了有关数据，方法和结果的三个研究问题的分析，以了解该研究领域。预期我们的发现将使研究领域的现有研究人员了解未来的研究方向，使新手能够了解分析社交媒体数据的总体过程，并为从业人员提供适合其环境的社交媒体分析方法。