Social media analytics and business intelligence research: A systematic review |
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| Institution: | 1. Department of Industrial Engineering, Konkuk University, 120 Neungdong-ro, Gwangjin-gu, Seoul 05029, Republic of Korea;2. Future Technology Analysis Center, Korea Institute of Science and Technology Information, 66 Hoegiro, Dongdaemun-gu, Seoul, 02456, Korea;1. Institute for Informatics and Telematics (IIT) of the National Research Council of Italy (CNR), Pisa, Italy;2. ANIMA Sgr S.p.a., Corso Giuseppe Garibaldi 99, 20121 Milan, Italy;3. ALGORITMI Centre, Department of Information Systems, University of Minho, 4804-533 Guimarães, Portugal;1. Department of Industrial Engineering, Konkuk University, Seoul, Republic of Korea;2. Future Technology Analysis Center, Korea Institute of Science and Technology Information, Seoul, Republic of Korea |
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| Abstract: | 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. |
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