Social business intelligence: Review and research directions
DOI:
https://doi.org/10.37380/jisib.v8i2.320Keywords:
Βig data, business intelligence, review, social business intelligence, social mediaAbstract
Social business intelligence (SBI) is a rather novel discipline, emerged in the academic and business literature as a result of the convergence of two distinct research domains: business intelligence (BI) and social media. Traditional BI scientists and practitioners, after an inevitable initial shock, are currently discovering and acknowledge the potential of user generated content (UGD) published in social media as an invaluable and inexhaustible source of information capable of supporting a wide range of business activities. The confluence of these two emerging domains is already producing new added value organizational processes and enhanced business capabilities utilized by companies all over the world to effectively harness social media data and analyze them in order to produce added value information such as customer profiles and demographics, search habits, and social behaviors. Currently the SBI domain is largely uncharted, characterized by controversial definitions of terms and concepts, fragmented and isolated research efforts, obstacles created by proprietary data, systems and technologies that are not mature yet. This paper aspires to be one of the few -to our knowledge- contemporary efforts to explore the SBI scientific field, clarify definitions and concepts, structure the documented research efforts in the area and finally formulate an agenda of future research based on the identification of current research shortcomings and limitations.
References
Abrahams, A.S., Jiao, J., Wang, G.A. and Fan, W. 2012. Vehicle defect discovery from social media. Decision Support Systems, 54(1), 87-97.
Arora, D., Li, K.F. and Neville, S.W. 2015. Consumers' sentiment analysis of popular phone brands and operating system preference using Twitter data: A feasibility study. In: Proceedings of Advanced Information Networking and Applications (AINA) IEEE 29th International Conference, pp. 680-686.
Bachmann, P. and Kantorová, K. 2016. From customer orientation to social CRM. New insights from Central Europe. Scientific papers of the University of Pardubice, Series D, Faculty of Economics and Administration, 36/2016.
Banerjee, S. and Agarwal, N. 2012. Analyzing collective behavior from blogs using swarm intelligence. Knowledge and Information Systems, 33(3), 523-547.
Basset, H., Stuart, D. and Silbe, D. 2012. From Science 2.0 to Pharma 3.0 Semantic Search and Social Media in the Pharmaceutical Industry and Stm Publishing. A volume in Chandos Publishing Social Media Series.
Baur, A., Lipenkova, J., Bühler, J. and Bick, M. 2015. A Novel Design Science Approach for Integrating Chinese User-Generated Content in Non-Chinese Market Intelligence.
Baur, A.W. (016. Harnessing the social web to enhance insights into people’s opinions in business, government and public administration. Information Systems Frontiers, pp.1-21.
Beigi, G., Hu, X., Maciejewski, R. and Liu, H. 2016. An overview of sentiment analysis in social media and its applications in disaster relief. Sentiment Analysis and Ontology Engineering, pp. 313-340, Springer International Publishing.
Bell, D. and Shirzad, S. R. 2013. Social media business intelligence: A pharmaceutical domain analysis study. International Journal of Sociotechnology and Knowledge Development (IJSKD), 5(3), pp. 51-73.
Bell, D. and Shirzad, S.R. 2013. Social Media Domain Analysis (SoMeDoA)-A Pharmaceutical Study. WEBIST, pp. 561-570.
Bendler, J., Ratku, A. and Neumann, D. 2014. Crime mapping through geo-spatial social media activity. In: Proceedings of 35th International Conference on Information Systems, Auckland 2014.
Berlanga, R., Aramburu, M.J., Llidó, D.M. and García-Moya, L. 2014. Towards a semantic data infrastructure for social business intelligence. New Trends in Databases and Information Systems, pp. 319-327, Springer International Publishing.
Berlanga, R., García-Moya, L., Nebot, V., Aramburu, M.J., Sanz, I. and Llidó, D.M. 2016. Slod-bi: An open data infrastructure for enabling social business intelligence. Big Data: Concepts, Methodologies, Tools, and Applications, pp. 1784-1813, IGI Global.
Beverungen, D., Eggert, M., Voigt, M. and Rosemann, M. 2014. Augmenting Analytical CRM Strategies with Social BI. Digital Arts and Entertainment: Concepts, Methodologies, Tools, and Applications, pp. 558-576, IGI Global.
Bjurstrom, S. and Plachkinova, M. 2015. Sentiment Analysis Methodology for Social Web Intelligence.
Bygstad, B. and Presthus, W. 2013. Social Media as CRM? How two airline companies used Facebook during the “Ash Crisis” in 2010. Scandinavian Journal of Information Systems, 25(1), 3.
Castellanos, M., Dayal, U., Hsu, M., Ghosh, R., Dekhil, M., Lu, Y., ... & Schreiman, M. 2011. LCI: a social channel analysis platform for live customer intelligence. In Proceedings of the 2011 ACM SIGMOD International Conference on Management of data (pp. 1049-1058). ACM.
Chan, H.K., Wang, X., Lacka, E. and Zhang, M. 2015. A Mixed-Method Approach to Extracting the Value of Social Media Data. Production and Operations Management.
Chaudhuri, S., Dayal, U. and Narasayya, V. 2011. An overview of business intelligence technology. Communications of the ACM, 54(8), 88-98.
Chen, H., Chiang, R.H. and Storey, V.C. 2012. Business intelligence and analytics: From big data to big impact. MIS quarterly, 36(4), 1165-1188. ISO 690
Chilhare, Y.R., Londhe, D.D. and Competiti, E.M. 2016. Competitive Analytics Framework on Bilingual Da Bilingual Dataset of Amazon Food Product. IJCTA, 9(21), pp. 179-189.
Chung, W., Zeng, D. and O'Hanlon, N. 2014. Identifying influential users in social media: A study of US immigration reform. In: Proceedings of the 20th Americas Conference on Information Systems, Savannah, 2014.
Colombo, C., Grech, J.P. and Pace, G.J. 2015. A controlled natural language for business intelligence monitoring. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9103, pp. 300-306.
Dey, L., Haque, S.M., Khurdiya, A. and Shroff, G. 2011. Acquiring competitive intelligence from social media. In: Proceedings of the 2011 joint workshop on multilingual OCR and analytics for noisy unstructured text data, p. 3. ACM.
Diamantopoulou, V., Charalabidis, Y., Loukis, E., Triantafillou, A., Sebou, G. Foley, P., Deluca, A., Wiseman, I. and Koutzeris, T. 2010. Categorization of Web 2.0 Social Media and Stakeholder Characteristics. Nomad Project. EU. pp.19. Available at: http://www.padgets.eu/Downloads/Deliverables/tabid/75/ctl/Versions/mid/623/Itemid/56/Default.aspx [Accessed 2 March 2017]
Dinter, B. and Lorenz, A. 2012. Social business intelligence: a literature review and research agenda. In: Proceedings of the 33rd International Conference on Information Systems, Orlando 2012.
Fan, S., Lau, R.Y. and Zhao, J.L. 2015. Demystifying big data analytics for business intelligence through the lens of marketing mix. Big Data Research, 2(1), 28-32.
Ferrara, E., De Meo, P., Fiumara, G. and Baumgartner, R. 2014. Web data extraction, applications and techniques: A survey. Knowledge-Based Systems, 70, 301-323.
Fourati-Jamoussi, F. 2015. E-reputation: A case study of organic cosmetics in social media. In: Proceedings of the Information Systems and Economic Intelligence (SIIE) 6th International Conference, pp. 125-132, IEEE.
Gallinucci, E., Golfarelli, M. and Rizzi, S. 2013. Meta-stars: multidimensional modeling for social business intelligence. In: Proceedings of the 16th international workshop on Data warehousing and OLAP, pp. 11-18, ACM.
Gallinucci, E., Golfarelli, M., & Rizzi, S. 2015. Advanced topic modeling for social business intelligence. Information Systems, 53, 87-106.
Golfarelli, M. 2014. Social business intelligence: OLAP applied to user generated contents. In: Proceedings of the e-Business (ICE-B) 11th
International Conference, pp. IS-11, IEEE.
Golfarelli, M. 2015. Design Issues in Social Business Intelligence Projects. In European Business Intelligence Summer School (pp. 62- 86). Springer International Publishing.
Gronroos, C. 2008. Service logic revisited: Who creates value? And who co-creates? European Business Review, Vol. 20, No. 4, pp. 298–314.
Hart C. 1998. Doing a Literature Review. Sage Publications, London
He, W., Tian, X., Chen, Y. and Chong, D. 2016. Actionable social media competitive analytics for understanding customer experiences. Journal of Computer Information Systems, 56(2), 145-155.
Heijnen, J., De Reuver, M., Bouwman, H., Warnier, M. and Horlings, H. 2013. Social media data relevant for measuring key performance indicators? A content analysis approach. In: Proceedings of the International Conference on Electronic Commerce, pp. 74-84, Springer Berlin Heidelberg.
Jingjing, W., Changhong, T., Xiangwen, L. and Guolong, C. 2013. Mining Social Influence in Microblogging via Tensor Factorization Approach. In: Proceedings of Cloud Computing and Big Data (CloudCom-Asia), December 2013 International Conference, pp. 583-591, IEEE.
Kaplan, A. M. and Haenlein, M. 2010. Users of the world, unite! The challenges and opportunities of Social Media. Business horizons, 53(1), 59-68.
Keele, S. 2007. Guidelines for performing systematic literature reviews in software engineering. In Technical report, Ver. 2.3 EBSE Technical Report. EBSE.
Kim, Y. and Jeong, S. R. 2015. Opinion-Mining Methodology for Social Media Analytics. TIIS, 9(1), 391-406.
Kucher, K., Kerren, A., Paradis, C. and Sahlgren, M. 2014. Visual analysis of stance markers in online social media. In: Proceedings of Visual Analytics Science and Technology (VAST), 2014 IEEE Conference, pp. 259-260, IEEE.
Kucher, K., Schamp-Bjerede, T., Kerren, A., Paradis, C. and Sahlgren, M. 2016. Visual analysis of online social media to open up the investigation of stance phenomena. Information Visualization, 15(2), 93-116.
Kulkarni, A. V., Joseph, S., Raman, R., Bharathi, V., Goswami, A. and Kelkar, B. 2013. Blog Content and User Engagement-An Insight Using Statistical Analysis. International Journal of Engineering and Technology, 5(3),
pp. 2719-2733.
Lee, C., Wu, C., Wen, W. and Yang, H. 2013. Construction of an event ontology model using a stream mining approach on social media. In: Proceedings of the 28th International Conference on Computers and Their Applications, 2013, CATA 2013, pp.249-254.
Lin, Z. and Goh, K. Y. 2011. Measuring the business value of online social media content for marketers. In: Proceedings of the 32nd International Conference on Information Systems, Shanghai.
Liu, S., Wang, S. and Zhu, F. 2015. Structured learning from heterogeneous behavior for social identity linkage. IEEE Transactions on Knowledge and Data Engineering, 27(7), 2005-
Liu, S., Wang, S., Zhu, F., Zhang, J. and Krishnan, R. 2014. Hydra: Large-scale social identity linkage via heterogeneous behavior modeling. In: Proceedings of the 2014 ACM SIGMOD international conference on Management of data, pp. 51-62, ACM.
Liu, X. and Yang, J. 2012. Social buying met network modeling and analysis. International Journal of Services Technology and Management, 18 (1- 2), 46-60.
Lotfy, A., El Tazi, N and El Gamal, N. 2016. SCI- F: Social-Corporate Data Integration Framework. In: Proceedings of the 20th International Database Engineering & Applications Symposium, June 2016, pp. 328-333, ACM.
Lu, Y., Wang, F. and Maciejewski, R. 2014. Business intelligence from social media: A study from the vast box office challenge. IEEE computer graphics and applications, 34(5), 58-69.
Luhn, H. P. 1958. A business intelligence system. IBM Journal of Research and Development, 2,14-31
Luo, J., Pan, X. and Zhu, X. 2015. Identifying digital traces for business marketing through topic probabilistic model. Technology Analysis & Strategic Management, 27(10), 1176-1192.
Marine-Roig, E., & Clavé, S. A. 2015. Tourism analytics with massive user-generated content: A case study of Barcelona. Journal of Destination Marketing & Management, 4(3), 162-172.
McKinsey and Altagamma 2015. Digital inside: Get wired for the ultimate luxury experience. Available at: https://www.mckinsey.de/files/dle-2015-global-report.pdf [Accessed 5 March 2017]
Meredith, R. and O'Donnell, P. A. 2010. A Functional Model of Social Media and its Application to Business Intelligence. In: Proceedings of the 2010 conference on Bridging the Socio-technical Gap in Decision Support Systems: Challenges for the Next Decade, August 2010, pp. 129-140, IOS Press, Netherlands.
Meredith, R. and O'Donnell, P. A. 2011. A framework for understanding the role of social media in business intelligence systems. Journal of Decision Systems, 20(3), 263-282.
Milolidakis, G., Akoumianakis, D. and Kimble, C. 2014. Digital traces for business intelligence: A case study of mobile telecoms service brands in Greece. Journal of Enterprise Information Management, 27(1), 66-98.
Moedeen, B. W. and Jeerooburkhan, A.S. 2016. Evaluating the strategic role of Social Media Analytics to gain business intelligence in Higher Education Institutions. In: Proceedings of Emerging Technologies and Innovative Business Practices for the Transformation of Societies (EmergiTech), IEEE International Conference, pp. 303-308.
Ngo-Ye, T. L. and Sinha, A.P. 2012. Analyzing online review helpfulness using a regressional ReliefF-enhanced text mining method. ACM Transactions on Management Information Systems (TMIS), 3(2), 10.
Nithya, R. and Maheswari, D. 2016. Correlation of feature score to overall sentiment score for identifying the promising features. In: Proceedings of Computer Communication and Informatics (ICCCI) International Conference, January 2016, pp. 1-5, IEEE.
O'Leary, D. E. 2015. Twitter Mining for Discovery, Prediction and Causality: Applications and Methodologies. Intelligent Systems in Accounting, Finance and Management, 22(3), 227-247.
Obradović, D., Baumann, S. and Dengel, A. 2013. A social network analysis and mining methodology for the monitoring of specific domains in the blogosphere. Social Network Analysis and Mining, 3(2), 221-232.
Olszak, C.M. 2016. Toward better understanding and use of Business Intelligence in organizations. Information Systems Management, 33(2), 105-123.
Palacios-Marqués, D., Merigó, J. M. and Soto- Acosta, P. 2015. Online social networks as an enabler of innovation in organizations. Management Decision, 53(9), 1906-1920.
Petychakis, M., Biliri, E., Arvanitakis, A., Michalitsi-Psarrou, A., Kokkinakos, P., Lampathaki, F. and Askounis, D. 2016. Detecting Influencing Behaviour for Product- Service Design through Big Data Intelligence in Manufacturing. In: Proceedings of Working Conference on Virtual Enterprises, pp. 361- 369, Springer International Publishing.
Piccialli, F. and Jung, J. E. 2016. Understanding Customer Experience Diffusion on Social Networking Services by Big Data Analytics. Mobile Networks and Applications, 1-8.
Ponis, S. T., & Christou, I. T. 2013. Competitive intelligence for SMEs: a web-based decision support system. International Journal of Business Information Systems, 12(3), 243-258.
Pu, J., Teng, Z., Gong, R., Wen, C. and Xu, Y. 2016. Sci-Fin: Visual Mining Spatial and Temporal Behavior Features from Social Media. Sensors, 16(12), 2194.
Qazi, A., Raj, R.G., Tahir, M., Cambria, E. and Syed, K.B.S. 2014. Enhancing business intelligence by means of suggestive reviews. The Scientific World Journal, 2014.
Ram, J., Zhang, C. and Koronios, A. 2016. The Implications of Big Data Analytics on Business Intelligence: A Qualitative Study in China. Procedia Computer Science, 87, 221-226.
Ranjan, J. 2009. Business intelligence: Concepts, components, techniques and benefits. Journal of Theoretical and Applied Information Technology, 9(1), 60-70.
Ranjan, R., Vyas, D. and Guntoju, D. P. 2014. Balancing the trade-off between privacy and profitability in Social Media using NMSANT. In: Proceedings of Advance Computing Conference (IACC), 2014 IEEE International, pp. 477-483, IEEE.
Rosemann, M., Eggert, M., Voigt, M. and Beverungen, D. 2012. Leveraging social network data for analytical CRM strategies: the introduction of social BI. In: Proceedings of the 20th European Conference on Information Systems (ECIS) 2012, AIS Electronic Library (AISeL).
Ruhi, U. 2014. Social Media Analytics as a business intelligence practice: current landscape & future prospects. Journal of Internet Social Networking & Virtual Communities, 2014.
Rui, H., & Whinston, A. 2011. Designing a social- broadcasting-based business intelligence system. ACM Transactions on Management Information Systems (TMIS), 2(4), 22.
Sathyanarayana, P., Tran, P.N.K., Meredith, R. and O'Donnell, P. A. 2012. Towards a Protocol to Measure the Social Media Affordances of Web Sites and Business Intelligence Systems. DSS, pp. 317-322.
Seebach, C., Beck, R. and Denisova, O. 2012. Sensing Social Media for Corporate Reputation Management: a Business Agility Perspective. ECIS, p. 140.
Shroff, G., Agarwal, P. and Dey, L. 2011. Enterprise information fusion for real-time business intelligence. In: Proceedings of the 14th International Conference, Information Fusion (FUSION), pp. 1-8, IEEE.
Sigman, B. P., Garr, W., Pongsajapan, R., Selvanadin, M., McWilliams, M. and Bolling, K. 2016. Visualization of Twitter Data in the Classroom. Decision Sciences Journal of Innovative Education, 14(4), 362-381.
Sijtsma, B., Qvarfordt, P. and Chen, F. 2016. Tweetviz: Visualizing Tweets for Business Intelligence. In: Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval, July 2016, pp. 1153-1156, ACM.
Sleem-Amer, M., Bigorgne, I., Brizard, S., Dos Santos, L.D.P., El Bouhairi, Y., Goujon, B. and Varga, L. 2012. Intelligent semantic search engines for opinion and sentiment mining. Next Generation Search Engines: Advanced Models for Information Retrieval, pp. 191-215, IGI Global.
Tayouri, D. 2015. The Human Factor in the Social Media Security–Combining Education and Technology to Reduce Social Engineering Risks and Damages. Procedia Manufacturing, 3, 1096-1100.
Tziralis, G., Vagenas, G., & Ponis, S. 2009. Prediction markets, an emerging Web 2.0 business model: towards the competitive intelligent enterprise. In Web 2.0 (pp. 1-21). Springer, Boston, MA.
Wen, C., Teng, Z., Chen, J., Wu, Y., Gong, R. and Pu, J. 2016. socialRadius: Visual Exploration of User Check-in Behavior Based on Social Media Data. In: Proceedings of the International Conference on Cooperative Design, October 2016, Visualization and Engineering, pp. 300-308, Springer International Publishing.
Wongthongtham, P., & Abu-Salih, B. 2015. Ontology and trust based data warehouse in new generation of business intelligence: State- of-the-art, challenges, and opportunities. In Industrial Informatics (INDIN), 2015 IEEE 13th International Conference on (pp. 476- 483). IEEE.
Wu, Y., Liu, S., Yan, K., Liu, M. and Wu, F. 2014. Opinionflow: Visual analysis of opinion diffusion on social media. IEEE Transactions on Visualization and Computer Graphics, 20(12), 1763-1772.
Yang, C. S. and Shih, H. P. 2012. A Rule-Based Approach for Effective Sentiment Analysis. PACIS, p. 181).
Yang, C.S. and Chang, P.C. 2015. Mining Social Media for Enhancing Personalized Document Clustering. In: Proceedings of the International Conference on HCI in Business, pp. 185-196, Springer International Publishing.
Yang, C.S. and Chen, L.C. 2014. Personalized Recommendation in Social Media: a Profile Expansion Approach. PACIS, p. 68.
Zeng, D., Chen, H., Lusch, R. and Li, S.H. 2010. Social media analytics and intelligence. IEEE Intelligent Systems, 25(6), 13-16.
Zhang, Z., Guo, C. and Goes, P. 2013. Product comparison networks for competitive analysis of online word-of-mouth. ACM Transactions on Management Information Systems (TMIS), 3(4), 20.
Zhang, Z., Li, X. and Chen, Y. 2012. Deciphering word-of-mouth in social media: Text-based metrics of consumer reviews. ACM Transactions on Management Information Systems (TMIS), 3(1), 5.
Zimmerman, C., & Vatrapu, R. 2015. The Social Newsroom: Visual Analytics for Social Business Intelligence. In: Proceedings of the International Conference on Design Science Research in Information Systems, pp. 386-390, Springer International Publishing.
Zimmerman, C.J., Wessels, H.T. and Vatrapu, R. 2015. Building a social newsroom: Visual analytics for social business intelligence. In: Proceedings of the IEEE 19th International Conference, Enterprise Distributed Object Computing Workshop (EDOCW), pp. 160-163, IEEE.
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