Social business intelligence: Review and research directions

Helena Gioti, Stavros T. Ponis, Nikolaos Panayiotou

Abstract


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.


Keywords


Βig data, business intelligence, review, social business intelligence, social media

Full Text:

PDF

References


Abrahams, A.S., Jiao, J., Wang, G.A. and Fan, W.

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,

/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.

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.

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.

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

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

ACM SIGMOD International Conference

on Management of data (pp. 1049-1058). ACM.

Chan, H.K., Wang, X., Lacka, E. and Zhang, M.

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,

(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-

ISO 690

Chilhare, Y.R., Londhe, D.D. and Competiti, E.M.

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.

-306.

Dey, L., Haque, S.M., Khurdiya, A. and Shroff, G.

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/Deliverabl

es/tabid/75/ctl/Versions/mid/623/Itemid/56/De

fault.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-

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-

. 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.

-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),

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),

-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. SCIF:

Social-Corporate Data Integration

Framework. In: Proceedings of the 20th

International Database Engineering &

Applications Symposium, June 2016, pp. 328-

, 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-

Luhn, H. P. 1958. A business intelligence system.

IBM Journal of Research and Development,

,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),

-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),

-282.

Milolidakis, G., Akoumianakis, D. and Kimble, C.

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.

, 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),

-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-

, 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,

-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-

Pu, J., Teng, Z., Gong, R., Wen, C. and Xu, Y.

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-

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 socialbroadcasting-

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

th 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: Stateof-

the-art, challenges, and opportunities. In

Industrial Informatics (INDIN), 2015 IEEE

th International Conference on (pp. 476-

. 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.

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.


Refbacks

  • There are currently no refbacks.

Comments on this article

View all comments
Cookies are small text files that are placed on your computer by websites that you visit. They are widely used in order to make websites work, or work more efficiently, as well as to provide information to the owners of the site.
OK!


ISIB is indexed by Web of Science (Emerging list), ESCI, SCOPUS, EBSCO, DOAJ, Google Scholar, EconBib and SCImago, and is ranked as a Level 1 publication by the Norwegian Social Science Data Services and the Finnish Publication Forum. 

 

                

 Journal Index by SCIMAGO