Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

Integrating data from user activities of social networks into public administrations

  • Published:
Information Systems Frontiers Aims and scope Submit manuscript

Abstract

Linking social networks with government applications promises various benefits, such as improving citizens’ public engagement, increasing transparency and openness in government actions, and new or enhanced government services. The research goal is to drive innovation in governments through the integration of user activities from social networks into government applications. Instead of using third-party social media tools, we call for self-developing integration software, so that the government retains full control of the sensitive government data that is linked to social network user data. Following a design science approach, we developed a data model of user activities in social networks. Our 40 user activity types conceptualize the common fundamental data structure and are a means for comparing current features of ten prominent social networks. We find that a substantial share of user activities can be mutually integrated by wrapping social network Application Programming Interfaces (APIs).

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Acker, O., Gröne, F., Akkad, F., et al. (2011). Social CRM: How companies can link into the social web of consumers. Journal of Direct, Data and Digital Marketing Practice, 13, 3–10.

    Article  Google Scholar 

  • Al-Hujran, O., Al-Debei, M. M., Chatfield, A., & Migdadi, M. (2015). The imperative of influencing citizen attitude toward e-government adoption and use. Computers in Human Behavior, 53, 189–203.

    Article  Google Scholar 

  • Archer LB (1984) Systematic method for designers. In: Cross N (ed) Developments in design methodology. Wiley, pp 57–82.

  • Atig MF, Cassel S, Kaati L, Shrestha A (2014) Activity profiles in online social media. In: IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014). pp 850–855.

  • Becker, J., Niehaves, B., Olbrich, S., & Pfeiffer, D. (2008). Forschungsmethodik einer Integrationsdisziplin - Eine Fortführung und Ergänzung zu Lutz Heinrichs “Beitrag zur Geschichte der Wirtschaftsinformatik” aus gestaltungsorientierter Perspektive. In J. Becker, H. Krcmar, & B. Niehaves (Eds.), Wissenschaftstheorie und Gestaltungsorientierte Wirtschaftsinformatik (pp. 5–26). Münster: Institut für Wirtschaftsinformatik - Westfälische Wilhelms-Universität Münster.

    Google Scholar 

  • Bertot, J. C., Jaeger, P. T., & Grimes, J. M. (2010a). Using ICTs to create a culture of transparency: E-government and social media as openness and anti-corruption tools for societies. Government Information Quarterly, 27, 264–271.

    Article  Google Scholar 

  • Bertot, J. C., Jaeger, P. T., Munson, S., & Glaisyer, T. (2010b). Social media technology and government transparency. Computer, 11, 53–59.

    Article  Google Scholar 

  • Bertot, J. C., Jaeger, P. T., & Hansen, D. (2012). The impact of polices on government social media usage: Issues, challenges, and recommendations. Government Information Quarterly, 29, 30–40.

    Article  Google Scholar 

  • Bonsón, E., Royo, S., & Ratkai, M. (2014). Citizens’ engagement on local governments'’ Facebook sites. An empirical analysis: The impact of different media and content types in Western Europe. Government Information Quarterly, 32, 52–62.

    Article  Google Scholar 

  • Bussler C (2003) Modeling Methodology. In: B2B Integration: Concepts and Architecture. Springer Berlin Heidelberg.

  • Cappuccio, S., Kulkarni, S., Sohail, M., et al. (2012). Social CRM for SMEs: Current Tools and Strategy. In V. Khachidze, T. Wang, S. Siddiqui, et al. (Eds.), Contemporary Research on E-business Technology and Strategy (pp. 422–435). Berlin Heidelberg: Springer.

    Chapter  Google Scholar 

  • Chun, S. A., & Luna Reyes, L. F. (2012). Social media in government. Government Information Quarterly, 29, 441–445.

    Article  Google Scholar 

  • Cooper, H. M. (1988). Organizing knowledge syntheses: A taxonomy of literature reviews. Knowledge in Society, 1, 104–126.

    Google Scholar 

  • Criado, J. I., Sandoval-Almazan, R., & Gil-Garcia, J. R. (2013). Government innovation through social media. Government Information Quarterly, 30, 319–326.

    Article  Google Scholar 

  • Dinter B, Lorenz A (2013) Social Business Intelligence : a Literature Review and Research Agenda. Thirty Third International Conference on Information Systems (ICIS 2012) 1–21.

  • Eekels, J., & Roozenburg, N. F. M. (1991). A methodological comparison of the structures of scientific research and engineering design: their similarities and differences. Design Studies, 12, 197–203.

    Article  Google Scholar 

  • Facebook (2015) Graph API Reference. https://developers.facebook.com/docs/graph-api. Accessed August 25, 2015.

  • Faulkner, P., & Runde, J. (2013). Technological Objects, Social Positions, Aand the tTransformational mModel of sSocial aActivity. MIS Quarterly, 37, 803–818.

    Google Scholar 

  • Fliess, S., Nadzeika, A., & Nesper, J. (2012). Understanding Patterns of Customer Engagement – How Companies Can Gain a Surplus from a Social Phenomenon. Journal of Marketing Development and Competitiveness, 6, 81–93.

    Google Scholar 

  • Gourley D, Totty B, Sayer M, et al (2002) HTTP: The Definitive Guide. O’Reilly Media, Inc.

  • Gross JL, Yellen J (2004) Handbook of Graph Theory. In: Discrete Mathematics and Its Applications. CRC Press, USA.

  • Hasselbring, W. (2000). Information system integration. Communications of the ACM, 43, 32–38.

    Article  Google Scholar 

  • Heinonen, K. (2011). Consumer activity in social media: mManagerial approaches to consumers’ social media behavior. Journal of Consumer Behaviour, 10, 356–364.

    Article  Google Scholar 

  • Hevner, A. R., March, S. T., Park, J., & Ram, S. (2004). Design Science in Information Systems Research. MIS Quarterly, 28, 75–105.

    Google Scholar 

  • Jaeger PT, Bertot JC (2010) Designing, Implementing, and Evaluating User-centered and Citizen-centered E-government. In: Citizens and E-Government. IGI Global, pp 1–19.

  • Jahn, B., & Kunz, W. (2012). How to transform consumers into fans of your brand. Journal of Service Management, 23, 344–361.

    Article  Google Scholar 

  • Janssen, K. (2011). The influence of the PSI directive on open government data: An overview of recent developments. Government Information Quarterly, 28, 446–456.

    Article  Google Scholar 

  • Janssen, M., Kuk, G., & Wagenaar, R. W. (2008). A survey of Web-based business models for e-government in the Netherlands. Government Information Quarterly, 25, 202–220.

    Article  Google Scholar 

  • Jayachandran, S., Sharma, S., Kaufman, P., & Raman, P. (2005). The role of relational information processes and technology use in customer relationship management. Journal of Marketing, 69, 177–192.

    Article  Google Scholar 

  • Kannabiran, G., Xavier, M. J., & Anantharaaj, A. (2005). Enabling E-Governance Through Citizen Relationship Management-Concept. Model and Applications. Journal of Services Research, 4(223–236), 238–240.

    Google Scholar 

  • Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of Social Media. Business Horizons, 53, 59–68.

    Article  Google Scholar 

  • Kietzmann, J. H., Hermkens, K., McCarthy, I. P., & Silvestre, B. S. (2011). Social media? Get serious! Understanding the functional building blocks of social media. Business Horizons, 54, 241–251.

    Article  Google Scholar 

  • King, S. F. (2007). Citizens as customers: eExploring the future of CRM in UK local government. Government Information Quarterly, 24, 47–63.

    Article  Google Scholar 

  • King, S., & Cotterill, S. (2007). Transformational Government? The role of information technology in delivering citizen-centric local public services. Local Government Studies, 33, 333–354.

    Article  Google Scholar 

  • Küpper T, Lehmkuhl T, Jung R, Wieneke A (2014) Features for Social CRM Technology – An Organizational Perspective. AMCIS 2014 Proceedings 1–10.

  • March, S. T., & Smith, G. F. (1995). Design and natural science research on information technology. Decision Support Systems, 15, 251–266.

    Article  Google Scholar 

  • Mergel I (2015) Social media institutionalization in the U.S. federal government.

  • Mohan S, Choi E, Min D (2008) Conceptual Modeling of Enterprise Application System Using Social Networking and Web 2.0 “Social CRM System.” 2008 International Conference on Convergence and Hybrid Information Technology 237–244.

  • Musser J, O’Reilly T (2007) Web 2.0 - Principles and Best Practices O’Reilly Media, Inc., Sebastopol, CA, USA.

  • Nunamaker, J. F., & Chen, M. (1991). Systems Development in Information Systems Research. Journal of Management Information Systems, 7, 89–106.

    Article  Google Scholar 

  • Oliveira, G. H. M., & Welch, E. W. (2013). Social media use in local government: Linkage of technology, task, and organizational context. Government Information Quarterly, 30, 397–405.

    Article  Google Scholar 

  • Österle H, Becker J, Frank U, et al (2010) Memorandum zur gestaltungsorientierten Wirtschaftsinformatik. Zeitschrift für Betriebswirtschaftliche ForschungZeitschrift für betriebswirtschaftliche Forschung 662–672.

  • Pankong N, Prakancharoen S, Buranarach M (2012) A combined semantic social network analysis framework to integrate social media data. Proceedings of the 2012 4th International Conference on Knowledge and Smart Technology, KST 2012 37–42.

  • Peffers K, Tuunanen T, Gengler CE, et al (2006) The Design Science Research Process: A Model for Producing and Presenting Information Systems Research. the Proceedings of Design Research in Information Systems and Technology DESRIST’06 24:83–106.

  • Peffers, K., Tuunanen, T., Rothenberger, M. A., & Chatterjee, S. (2007). A Design Science Research Methodology for Information Systems Research. Journal of Management Information Systems, 24, 45–77.

    Article  Google Scholar 

  • Pirolli, P., Preece, J., & Shneiderman, B. (2010). Cyberinfrastructure for Social Action on National Priorities. Computer, 43, 20–21.

    Article  Google Scholar 

  • Porter J (2010) Designing for the social web. Peachpit Press.

  • Reddik, C. G. (2010). Impact of cCitizen rRelationship mManagement (CRM) on gGovernment: eEvidence from U.S. Local Governments. Journal of E-Governance, 33, 88–99.

    Google Scholar 

  • Reinhold O, Alt R (2011) Analytical Social CRM: Concept and Tool Support. In: Proceedings 24th Bled eConference. pp 226–241.

  • Richthammer, C., Netter, M., Riesner, M., et al. (2014). Taxonomy of social network data types. EURASIP Journal on Information Security, 2014, 11.

    Article  Google Scholar 

  • Roberts A (2006) Government Secrecy in the Information Age.

  • Rosch, E., & Mervis, C. B. (1975). Family resemblances: Studies in the internal structure of categories. Cognitive Psychology, 7, 573–605.

    Article  Google Scholar 

  • Rosemann M, Eggert M, Voigt M, Beverungen D (2012) Leveraging Social Network Data for Analytical CRM Strategies - The Introductioin of Social BI.

  • Rosenberger M, Lehmkuhl T, Jung R (2015) Conceptualising and Exploring User Activities in Social Media. In: Janssen M, Mäntymäki M, Hidders J, et al. (eds) Open and Big Data Management and Innovation. Springer International Publishing, pp 107–118.

  • Rosenberger, M., Lehrer, C., & Jung, R. (2016). A System Architecture for Integrating User Activities in Social Networks with Customer Relationship Management. In V. Nissen, D. Stelzer, S. Straßburger, & D. Fischer (Eds.), Multikonferenz Wirtschaftsinformatik (MKWI) (pp. 1179–1190). Ilmenau: Universitätsverlag Ilmenau.

    Google Scholar 

  • Rossi M, Sein MK (2003) Design research workshop: a proactive research approach. In: 26th Information Systems Research Seminar in Scandinavia. The IRIS Association, Haikko Finland.

  • Sarkar A, Waxman R, Cohoon JP (1995) High-Level System Modeling. In: Bergé J-M, Levia O, Rouillard J (eds) High-Level System Modeling: Specification Languages. Springer US, pp 1–34.

  • Sarner, A., Thompson, E., Sussin, J., et al. (2012). Magic Quadrant for Social CRM. Gartner Research September, 1–20.

  • Singh, N., Lehnert, K., & Bostick, K. (2012). Global Social Media Usage : Insights Into Reaching Consumers Worldwide. Thunderbird International Business Review, 54, 683–700.

    Article  Google Scholar 

  • Sivarajah U, Irani Z, Weerakkody V (2015) Evaluating the use and impact of Web 2.0 technologies in local government.

  • Smith, T. (2009). Conference notes – The social media revolution. International Journal of Market Research, 51, 559.

    Article  Google Scholar 

  • Smith M, Shneiderman B, Milic-Frayling N, et al (2009) Analyzing (Social Media) Networks with NodeXL. In: Proceedings of the fourth international conference on Communities and technologies. ACM, pp 255–264.

  • Spagnoletti P, Resca A (2012) A Design Theory for IT Supporting Online Communities. 2012 45th Hawaii International Conference on System Sciences 4082–4091.

  • Statista (2014) Leading social networks worldwide as of June 2014, ranked by number of active users. http://www.statista.com/statistics/272014/global-social-networks-ranked-by-num-ber-of-users/. Accessed July 14, 2014.

  • Takeda, H., Veerkamp, P., Tomiyama, T., & Yoshikawam, H. (1990). Modeling Design Processes. AI Magazine, 11(4), 37–48.

    Google Scholar 

  • Trainor, K. J., Andzulis, J.(. M.)., Rapp, A., & Agnihotri, R. (2014). Social media technology usage and customer relationship performance: A capabilities-based examination of social CRM. Journal of Business Research, 67, 1201–1208.

    Article  Google Scholar 

  • Valos, M., Polonsky, M. J., Mavondo, F., & Lipscomb, J. (2015). Senior marketers’ insights into the challenges of social media implementation in large organisations: assessing generic and electronic orientation models as potential solutions. Journal of Marketing Management, 31, 713–746.

    Article  Google Scholar 

  • van der Aalst, W. M. P., Reijers, H. a., & Song, M. (2005). Discovering Social Networks from Event Logs. Computer Supported Cooperative Work (CSCW), 14, 549–593.

    Article  Google Scholar 

  • vom Brocke J, Simons A, Niehaves B, et al (2009) Reconstructing the Giant: On the Importance of Rigour in Documenting the Literature Search Process. In: 17th European Conference on Information Systems.

  • W3C Social Web Working Group (2015) Social Web Working Group (SocialWG) Home Page. http://www.w3.org/Social/WG. Accessed August 03, 2015.

  • Walls, J., Widmeyer, G., & El Sawy, O. (1992). Building an Information System Design Theory for Vigilant EIS. Information Systems Research, 3, 36–59.

    Article  Google Scholar 

  • Webster, J., & Watson, R. T. (2002). Analyzing the Past to Prepare for the Future: Writing a Literature Review. MIS Quarterly, 26, xiii–xxiii.

    Google Scholar 

  • Williams, D. S. (2014). Connected CRM: implementing a data-driven, customer-centric business strategy. New Jersey: Hoboken.

    Google Scholar 

  • Winter, R., & Baskerville, R. (2010). Methodik der WirtschaftsinformatikWirtschaftsinformatik. Wirtschaftsinformatik, 52, 257–258.

    Article  Google Scholar 

  • Woerndl W, Manhardt A, Schulze F, Prinz V (2011) Logging User Activities and Sensor Data on Mobile Devices. In: Atzmueller, M, Hotho A, Strohmaier M, Chin A (eds) Analysis of Social Media and Ubiquitous Data. Springer, pp 1–19.

  • Woodcock, N., Broomfield, N., Downer, G., & McKee, S. (2011). The evolving data architecture of social customer relationship management. Journal of Direct, Data and Digital Marketing Practice, 12, 249–266.

    Article  Google Scholar 

  • Yang, C. C., Tang, X., Dai, Q., et al. (2013). Identifying Implicit and Explicit Relationships Through User Activities in Social Media. International Journal of Electronic Commerce, 18, 73–96.

    Article  Google Scholar 

  • Yu Y, Tang S, Zimmermann R, Aizawa K (2014) Empirical Observation of User Activities. In: Proceedings of the First International Workshop on Internet-Scale Multimedia Management - WISMM ‘’14. pp 31–34.

  • Zuiderwijk A, Janssen M, Dwivedi YK (2015) Acceptance and use predictors of open data technologies: Drawing upon the unified theory of acceptance and use of technology. Government Information Quarterly.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Marcel Rosenberger.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rosenberger, M., Lehrer, C. & Jung, R. Integrating data from user activities of social networks into public administrations. Inf Syst Front 19, 253–266 (2017). https://doi.org/10.1007/s10796-016-9682-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10796-016-9682-6

Keywords