Abstract
There is a growing need for, often non-technical, organisations to analyse valuable information stored within often separate social networking systems (SNSs). Open architectures provide programmatic access to most SNSs permitting the creation of applications which may leverage information, for example statistics regarding the impact of marketing campaigns or new product or service announcements. This type of information is necessary for the development of sound evidence based social media strategies. Software products are available which provide this type of information, though for organisations to be able to tailor these to their specific needs, solutions are often very expensive. One solution would be for organisations to have the facility to build their own systems. This paper describes a research programme that will investigate developing, amending or extending a modelling notation, capable of being used by non-technical people for the development of systems to extract and analyse social networking data.
Chapter PDF
Similar content being viewed by others
References
Boyd, D.M., Ellison, N.B.: Social Network Sites: Definition, History, and Scholarship. Journal of Computer-Mediated Communication 13(1), 210–230 (2007), http://onlinelibrary.wiley.com/doi/10.1111/j.1083-6101.2007.00393.x/full
MPI, MPI Home (2013), http://www.mpiweb.org/Home (accessed March 11, 2013)
Hawker, M.D.: Developer’s Guide to Social Programming: Building Social Context Using Facebook, Google Friend Connect, and the Twitter API. Addison-Wesley (2010)
The Brick Factory, ImpactWatch, Impact Watch: monitoring made simple, The Brick Factory (2012), http://www.impactwatch.com/ (accessed June 25, 2012)
Perez, S.: Facebook Wins “Worst API”, Techcrunch (2011), http://techcrunch.com/2011/08/11/facebook-wins-worst-api-in-developer-survey/ (accessed June 25, 2012)
Grant, M.: 76% of Companies Do Not Have a Social Media Policy. Social Business News (2012), http://www.socialbusinessnews.com/76-of-companies-do-not-have-a-social-media-policy/ (accessed January 25, 2013)
Petre, M.: Why looking isn’t always seeing. Communications of the ACM 38(6), 33–44 (1995), http://rtsys.informatik.uni-kiel.de/teaching/ws03-04/s-synth/papers/p33-petre.pdf (accessed January 28, 2013)
Groenniger, H., et al.: Text-based Modeling. In: Proceedings of the 4th International Workshop on Software Language Engineering, Nashville, TN, USA, Johannes-Gutenberg-Universitat Mainz, p. 2 (October 2007), http://www.se-rwth.de/~rumpe/publications20042008/Groenniger_et_al_ATEM_07.pdf (accessed January 28, 2013)
Chapron, P., Sibertin-Blanc, C., Adreit, F.: Analysis of Power Networks among the Actors of a Social Organisation. In: Kazakov, D., Tsoulas, G. (eds.) AISB 2011 Social Networks and Multiagent Systems, April 4-7, pp. 2–7. The Society for the Study of Artificial Intelligence and the Simulation of Behaviour, York (2011)
Chun, H., Kwak, H., Eom, Y., Moon, S., Jeong, H.: Comparison of online social relations in volume vs interaction: a case study of cyworld. In: Papagiannaki, K., Zhang, Z. (eds.) Proceedings of the 8th ACM SIGCOMM Conference on Internet Measurement, October 20-22, pp. 57–70. ACM New York (2008)
Golbeck, J., Hendler, J.: Inferring binary trust relationships in Web-based social networks. ACM Transactions on Internet Technology (TOIT) 6(4), 497–529 (2006)
Brambilla, M., Mauri, A.: Model-Driven Development of Social Network Enabled Applications with WebML and Social Primitives. In: Grossniklaus, M., Wimmer, M. (eds.) ICWE 2012 Workshops. LNCS, vol. 7703, pp. 41–55. Springer, Heidelberg (2012)
Klout, Inc. The KLOUT Score (2008), http://klout.com/corp/kscore (accessed 26, 2012)
Object Management Group, OMG’s MetaObject Facility (MOF) Home Page (2012), http://www.omg.org/mof/ (accessed February 12, 2013)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer International Publishing Switzerland
About this paper
Cite this paper
Dixon, S.J., Dixon, M., Halpin, E., Pattinson, C. (2013). A Modelling Based Notation for the Automated Extraction and Analysis of Social Networking Data. In: Sheng, Q.Z., Kjeldskov, J. (eds) Current Trends in Web Engineering. ICWE 2013. Lecture Notes in Computer Science, vol 8295. Springer, Cham. https://doi.org/10.1007/978-3-319-04244-2_34
Download citation
DOI: https://doi.org/10.1007/978-3-319-04244-2_34
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-04243-5
Online ISBN: 978-3-319-04244-2
eBook Packages: Computer ScienceComputer Science (R0)