Abstract
In the convergence culture we are witnessing the rise of social or consumer-generated media—social networks, social blogs, weblogs, podcasts, pictures and videos—that increase communication intensity between people. Key properties of social media, such as frequency, immediacy, permanence and interactivity, should also be the key properties of traditional media—television and newspapers. Unfortunately this is rarely the case.
This book chapter focuses on the possibility to use various social media and other informational and data channels for automatic generation of interactive social media news streams. We propose a network representation and the network model of spreadable media content serving as a basis of new application using the notion of persistent context and apply perpetual analytics on social media data streams, where every incoming observation is evaluated against all prior observations. We discuss our Guerrilla media application idea of tapping into collective intelligence and detecting messages from huge amount of social network accounts and spreading them through interactive social media news streams into the digital universe.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
An, J., Cha, M., Gummadi, K., & Crowcroft, J. (2011). Media landscape in Twitter: A world of new conventions and political diversity. In International AAAI Conference on Weblogs and Social Media
Asur, S., & Huberman, B. A. (2010). Predicting the future with social media. In Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (Vol. 1, pp. 492–499).
Bakshy, E., Marlow, C., Rosenn, I., & Adamic, L. (2012). The role of social networks in information diffusion. In Proceedings of the 21st International Conference on World Wide Web (WWW’12) (pp. 519–522).
Bandari, R., Asur, S., & Huberman, B. A. (2012). The pulse of news in social media: Forecasting popularity. In Proceedings of the Sixth International AAAI Conference on Weblogs and Social Media (ICWSM ’12).
Blei, M. (2012). Probabilistic topic models. Communications of the ACM, 55(4), 77–84.
Brill, E. (1992). A simple rule-based part of speech tagger. In Proceedings of the Third Conference on Applied Natural Language Processing (ANLC ’92) (pp. 152–155).
Buldyrev, S. V., Parshani, R., Paul, G., Stanley, H. E., & Havlin, S. (2010). Catastrophic cascade of failures in interdependent networks. Nature, 464, 1025–1028.
CERN. (2013). Large Hadron Collider at CERN. Accessed March 2013, from http://public.web.cern.ch/public/en/lhc/Computing-en.html
Cha, M., Pérez, J. A. N., & Haddadi, H. (2012). The spread of media content through blogs. Social Network Analysis and Mining, 2, 249–264.
Ciulla, F., Mocanu, D., Baronchelli, A., Goncalves, B., Perra, N., & Vespignani, A. (2012). Beating the news using social media: The case study of American Idol. EPJ Data Science, 1, 8.
FICO. (2013). FICO, Flacon Fraud Manager. Accessed March 2013, from http://www.fico.com/en/Products/DMApps/Pages/FICO-Falcon-Fraud-Manager.aspx
Gillmor, D. (2006). We the media. Grassroots journalism by the people, for the people. London: O’Reilly Media.
Goodall, D. (2013). Accessed July 2013, from http://danielgoodall.com/2009/03/02/owned-bought-and-earned-media/
Grabowicz, P. A., Ramasco, J. J., Moro, E., Pujol, J. M., & Eguiluz, V. M. (2012). Social features of online networks: The strength of intermediary ties in online social media. PLoS One, 7(1), e29358.
Himler, P. (2013). Accessed July 2013, from http://www.forbes.com/sites/peterhimler/2012/09/11/converged-media-rising/
Hull, D. A. (1996). Stemming algorithms: A case study for detailed evaluation. Journal of the American Society for Information Science, 47, 70–84.
Jenkins, H. (2001, June). Convergence? I Diverge. Technology Review, 104(5), 93.
Jenkins, H. (2006). Convergence culture: Where old and new media collide. New York, NY: New York University Press.
Jenkins, H., Ford, S., & Green, J. (2013). Spreadable media. New York, NY: New York University Press.
Kissmetrics. (2013). A blog about analytics, marketing and testing. Accessed March 2013, from http://blog.kissmetrics.com
Klimek, P., Bayer, W., & Thurner, S. (2011). The blogosphere as an excitable social medium: Richter’s and Omori’s Law in media coverage. Physica A: Statistical Mechanics and its Applications, 390(21–22), 3870–3875.
Kohlschütter, C., Fankhauser, P., & Nejdl, W. (2010). Boilerplate detection using shallow text features. In Proceedings of WSDM 2010 (pp. 441–450).
Kulshrestha, J., Kooti, F., Nikravesh, A., & Gummadi, K. (2012). Geographic dissection of the Twitter network. In International AAAI Conference on Weblogs and Social Media.
Kunda, Z. (1990). The case for motivated reasoning. Psychological Bulletin, 108(3), 480–498.
Kwak, H., Lee, C., Park, H., & Moon, S. (2010). What is Twitter, a social network or a news media? In Proceedings of the 19th International Conference on World Wide Web (WWW’10) (pp. 591–600).
Leskovec, J., Backstrom, L., & Kleinberg, J. (2009). Meme-tracking and the dynamics of the news cycle. In Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD ’09) (pp. 497–506).
Lévy, P. (1994). L’Intelligence collective. Pour une anthropologie du cyberspace. La Découverte.
Liben-Nowell, D., Novak, J., Kumar, R., Raghavan, P., & Tomkins, A. (2005). Geographic routing in social networks. PNAS, 102(33), 11623–11628.
Mayer-Schoenberger, V., & Cukier, K. (2013). Big data: A revolution that will transform how we live, work and think. London: John Murray.
McLuhan, M. (1964). Understanding media: The extension of man. Cambridge: MIT Press.
Metaxas, P. T., & Mustafaraj, E. (2012). Social media and the elections. Science, 338, 472–473.
Miller, G. A. (1995). WordNet: A lexical database for English. Communications of the ACM, 38(11), 39–41.
Morales, G. D., Gionis, A., & Lucchese, C. (2012). From chatter to headlines: Harnessing the real-time web for personalized news recommendation. In Proceedings of the Fifth ACM International Conference on Web Search and Data Mining (WSDM’12) (pp. 153–162).
Negroponte, N. (1995). Being digital. London: Hodder & Stoughton.
Pasternack, J., & Roth, D. (2009). Extracting article text from the Web with Maximum subsequence segmentation. In Proceedings of the 18th International Conference on World Wide Web (WWW2009) (pp. 971–980).
Quercia, D., Capra, L., & Crowcroft, J. (2012). The social world of Twitter: Topics, geography, and emotions. In International AAAI Conference on Weblogs and Social Media.
Ranger, C., Raghuraman, R., Penmets, A., Bradski, G., & Kozyrakism, C. (2007). Evaluating MapReduce for multi-core and multiprocessor systems. In IEEE 13th International Symposium on HPCA 2007 (pp. 13–24).
Reynolds, G. (2006, Winter). The rise of guerrilla media. The New Atlantis (pp. 97–111). This article is an excerpt from the book “An Army of Davids” by G. Reynolds.
Rodriguez, M. G., Leskovec, J., & Schölkopf, B. (2013). Structure and dynamics of information pathways in online media. In Proceedings of the Sixth ACM International Conference on Web Search and Data Mining (WSDM ’13) (pp. 23–32).
Ruan, Y., Purohit, H., Fuhry, D., Parthasarathy, S., & Sheth, A. (2012). Prediction of topic volume on Twitter. In Proceedings of the Fourth International ACM Conference on Web Science. ACM 978-1-4503-1228-8.
Simini, F., Gonzalez, M. C., Maritan, A., & Barabasi, A.-L. (2012). A universal model for mobility and migration patterns. Nature, 484, 96–100.
Somlo, G. L., & Howe, A. E. (2001). Incremental clustering for profile maintenance in information gathering web agents. In Proceedings of the Fifth International Conference on Autonomous Agents (pp. 262–269).
Stallman, R. (1999). The GNU operating system and the free software movement. In C. DiBona, S. Ockman, & M. Stone (Eds.), Open sources voices from the open source revolution. Sebastopol, CA: O’Reilly.
Sundaram, H., Xie, L., De Choudhury, M., Lin, Y.-R., & Natsev, A. (2012). Multimedia semantics: Interactions between content and community. Proceedings of the IEEE, 100(9), 2737–2758.
Taber, C. S., & Lodge, M. (2006). Motivated skepticism in the evaluation of political beliefs. American Journal of Political Science, 50(3), 755–769.
Takhteyev, Y., Gruzd, A., & Wellman, B. (2012). Geography of Twitter networks. Social Networks., 34(1), 73–81.
Tsur, O., & Rappoport, A. (2012). What’s in a hashtag?: Content based prediction of the spread of ideas in microblogging communities. In Proceedings of the Fifth ACM International Conference on Web Search and Data Mining (WSDM’12) (pp. 643–652).
Ugander, J., Backstrom, L., Marlow, C., & Kleinberg, J. (2012). Structural diversity in social contagion. PNAS, 109, 5962–5966.
Vanderbilt, T. (2013, April). The Nielsen family is dead. Wired. http://www.wired.com/underwire/2013/03/nielsen-family-is-dead/
Vespignani, A. (2010). Complex networks: The fragility of interdependency. Nature, 464(7291), 984–985. doi:10.1038/464984a.
Villars, R. L., Olofson, C. W., & Eastwood, M. (2011). Big data: What is and why you should care. IDC.
Wang, C., & Huberman, B. A. (2012a). How random are online social interactions? Scientific Reports, 2, 633. doi:10.1083/srep00633.
Wang, C., & Huberman, B. A. (2012b). Long trend dynamics in social media. EPJ Data Science, 1, 2.
Web-strategist. (2013). Accessed July 2013, from http://www.web-strategist.com/blog/2012/07/19/altimeter-report-paid-owned-earned-converged-media/
Weng, L., Flammini, A., Vespignani, A., & Menczer, F. (2012). Competition among memes in a world with limited attention. Scientific Report, 2, 335.
Ytreberg, E. (2011). Convergence: Essentially confused? New Media & Society, 13(3), 502–508.
Acknowledgments
The work that led to this paper was partially financed by the project SEETechnology “Co-operation of SEE science parks for the promotion of transnational market uptake of R&D results and technologies by SMEs” co-funded by South East Europe Transnational Cooperation Programme. The work of one of us (DK) was partly financed within the framework of the operation entitled “Centre for Open Innovation and Research of the University of Maribor”. The operation is co-funded by the European Regional Development Fund and conducted within the framework of the Operational Programme for Strengthening Regional Development Potentials for the period 2007–2013, development priority 1: “Competitiveness of companies and research excellence”, priority axis 1.1: “Encouraging competitive potential of enterprises and research excellence.”
The authors wish to thank Marko and Urška Samec for the infographics design.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Duh, A., Meznaric, S., Korošak, D. (2016). Guerrilla Media: Interactive Social Media. In: Lugmayr, A., Dal Zotto, C. (eds) Media Convergence Handbook - Vol. 1. Media Business and Innovation. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54484-2_17
Download citation
DOI: https://doi.org/10.1007/978-3-642-54484-2_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-54483-5
Online ISBN: 978-3-642-54484-2
eBook Packages: Business and ManagementBusiness and Management (R0)