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Bio-inspired Clustering and Data Diffusion in Machine Social Networks

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Computational Social Networks

Abstract

At the end of 2010, we are at the effective end of the second phase of research in the field of Social Networks (SNs) and aspects such as Human-to-Human (H2H) interactions have pretty much had their day due to advances in Machine-to-Machine (M2M) interactions. This chapter will provide a useful insight into the differences between those two types of SNs: the human SNs (hSNs) based on H2H interactions and the machine SNs (mSNs) based on M2M interactions. During the last two decades rapid improvements in computing and communication technologies have enabled a proliferation of hSNs and we believe they will induce the formation of mSNs in the next decades. To this end, we will show how to carry out successful SN analyses (e.g. clustering and data diffusion) by connecting ethological approaches to social behaviour in animals (e.g. the study of firefly synchronization) and M2M interactions.

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Notes

  1. 1.

    The SN was established in 2002. It is active today (http://www.friendster.com) and has over 115 million registered users, of which over 90% come from Asian countries (in Western countries it is no longer popular).

  2. 2.

    The SN was established in 2003. This SN (http://www.myspace.com) gained the first million users in 2004, while in early 2007 the number of its users reached the 100 million mark. The period between 2005 and 2007 was a time when MySpace was the most popular SNS in the world, after which Facebook assumed primacy. Today, the number of MySpace users is around the 130 million mark (70% of users are Americans). Since 2005 MySpace has been owned by News Corporation (the second largest media company in the world), which bought it for 580 million US dollars.

  3. 3.

    The SN was established in 2003. It is active today (http://www.linkedin.com) and has over 100 million users from over 200 countries representing today’s most important professional SN in which more than 150 different industries are represented, and whose members are leading people of all Fortune 500 global companies.

  4. 4.

    The SN was established in 2004 and today is the most popular SNS (http://www.facebook.com/) with over 700 million users worldwide (more than 10% of the entire world population) and is constantly growing. The value of the Facebook brand was estimated at a staggering 50 billion US dollars. General statistics about Facebook are available at http://www.facebook.com/press/info.php?statistics and http://www.socialbakers.com

  5. 5.

    The SN was established in 2005. The name Bebo is an acronym for “Blog early, blog often.” The target users of this SN (http://www.bebo.com/) are primarily residents of Ireland, UK, Australia, New Zealand and US, and their total number is about 40 million. Since 2008 Bebo has been owned by AOL (one of the world’s major Internet and media companies), who bought it for 850 million US dollars.

  6. 6.

    The SN was established in 2006. It is based on the microblogging principle – users can post and read short messages (text messages to a maximum of 140 characters long) called tweets. The similarities with the concept of the SMS (Short Message Service) in mobile telecommunications is responsible for Twitter being called the “SMS of the Internet.” This SN (http://www.twitter.com) recorded staggering user growth rates (greater than 1,000% per year), but the problem with Twitter is the fact that it has a large number of inactive users (compared to other leading SNSs – it is estimated that only 40% of Twitter users are actually active, while this number for Facebook and MySpace is around 70%). The current total number of Twitter users has exceeded 200 million, while the dizzying growth rate has began to calm down. There is, on average, 150 million tweets sent per day.

  7. 7.

    Smart vacuum cleaners – http://bestvacuumcleanerreviews.co.uk/

  8. 8.

    Smart washing machines – http://weblogs.asp.net/ssivakumar/archive/2004/09/21/232359.aspx

  9. 9.

    Smart fridges – http://www.guardian.co.uk/environment/2008/dec/02/energy-efficient-dynamic-demand-fridges

  10. 10.

    Smart heating and cooling subsystems – http://smartheat.com.au/

  11. 11.

    Smart cities – http://www.smart-cities.eu/

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Acknowledgements

The authors acknowledge the support of the research project “Content Delivery and Mobility of Users and Services in New Generation Networks” (036-0362027-1639), funded by the Ministry of Science, Education and Sports of the Republic of Croatia.

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Authors and Affiliations

  1. Faculty of Electrical Engineering and Computing, University of Zagreb, Unska 3, HR-10000, Zagreb, Croatia

    Iva Bojic & Tomislav Lipic

  2. Centre for Informatics and Computing, Rudjer Boskovic Institute, Bijenicka 54, HR-10000, Zagreb, Croatia

    Vedran Podobnik

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  1. Iva Bojic
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  2. Tomislav Lipic
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Correspondence to Iva Bojic .

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  1. Auburn, 98071, USA

    Ajith Abraham

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Bojic, I., Lipic, T., Podobnik, V. (2012). Bio-inspired Clustering and Data Diffusion in Machine Social Networks. In: Abraham, A. (eds) Computational Social Networks. Springer, London. https://doi.org/10.1007/978-1-4471-4054-2_3

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  • DOI: https://doi.org/10.1007/978-1-4471-4054-2_3

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