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Social Network Data Analytics pp 379–412Cite as

Integrating Sensors and Social Networks

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Abstract

A number of sensor applications in recent years collect data which can be directly associated with human interactions. Some examples of such applications include GPS applications on mobile devices, accelerometers, or location sensors designed to track human and vehicular traffic. Such data lends itself to a variety of rich applications in which one can use the sensor data in order to model the underlying relationships and interactions. It also leads to a number of challenges, since such data may often be private, and it is important to be able to perform the mining process without violating the privacy of the users. In this chapter, we provide a broad survey of the work in this important and rapidly emerging field. We also discuss the key problems which arise in the context of this important field and the corresponding solutions.

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Author information

Authors and Affiliations

  1. IBM T. J. Watson Research Center, 10532, Hawthorne, NY, USA

    Charu C. Aggarwal

  2. University of Illinois at Urbana Champaign, Urbana, IL, USA

    Tarek Abdelzaher

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  1. Charu C. Aggarwal
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  2. Tarek Abdelzaher
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Correspondence to Charu C. Aggarwal .

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Editors and Affiliations

  1. Thomas J. Watson Research Center, IBM, Skyline Drive 19, Hawthorne, 10532, New York, USA

    Charu C. Aggarwal

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Aggarwal, C.C., Abdelzaher, T. (2011). Integrating Sensors and Social Networks. In: Aggarwal, C. (eds) Social Network Data Analytics. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-8462-3_14

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  • DOI: https://doi.org/10.1007/978-1-4419-8462-3_14

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