Social Network Signal Processing for Cyber-Physical Systems

T. Abdelzaher; S. Wang; P. Giridhar; T. A. Amin; P. Seetharamu; H. Roy; H. Wang; L. Kaplan; E. Bowman; J. George

doi:10.1016/B978-0-12-803801-7.00011-0

Social Network Signal Processing for Cyber-Physical Systems

T. Abdelzaher, S. Wang, P. Giridhar, T. A. Amin, P. Seetharamu, H. Roy, H. Wang, L. Kaplan, E. Bowman, J. George

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

This chapter demonstrates the utility of exploiting signal processing techniques common to physical sensing modalities in order to reconstruct conditions of the physical world from social network feeds. We show that, as a sensing modality, social sensing is not unlike acoustic, vibration, or magnetic sensing. A mathematical analogy is presented between social networks and physical media that allows adaptation of signal processing algorithms derived for the latter to solve novel challenges observed in the former. The chapter describes examples of event identification and tracking using Twitter and Instagram data, and presents the underlying analytical foundations.

Original language	English (US)
Title of host publication	Cyber-Physical Systems
Subtitle of host publication	Foundations, Principles and Applications
Publisher	Elsevier Inc.
Pages	161-174
Number of pages	14
ISBN (Electronic)	9780128038741
ISBN (Print)	9780128038017
DOIs	https://doi.org/10.1016/B978-0-12-803801-7.00011-0
State	Published - Jan 1 2017

Keywords

Data fusion
Signal processing
Social networks

ASJC Scopus subject areas

Computer Science(all)

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10.1016/B978-0-12-803801-7.00011-0

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abstract = "This chapter demonstrates the utility of exploiting signal processing techniques common to physical sensing modalities in order to reconstruct conditions of the physical world from social network feeds. We show that, as a sensing modality, social sensing is not unlike acoustic, vibration, or magnetic sensing. A mathematical analogy is presented between social networks and physical media that allows adaptation of signal processing algorithms derived for the latter to solve novel challenges observed in the former. The chapter describes examples of event identification and tracking using Twitter and Instagram data, and presents the underlying analytical foundations.",

keywords = "Data fusion, Signal processing, Social networks",

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AU - Abdelzaher, T.

AU - Wang, S.

AU - Giridhar, P.

AU - Amin, T. A.

AU - Seetharamu, P.

AU - Roy, H.

AU - Wang, H.

AU - Kaplan, L.

AU - Bowman, E.

AU - George, J.

PY - 2017/1/1

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N2 - This chapter demonstrates the utility of exploiting signal processing techniques common to physical sensing modalities in order to reconstruct conditions of the physical world from social network feeds. We show that, as a sensing modality, social sensing is not unlike acoustic, vibration, or magnetic sensing. A mathematical analogy is presented between social networks and physical media that allows adaptation of signal processing algorithms derived for the latter to solve novel challenges observed in the former. The chapter describes examples of event identification and tracking using Twitter and Instagram data, and presents the underlying analytical foundations.

AB - This chapter demonstrates the utility of exploiting signal processing techniques common to physical sensing modalities in order to reconstruct conditions of the physical world from social network feeds. We show that, as a sensing modality, social sensing is not unlike acoustic, vibration, or magnetic sensing. A mathematical analogy is presented between social networks and physical media that allows adaptation of signal processing algorithms derived for the latter to solve novel challenges observed in the former. The chapter describes examples of event identification and tracking using Twitter and Instagram data, and presents the underlying analytical foundations.

KW - Data fusion

KW - Signal processing

KW - Social networks

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M3 - Chapter

AN - SCOPUS:85024138112

SN - 9780128038017

SP - 161

EP - 174

BT - Cyber-Physical Systems

PB - Elsevier Inc.

ER -

Social Network Signal Processing for Cyber-Physical Systems

Abstract

Keywords

ASJC Scopus subject areas

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