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 | |
| State | Published - Jan 1 2017 |
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Keywords
- Data fusion
- Signal processing
- Social networks
ASJC Scopus subject areas
- Computer Science(all)
Cite this
Social Network Signal Processing for Cyber-Physical Systems. / Abdelzaher, Tarek; Wang, S.; Giridhar, P.; Amin, T. A.; Seetharamu, P.; Roy, H.; Wang, H.; Kaplan, L.; Bowman, E.; George, J.
Cyber-Physical Systems: Foundations, Principles and Applications. Elsevier Inc., 2017. p. 161-174.Research output: Chapter in Book/Report/Conference proceeding › Chapter
}
TY - CHAP
T1 - Social Network Signal Processing for Cyber-Physical Systems
AU - Abdelzaher, Tarek
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
Y1 - 2017/1/1
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
UR - http://www.scopus.com/inward/record.url?scp=85024138112&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85024138112&partnerID=8YFLogxK
U2 - 10.1016/B978-0-12-803801-7.00011-0
DO - 10.1016/B978-0-12-803801-7.00011-0
M3 - Chapter
AN - SCOPUS:85024138112
SN - 9780128038017
SP - 161
EP - 174
BT - Cyber-Physical Systems
PB - Elsevier Inc.
ER -