Data-driven system identification of the social network dynamics in online postings of an extremist group

Alejandro R. Diaz, Jongeun Choi, Thomas J. Holt, Steven Chermak, Joshua D. Freilich

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Terrorism research has begun to focus on the issue of radicalization, or the acceptance of ideological belief systems that lead toward violence. There has been particular attention paid to the role of the Internet in the exposure to and promotion of radical ideas. There is, however, minimal work that attempts to model the ways that messages are spread or how individual participation in radical on-line communities operates. In this paper, we present a stochastic linear system to represent the evolution of contribution to a sample of 126 threads in an on-line forum where individuals discuss radical belief systems. To estimate or predict the time-varying contributions of agents for given onlineforum data, each agent's contribution has been modeled as a state variable. We then use the expectation-maximization (EM) algorithm to identify the model parameters including the adjacency matrix of the graph constructed among participating agents along with measurement and system uncertainty levels in online-postings. Our approach reveals the identified dynamical influences among agents in the time-varying shaping of the contribution in a datadriven fashion. We use the real-world data from online-postings to demonstrate the usefulness of our approach, and its application toward on-line radicalization.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Cybercrime and Computer Forensic, ICCCF 2016
EditorsBarry Cartwright, Laurie Yiu-Chung Lau, George Weir
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509060962
DOIs
Publication statusPublished - 2016 Nov 9
Event4th IEEE International Conference on Cybercrime and Computer Forensic, ICCCF 2016 - Vancouver, Canada
Duration: 2016 Jun 122016 Jun 14

Publication series

Name2016 IEEE International Conference on Cybercrime and Computer Forensic, ICCCF 2016

Other

Other4th IEEE International Conference on Cybercrime and Computer Forensic, ICCCF 2016
CountryCanada
CityVancouver
Period16/6/1216/6/14

Fingerprint

Information Systems
Social Support
Identification (control systems)
social network
Terrorism
radicalization
Violence
Internet
Uncertainty
Group
internet community
Research
Linear systems
terrorism
promotion
acceptance
uncertainty
violence
participation
System identification

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Information Systems and Management
  • Social Psychology
  • Law

Cite this

Diaz, A. R., Choi, J., Holt, T. J., Chermak, S., & Freilich, J. D. (2016). Data-driven system identification of the social network dynamics in online postings of an extremist group. In B. Cartwright, L. Y-C. Lau, & G. Weir (Eds.), 2016 IEEE International Conference on Cybercrime and Computer Forensic, ICCCF 2016 [7740429] (2016 IEEE International Conference on Cybercrime and Computer Forensic, ICCCF 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCCF.2016.7740429
Diaz, Alejandro R. ; Choi, Jongeun ; Holt, Thomas J. ; Chermak, Steven ; Freilich, Joshua D. / Data-driven system identification of the social network dynamics in online postings of an extremist group. 2016 IEEE International Conference on Cybercrime and Computer Forensic, ICCCF 2016. editor / Barry Cartwright ; Laurie Yiu-Chung Lau ; George Weir. Institute of Electrical and Electronics Engineers Inc., 2016. (2016 IEEE International Conference on Cybercrime and Computer Forensic, ICCCF 2016).
@inproceedings{7bc215188dca453d83b6adfccedd14c0,
title = "Data-driven system identification of the social network dynamics in online postings of an extremist group",
abstract = "Terrorism research has begun to focus on the issue of radicalization, or the acceptance of ideological belief systems that lead toward violence. There has been particular attention paid to the role of the Internet in the exposure to and promotion of radical ideas. There is, however, minimal work that attempts to model the ways that messages are spread or how individual participation in radical on-line communities operates. In this paper, we present a stochastic linear system to represent the evolution of contribution to a sample of 126 threads in an on-line forum where individuals discuss radical belief systems. To estimate or predict the time-varying contributions of agents for given onlineforum data, each agent's contribution has been modeled as a state variable. We then use the expectation-maximization (EM) algorithm to identify the model parameters including the adjacency matrix of the graph constructed among participating agents along with measurement and system uncertainty levels in online-postings. Our approach reveals the identified dynamical influences among agents in the time-varying shaping of the contribution in a datadriven fashion. We use the real-world data from online-postings to demonstrate the usefulness of our approach, and its application toward on-line radicalization.",
author = "Diaz, {Alejandro R.} and Jongeun Choi and Holt, {Thomas J.} and Steven Chermak and Freilich, {Joshua D.}",
year = "2016",
month = "11",
day = "9",
doi = "10.1109/ICCCF.2016.7740429",
language = "English",
series = "2016 IEEE International Conference on Cybercrime and Computer Forensic, ICCCF 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Barry Cartwright and Lau, {Laurie Yiu-Chung} and George Weir",
booktitle = "2016 IEEE International Conference on Cybercrime and Computer Forensic, ICCCF 2016",
address = "United States",

}

Diaz, AR, Choi, J, Holt, TJ, Chermak, S & Freilich, JD 2016, Data-driven system identification of the social network dynamics in online postings of an extremist group. in B Cartwright, LY-C Lau & G Weir (eds), 2016 IEEE International Conference on Cybercrime and Computer Forensic, ICCCF 2016., 7740429, 2016 IEEE International Conference on Cybercrime and Computer Forensic, ICCCF 2016, Institute of Electrical and Electronics Engineers Inc., 4th IEEE International Conference on Cybercrime and Computer Forensic, ICCCF 2016, Vancouver, Canada, 16/6/12. https://doi.org/10.1109/ICCCF.2016.7740429

Data-driven system identification of the social network dynamics in online postings of an extremist group. / Diaz, Alejandro R.; Choi, Jongeun; Holt, Thomas J.; Chermak, Steven; Freilich, Joshua D.

2016 IEEE International Conference on Cybercrime and Computer Forensic, ICCCF 2016. ed. / Barry Cartwright; Laurie Yiu-Chung Lau; George Weir. Institute of Electrical and Electronics Engineers Inc., 2016. 7740429 (2016 IEEE International Conference on Cybercrime and Computer Forensic, ICCCF 2016).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Data-driven system identification of the social network dynamics in online postings of an extremist group

AU - Diaz, Alejandro R.

AU - Choi, Jongeun

AU - Holt, Thomas J.

AU - Chermak, Steven

AU - Freilich, Joshua D.

PY - 2016/11/9

Y1 - 2016/11/9

N2 - Terrorism research has begun to focus on the issue of radicalization, or the acceptance of ideological belief systems that lead toward violence. There has been particular attention paid to the role of the Internet in the exposure to and promotion of radical ideas. There is, however, minimal work that attempts to model the ways that messages are spread or how individual participation in radical on-line communities operates. In this paper, we present a stochastic linear system to represent the evolution of contribution to a sample of 126 threads in an on-line forum where individuals discuss radical belief systems. To estimate or predict the time-varying contributions of agents for given onlineforum data, each agent's contribution has been modeled as a state variable. We then use the expectation-maximization (EM) algorithm to identify the model parameters including the adjacency matrix of the graph constructed among participating agents along with measurement and system uncertainty levels in online-postings. Our approach reveals the identified dynamical influences among agents in the time-varying shaping of the contribution in a datadriven fashion. We use the real-world data from online-postings to demonstrate the usefulness of our approach, and its application toward on-line radicalization.

AB - Terrorism research has begun to focus on the issue of radicalization, or the acceptance of ideological belief systems that lead toward violence. There has been particular attention paid to the role of the Internet in the exposure to and promotion of radical ideas. There is, however, minimal work that attempts to model the ways that messages are spread or how individual participation in radical on-line communities operates. In this paper, we present a stochastic linear system to represent the evolution of contribution to a sample of 126 threads in an on-line forum where individuals discuss radical belief systems. To estimate or predict the time-varying contributions of agents for given onlineforum data, each agent's contribution has been modeled as a state variable. We then use the expectation-maximization (EM) algorithm to identify the model parameters including the adjacency matrix of the graph constructed among participating agents along with measurement and system uncertainty levels in online-postings. Our approach reveals the identified dynamical influences among agents in the time-varying shaping of the contribution in a datadriven fashion. We use the real-world data from online-postings to demonstrate the usefulness of our approach, and its application toward on-line radicalization.

UR - http://www.scopus.com/inward/record.url?scp=85004073330&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85004073330&partnerID=8YFLogxK

U2 - 10.1109/ICCCF.2016.7740429

DO - 10.1109/ICCCF.2016.7740429

M3 - Conference contribution

AN - SCOPUS:85004073330

T3 - 2016 IEEE International Conference on Cybercrime and Computer Forensic, ICCCF 2016

BT - 2016 IEEE International Conference on Cybercrime and Computer Forensic, ICCCF 2016

A2 - Cartwright, Barry

A2 - Lau, Laurie Yiu-Chung

A2 - Weir, George

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Diaz AR, Choi J, Holt TJ, Chermak S, Freilich JD. Data-driven system identification of the social network dynamics in online postings of an extremist group. In Cartwright B, Lau LY-C, Weir G, editors, 2016 IEEE International Conference on Cybercrime and Computer Forensic, ICCCF 2016. Institute of Electrical and Electronics Engineers Inc. 2016. 7740429. (2016 IEEE International Conference on Cybercrime and Computer Forensic, ICCCF 2016). https://doi.org/10.1109/ICCCF.2016.7740429