The role of motifs in understanding behavior in social and engineered networks

Dave Braines, Diane Felmlee, Don Towsley, Kun Tu, Roger M. Whitaker, Liam D. Turner

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

1 Citation (Scopus)

Abstract

Within networks one can identify motifs that are significant recurring patterns of interaction between nodes. Here motifs are sub-graphs that occur more frequently than would be explained by random connections. Graphs can be used to model internal network structures of human groups, or links between groups, with group dynamics being governed by these structures. Graphs can also model behavior in engineered systems, and internal network structures can significantly affect dynamic behavior. A graph may only be partially visible (such as in hostile or coalition environments), however detectable network motifs may in some cases be reflective of the entire graph. We outline a research plan and describe basic network motifs and their properties, along with current analytic techniques for static and dynamic settings. We offer suggestions as to how network motif techniques can be applied to intra- or inter- group behavior, for example to detect whether multiple groups behave as a co-operative alliance, or whether coalition networks inter-operate in positive ways. As an example, we examine a complex time-series graph dataset relevant to coalition focused aspects of the class of networks under study, specifically related to the social network resulting from the authorship of academic papers within a coalition. We provide details of the basic analysis of this network over time and outline how this can be used as one of the datasets for our planned network motif research activities, especially with regards to the temporal and evolutionary aspects.

Original languageEnglish (US)
Title of host publicationNext-Generation Analyst VI
EditorsJames Llinas, Timothy P. Hanratty
PublisherSPIE
ISBN (Electronic)9781510618176
DOIs
StatePublished - Jan 1 2018
EventNext-Generation Analyst VI 2018 - Orlando, United States
Duration: Apr 16 2018Apr 17 2018

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume10653
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Other

OtherNext-Generation Analyst VI 2018
CountryUnited States
CityOrlando
Period4/16/184/17/18

Fingerprint

Coalitions
Graph in graph theory
Time series
group dynamics
Network Structure
Internal
Social Networks
Dynamic Behavior
Subgraph
Entire
suggestion
Vertex of a graph
Interaction
Model
interactions

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Cite this

Braines, D., Felmlee, D., Towsley, D., Tu, K., Whitaker, R. M., & Turner, L. D. (2018). The role of motifs in understanding behavior in social and engineered networks. In J. Llinas, & T. P. Hanratty (Eds.), Next-Generation Analyst VI [106530W] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 10653). SPIE. https://doi.org/10.1117/12.2309471
Braines, Dave ; Felmlee, Diane ; Towsley, Don ; Tu, Kun ; Whitaker, Roger M. ; Turner, Liam D. / The role of motifs in understanding behavior in social and engineered networks. Next-Generation Analyst VI. editor / James Llinas ; Timothy P. Hanratty. SPIE, 2018. (Proceedings of SPIE - The International Society for Optical Engineering).
@inproceedings{da76d3b4b06c425e9d17cac83daf96e8,
title = "The role of motifs in understanding behavior in social and engineered networks",
abstract = "Within networks one can identify motifs that are significant recurring patterns of interaction between nodes. Here motifs are sub-graphs that occur more frequently than would be explained by random connections. Graphs can be used to model internal network structures of human groups, or links between groups, with group dynamics being governed by these structures. Graphs can also model behavior in engineered systems, and internal network structures can significantly affect dynamic behavior. A graph may only be partially visible (such as in hostile or coalition environments), however detectable network motifs may in some cases be reflective of the entire graph. We outline a research plan and describe basic network motifs and their properties, along with current analytic techniques for static and dynamic settings. We offer suggestions as to how network motif techniques can be applied to intra- or inter- group behavior, for example to detect whether multiple groups behave as a co-operative alliance, or whether coalition networks inter-operate in positive ways. As an example, we examine a complex time-series graph dataset relevant to coalition focused aspects of the class of networks under study, specifically related to the social network resulting from the authorship of academic papers within a coalition. We provide details of the basic analysis of this network over time and outline how this can be used as one of the datasets for our planned network motif research activities, especially with regards to the temporal and evolutionary aspects.",
author = "Dave Braines and Diane Felmlee and Don Towsley and Kun Tu and Whitaker, {Roger M.} and Turner, {Liam D.}",
year = "2018",
month = "1",
day = "1",
doi = "10.1117/12.2309471",
language = "English (US)",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "James Llinas and Hanratty, {Timothy P.}",
booktitle = "Next-Generation Analyst VI",
address = "United States",

}

Braines, D, Felmlee, D, Towsley, D, Tu, K, Whitaker, RM & Turner, LD 2018, The role of motifs in understanding behavior in social and engineered networks. in J Llinas & TP Hanratty (eds), Next-Generation Analyst VI., 106530W, Proceedings of SPIE - The International Society for Optical Engineering, vol. 10653, SPIE, Next-Generation Analyst VI 2018, Orlando, United States, 4/16/18. https://doi.org/10.1117/12.2309471

The role of motifs in understanding behavior in social and engineered networks. / Braines, Dave; Felmlee, Diane; Towsley, Don; Tu, Kun; Whitaker, Roger M.; Turner, Liam D.

Next-Generation Analyst VI. ed. / James Llinas; Timothy P. Hanratty. SPIE, 2018. 106530W (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 10653).

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

TY - GEN

T1 - The role of motifs in understanding behavior in social and engineered networks

AU - Braines, Dave

AU - Felmlee, Diane

AU - Towsley, Don

AU - Tu, Kun

AU - Whitaker, Roger M.

AU - Turner, Liam D.

PY - 2018/1/1

Y1 - 2018/1/1

N2 - Within networks one can identify motifs that are significant recurring patterns of interaction between nodes. Here motifs are sub-graphs that occur more frequently than would be explained by random connections. Graphs can be used to model internal network structures of human groups, or links between groups, with group dynamics being governed by these structures. Graphs can also model behavior in engineered systems, and internal network structures can significantly affect dynamic behavior. A graph may only be partially visible (such as in hostile or coalition environments), however detectable network motifs may in some cases be reflective of the entire graph. We outline a research plan and describe basic network motifs and their properties, along with current analytic techniques for static and dynamic settings. We offer suggestions as to how network motif techniques can be applied to intra- or inter- group behavior, for example to detect whether multiple groups behave as a co-operative alliance, or whether coalition networks inter-operate in positive ways. As an example, we examine a complex time-series graph dataset relevant to coalition focused aspects of the class of networks under study, specifically related to the social network resulting from the authorship of academic papers within a coalition. We provide details of the basic analysis of this network over time and outline how this can be used as one of the datasets for our planned network motif research activities, especially with regards to the temporal and evolutionary aspects.

AB - Within networks one can identify motifs that are significant recurring patterns of interaction between nodes. Here motifs are sub-graphs that occur more frequently than would be explained by random connections. Graphs can be used to model internal network structures of human groups, or links between groups, with group dynamics being governed by these structures. Graphs can also model behavior in engineered systems, and internal network structures can significantly affect dynamic behavior. A graph may only be partially visible (such as in hostile or coalition environments), however detectable network motifs may in some cases be reflective of the entire graph. We outline a research plan and describe basic network motifs and their properties, along with current analytic techniques for static and dynamic settings. We offer suggestions as to how network motif techniques can be applied to intra- or inter- group behavior, for example to detect whether multiple groups behave as a co-operative alliance, or whether coalition networks inter-operate in positive ways. As an example, we examine a complex time-series graph dataset relevant to coalition focused aspects of the class of networks under study, specifically related to the social network resulting from the authorship of academic papers within a coalition. We provide details of the basic analysis of this network over time and outline how this can be used as one of the datasets for our planned network motif research activities, especially with regards to the temporal and evolutionary aspects.

UR - http://www.scopus.com/inward/record.url?scp=85049690404&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85049690404&partnerID=8YFLogxK

U2 - 10.1117/12.2309471

DO - 10.1117/12.2309471

M3 - Conference contribution

AN - SCOPUS:85049690404

T3 - Proceedings of SPIE - The International Society for Optical Engineering

BT - Next-Generation Analyst VI

A2 - Llinas, James

A2 - Hanratty, Timothy P.

PB - SPIE

ER -

Braines D, Felmlee D, Towsley D, Tu K, Whitaker RM, Turner LD. The role of motifs in understanding behavior in social and engineered networks. In Llinas J, Hanratty TP, editors, Next-Generation Analyst VI. SPIE. 2018. 106530W. (Proceedings of SPIE - The International Society for Optical Engineering). https://doi.org/10.1117/12.2309471