Pipelines and their compositions for modeling and analysis of controlled online networked social science experiments

Vanessa Cedeno-Mieles, Zhihao Hu, Xinwei Deng, Noshir Contractor, Yihui Ren, Saliya Ekanayake, Brian J. Goode, Chris J. Kuhlman, Dustin Machi, Madhav V. Marathe, Henning H. Mortveit, Naren Ramakrishnan, Parang Saraf, Nathan Self, Joshua M. Epstein, Michael W. Macy

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

Abstract

There has been significant growth in online social science experiments in order to understand behavior at-scale, with finer-grained data collection. Considerable work is required to perform data analytics for custom experiments. We also seek to perform repeated networked experiments and modeling in an iterative loop. In this work, we design and build four composable and extensible automated software pipelines for (1) data analytics; (2) model property inference; (3) model/simulation; and (4) results analysis and comparisons between experimental data and model predictions. To reason about experiments and models, we design a formal data model. Our data model is for scenarios where subjects can repeat actions (from a set) any number of times over the game duration. Because the types of interactions and action sets are flexible, this class of experiments is large. Two case studies, on collective identity and complex contagion, illustrate use of the system.

Original languageEnglish (US)
Title of host publicationWSC 2018 - 2018 Winter Simulation Conference
Subtitle of host publicationSimulation for a Noble Cause
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages774-785
Number of pages12
ISBN (Electronic)9781538665725
DOIs
StatePublished - Jan 31 2019
Event2018 Winter Simulation Conference, WSC 2018 - Gothenburg, Sweden
Duration: Dec 9 2018Dec 12 2018

Publication series

NameProceedings - Winter Simulation Conference
Volume2018-December
ISSN (Print)0891-7736

Conference

Conference2018 Winter Simulation Conference, WSC 2018
CountrySweden
CityGothenburg
Period12/9/1812/12/18

Fingerprint

Social sciences
Social Sciences
Pipelines
Chemical analysis
Modeling
Experiment
Experiments
Data Model
Data structures
Contagion
Formal Model
Prediction Model
Simulation Model
Experimental Data
Game
Scenarios
Software
Interaction
Model
Design

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications

Cite this

Cedeno-Mieles, V., Hu, Z., Deng, X., Contractor, N., Ren, Y., Ekanayake, S., ... Macy, M. W. (2019). Pipelines and their compositions for modeling and analysis of controlled online networked social science experiments. In WSC 2018 - 2018 Winter Simulation Conference: Simulation for a Noble Cause (pp. 774-785). [8632478] (Proceedings - Winter Simulation Conference; Vol. 2018-December). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WSC.2018.8632478
Cedeno-Mieles, Vanessa ; Hu, Zhihao ; Deng, Xinwei ; Contractor, Noshir ; Ren, Yihui ; Ekanayake, Saliya ; Goode, Brian J. ; Kuhlman, Chris J. ; Machi, Dustin ; Marathe, Madhav V. ; Mortveit, Henning H. ; Ramakrishnan, Naren ; Saraf, Parang ; Self, Nathan ; Epstein, Joshua M. ; Macy, Michael W. / Pipelines and their compositions for modeling and analysis of controlled online networked social science experiments. WSC 2018 - 2018 Winter Simulation Conference: Simulation for a Noble Cause. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 774-785 (Proceedings - Winter Simulation Conference).
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author = "Vanessa Cedeno-Mieles and Zhihao Hu and Xinwei Deng and Noshir Contractor and Yihui Ren and Saliya Ekanayake and Goode, {Brian J.} and Kuhlman, {Chris J.} and Dustin Machi and Marathe, {Madhav V.} and Mortveit, {Henning H.} and Naren Ramakrishnan and Parang Saraf and Nathan Self and Epstein, {Joshua M.} and Macy, {Michael W.}",
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Cedeno-Mieles, V, Hu, Z, Deng, X, Contractor, N, Ren, Y, Ekanayake, S, Goode, BJ, Kuhlman, CJ, Machi, D, Marathe, MV, Mortveit, HH, Ramakrishnan, N, Saraf, P, Self, N, Epstein, JM & Macy, MW 2019, Pipelines and their compositions for modeling and analysis of controlled online networked social science experiments. in WSC 2018 - 2018 Winter Simulation Conference: Simulation for a Noble Cause., 8632478, Proceedings - Winter Simulation Conference, vol. 2018-December, Institute of Electrical and Electronics Engineers Inc., pp. 774-785, 2018 Winter Simulation Conference, WSC 2018, Gothenburg, Sweden, 12/9/18. https://doi.org/10.1109/WSC.2018.8632478

Pipelines and their compositions for modeling and analysis of controlled online networked social science experiments. / Cedeno-Mieles, Vanessa; Hu, Zhihao; Deng, Xinwei; Contractor, Noshir; Ren, Yihui; Ekanayake, Saliya; Goode, Brian J.; Kuhlman, Chris J.; Machi, Dustin; Marathe, Madhav V.; Mortveit, Henning H.; Ramakrishnan, Naren; Saraf, Parang; Self, Nathan; Epstein, Joshua M.; Macy, Michael W.

WSC 2018 - 2018 Winter Simulation Conference: Simulation for a Noble Cause. Institute of Electrical and Electronics Engineers Inc., 2019. p. 774-785 8632478 (Proceedings - Winter Simulation Conference; Vol. 2018-December).

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

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AU - Cedeno-Mieles, Vanessa

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AU - Deng, Xinwei

AU - Contractor, Noshir

AU - Ren, Yihui

AU - Ekanayake, Saliya

AU - Goode, Brian J.

AU - Kuhlman, Chris J.

AU - Machi, Dustin

AU - Marathe, Madhav V.

AU - Mortveit, Henning H.

AU - Ramakrishnan, Naren

AU - Saraf, Parang

AU - Self, Nathan

AU - Epstein, Joshua M.

AU - Macy, Michael W.

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AB - There has been significant growth in online social science experiments in order to understand behavior at-scale, with finer-grained data collection. Considerable work is required to perform data analytics for custom experiments. We also seek to perform repeated networked experiments and modeling in an iterative loop. In this work, we design and build four composable and extensible automated software pipelines for (1) data analytics; (2) model property inference; (3) model/simulation; and (4) results analysis and comparisons between experimental data and model predictions. To reason about experiments and models, we design a formal data model. Our data model is for scenarios where subjects can repeat actions (from a set) any number of times over the game duration. Because the types of interactions and action sets are flexible, this class of experiments is large. Two case studies, on collective identity and complex contagion, illustrate use of the system.

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M3 - Conference contribution

T3 - Proceedings - Winter Simulation Conference

SP - 774

EP - 785

BT - WSC 2018 - 2018 Winter Simulation Conference

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Cedeno-Mieles V, Hu Z, Deng X, Contractor N, Ren Y, Ekanayake S et al. Pipelines and their compositions for modeling and analysis of controlled online networked social science experiments. In WSC 2018 - 2018 Winter Simulation Conference: Simulation for a Noble Cause. Institute of Electrical and Electronics Engineers Inc. 2019. p. 774-785. 8632478. (Proceedings - Winter Simulation Conference). https://doi.org/10.1109/WSC.2018.8632478