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Opinion Dynamics in Gendered Social Networks: An Examination of Female Engagement Teams in Afghanistan

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNISA,volume 7227)

Abstract

International forces in Afghanistan have experienced difficulties in developing constructive engagements with the Afghan population, an experience familiar to a wide range of international agencies working in underdeveloped and developing nations around the world. Recently, forces have begun deploying Female Engagement Teams, female military units who engage directly with women in occupied communities, resulting inmore positive relationships with those communities as a whole. In this paper, we explore the hypothesis that the structure of community-based social networks strongly contributes to the effectiveness of the Female Engagement Team strategy, specifically considering gender-based differences in network community structure. We find that the ability to address both female and male network components provides a superior ability to affect opinions in the network, and can provide an effective means of counteracting influences from opposition forces.

Keywords

  • Social Network
  • Opinion Dynamics
  • Female Community
  • Exponential Random Graph Model
  • Opposition Force

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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© 2012 Springer-Verlag Berlin Heidelberg

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Moore, T.W., Finley, P.D., Hammer, R.J., Glass, R.J. (2012). Opinion Dynamics in Gendered Social Networks: An Examination of Female Engagement Teams in Afghanistan. In: Yang, S.J., Greenberg, A.M., Endsley, M. (eds) Social Computing, Behavioral - Cultural Modeling and Prediction. SBP 2012. Lecture Notes in Computer Science, vol 7227. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29047-3_9

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  • DOI: https://doi.org/10.1007/978-3-642-29047-3_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29046-6

  • Online ISBN: 978-3-642-29047-3

  • eBook Packages: Computer ScienceComputer Science (R0)