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Dr. Maciej Latek speaker at 10/12 Colloquium

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The Computational Social Science Research Colloquium /Colloquium in Computational and Data Sciences speaker for Friday, October 12, will be Maciej Latek (Computational Social Science Ph.D. 2011), Chief Technology Officer, trovero. Dr. Latek’s talk entitled “Industrializing multi-agent simulations: The case of social media marketing, advertising and influence campaigns” (abstract below) will begin at 3:00 in the Center for Social Complexity Suite located on the 3rd floor of Research Hall. The talk will be followed by a Q&A session along with light refreshments.

This session will be live-streamed on the YouTube channel:

For announcements regarding this and future streams, please join the CSS/CDS student and alumni Facebook group:

For a list of upcoming and previous seminars, please visit:

Abstract: System engineering approaches required to transition multi-agent simulations out of science into decision support share features with AI, machine learning, and application development, but also present unique challenges. In this talk, I will use trovero as an example to illustrate how some of these challenges can be addressed.

As a platform to help advertisers and marketers plan and implement campaigns on social media, trovero is comprised of social network simulations for optimization and automation and network population synthesis used to preserve people’s privacy while maintaining a robust picture of social media communities. Social network simulations forecast campaign outcomes and pick the right campaigns for given KPIs. Simulation is the only viable way to reliably forecast campaign outcomes. Big data methods fail to forecast campaign outcomes, because they are fundamentally unfit for social network data. Network population synthesis enables working with aggregate data without relying on data-sharing agreements with social media platforms that are ever more reluctant to share user data with third parties after GDPR and the Cambridge Analytica debacle.

I will outline how these two approaches complement one another, what computational and data infrastructure is required to support them, and how workflows and interactions with social media platforms are organized.