SimON-Feedback: An Iterative Algorithm for Performance Tuning in Online Social Simulation

Date

2019-01-01

Author

Vora, Mehul
Chung, Wingyan
Toraman, Çağrı
Huang, Yifan

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Simulation of human behaviour being an intrinsically difficult problem, no single algorithm or model can accurately simulate online social networks. One can obtain an optimal and reliable simulation only after combining several models focusing on diverse social aspects. Since all independent models focus on different social aspects, it is inherently difficult to combine and optimize their performance. Moreover black-box nature of these predictive algorithm makes it difficult to integrate human-guided intelligence. Here we are presenting SimON-Feedback, an iterative ensemble algorithm to combine the prediction of several independent models into a significantly improved simulation of an online social network. To this end, we explore user posting and commenting behavior on Reddit, a large social networking platform comprised of many communities called as subreddits.

URI

https://hdl.handle.net/11511/109643

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Department of Computer Engineering, Conference / Seminar