Design of Coalition Resistant Credit Score Functions for Online Discussion Forums

Ghalme, Ganesh and Gujar, Sujit and Kumar, Amleshwar and Jain, Shweta and Narahari, Y (2018) Design of Coalition Resistant Credit Score Functions for Online Discussion Forums. In: 17th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2018, 10-15 Jul 2018, Stockholm; Sweden, pp. 95-103.

PDF AAMAS_2018.pdf - Published Version Restricted to Registered users only Download (1MB) | Request a copy

Abstract

We consider the problem of designing a robust credit score function in the context of online discussion forums. Credit score function assigns a real-valued credit score to each participant based on activities on the forum. A credit score of a participant quantifies the usefulness of contribution made by her. However, participants can manipulate a credit score function by forming coalitions, i.e., by strategically awarding upvotes, likes, etc. among a subset of agents to maximize their credit scores. We propose a coalition resistant credit score function which discourages such strategic endorsements. We use community detection algorithms to identify close-knit communities in the graph of interactions and characterize coalition identifying community detection metric. In particular, we show that modularity is coalition identifying and provide theoretical guarantees on modularity based credit score function. Finally, we validate our theoretical findings with simulations on illustrative datasets.

Item Type:	Conference Paper
Publisher:	ASSOC COMPUTING MACHINERY
Additional Information:	The copyright of this article belongs to ASSOC COMPUTING MACHINERY
Department/Centre:	Division of Electrical Sciences > Computer Science & Automation
Date Deposited:	26 Mar 2021 09:50
Last Modified:	26 Mar 2021 09:50
URI:	http://eprints.iisc.ac.in/id/eprint/62937

Actions (login required)

View Item