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In proportional elections with open lists the excess of preferences receivedby candidates with respect to the list average is known to follow a universallognormal distribution. We show that lognormality is broken providedpreferences are conditioned to lists with many candidates. In this limitpower-law tails emerge. We study the large-list limit in the framework of aquenched approximation of the word-of-mouth model introduced by Fortunato andCastellano (Phys.Rev.Lett.99(13):138701,2007), where the activism of the agentsis mitigated and the noise of the agent-agent interactions is averaged out.Then we argue that our analysis applies mutatis mutandis to the original modelas well.

On the Power-Law Tails of Vote Distributions in Proportional Elections