Content Filtering with Inattentive Information Consumers

TL;DR

This paper models content filtering as a strategic game between a filter and an inattentive consumer, revealing how filter quality and strategic behavior impact effectiveness and outcomes in misinformation and spam filtering.

Contribution

It introduces a game-theoretic framework for content filtering considering consumer inattention and strategic attackers, highlighting conditions affecting filter effectiveness and equilibrium payoffs.

Findings

Improving filter quality is weakly Pareto improving but may not affect payoffs until a threshold.

Lack of commitment by the filter can lead to inefficiencies.

Strategic attackers can cause higher filter quality to decrease payoffs.

Abstract

We develop a model of content filtering as a game between the filter and the content consumer, where the latter incurs information costs for examining the content. Motivating examples include censoring misinformation, spam/phish filtering, and recommender systems. When the attacker is exogenous, we show that improving the filter's quality is weakly Pareto improving, but has no impact on equilibrium payoffs until the filter becomes sufficiently accurate. Further, if the filter does not internalize the information costs, its lack of commitment power may render it useless and lead to inefficient outcomes. When the attacker is also strategic, improvements to filter quality may sometimes decrease equilibrium payoffs.