Engagement vs. Commitment: The Economic Trade-Offs of Polarizing News Content

We study how polarizing content shapes two economic outcomes on a major European news website: engagement (time on site) and commitment (paid subscriptions). Using advances in natural language processing, we construct deep-learning and large-language-model-based textual measures of polarization tailored to a multiparty system. We combine comprehensive supply and demand data-the full publisher-wide article inventory with user-level clicks and subscription outcomes-to track how consumers interact with polarizing articles. To identify causal effects, we use two theoretically distinct instruments: (i) a Bartik-style design that interacts users' stable topic preferences with weekly shifts in the supply of polarizing content; and (ii) an election shock that raises political salience for a subset of readers. We document a "polarization trap": exogenous increases in exposure to polarizing content raise engagement (time on site) but reduce the probability of subscribing. The negative subscription effect is driven more by the affective than the ideological dimension of polarization and is strongest during high-salience political periods. These results imply a strategic trade-off for publishers: content that maximizes short-run attention can undermine the formation of a loyal, paying subscriber base.