This paper studies how profit-maximizing media outlets select headlines when consumers face costly access to information. I develop a model of strategic disclosure under hard information in which an outlet chooses a truthful subset of an article to maximize income. In equilibrium, outlets strategically emphasize information that maximizes the expected value of reading the article, and, in some cases, this strategic selection induces rational beliefs opposite to those supported by the full text, even under hard information constraints and in the absence of ideological bias. The model predicts that headline--article misalignment is more likely when information is more heterogeneous and that subscription models do not eliminate incentives for strategic selection. I test these predictions using two newly assembled datasets covering more than 380,000 headline--article pairs from major English-language newspapers and state-of-the-art semantic measures of informativeness, heterogeneity, and alignment. Consistent with the model, greater heterogeneity is associated with lower alignment, while a difference-in-differences analysis of the 2011 \textit{New York Times} paywall introduction finds no detectable change in alignment relative to control newspapers. The findings show how truthful but selective disclosure can generate systematic informational distortions through purely economic incentives.

I develop a model where media outlets jointly choose which topic to cover (agenda setting) and how to report (editorial slant) under limited consumer attention. I characterize the conditions under which a “curse of popularity” emerges: when a topic becomes sufficiently popular, competing outlets converge on that same issue and—rather than conveying the most informative coverage—have incentives to introduce editorial bias, crowding out other topics and reducing welfare. By contrast, when attention is more dispersed, outlets tend to specialize across topics and (in equilibrium) report more truthfully, improving informational quality and decision-making.

I exploit a unique dataset in which each article appears simultaneously in two attention rankings—Most Viewed and Most Shared—to study how private and public use of news diverge for identical content. I combine these empirical patterns with a simple model of informational and signaling utility. Preliminary results reveal a systematic “scope wedge”: locally useful articles attract more private attention, while nationally framed or identity-related pieces are disproportionately shared. Moreover, contrary to common claims, shared articles are not simpler—they are more sophisticated, consistent with signaling rather than “dumbing down.”