ALT Text analysis typically focuses on content—such as sentiment or topic—but expression is also a form of effortful action. Building on this insight, I propose using simple features of open-ended tasks to study text as behavior. This approach treats expression, such as writing, as cognitively, emotionally and temporally “costly” for subjects but inexpensive for researchers. I show basic statistics like the number of characters can approximate effort and significantly improve estimation of quantities of interest, including candidate choice, the probability of turning out to vote and psychological states about which a subject may not be fully aware. Further, these methods can convert nonresponse into informative data; validate survey instruments; serve as mechanism checks; be hard for a subject to “game”; work across different languages and analogize well to real-world situations. In sum, text as behavior can help address a range of issues related to quantifying attitudes and actions.