This dissertation is focused on topics in information diffusion and regulation, and consists of three independent essays, which correspond to the first three chapters. In the first chapter, I provide a signaling-game theoretical foundation, upon which an updated empirical framework is proposed, to study the effects of issuing quality report cards for health care providers. I find that, when providers face an identical distribution of patient illness severity types, a trade-off between multidimensional measures in the existing report cards renders them a mechanism that reveals the providers' qualities without causing providers to select patients. However, non-identical patient type distributions between providers, attributed to the referring physician, may force the high-quality provider to shun patients in order to signal himself. Despite this imperfection, the existing report cards cause the minimum selection compared with alternative report mechanisms. In contrast to prior research, my results imply that a single difference-in-differences estimate is not sufficient to indicate providers' selection behavior, and cannot capture the report cards' long run welfare effect with short run data. In my new empirical framework, a treatment effect will be estimated once every period. In the second chapter, Using a repeated-game model, I show that prohibition of "character evidence" in the evidence law will lead to a tacit collusion, in form of providing perjury, between producers who are skilled experts. In the context of health care, in equilibrium such collusion results in not only medical malpractice from the providers but also no litigation from the patients. In the third chapter, which is joint with Qiang Pan, we study the word-of-mouth effect on movies with platform release, a common marketing strategy in the motion picture industry. We construct a theoretical model which shows that the word-of-mouth effect together with a sliding-percentage contract between the movie distributor and exhibitors gives rise to the usage of platform release. Using the data in the U.S. motion picture industry from 2000 to 2005, we quantify the word-of-mouth scales and estimate the information transmission process in the movies featuring platform release. [PUBLICATION ABSTRACT]