This dissertation explores the effect product reviews have on consumer emotions, judgments, and decisions. Especially with the continued growth of e-commerce, product reviews play an important role in consumer decisions. More than 90% of consumers in the United States have used online reviews to help them make a purchase (Kaemingk, 2020). The majority of consumers trust these online reviews at least as much as they trust personal and expert recommendations (Galante, 2018; Statista, 2021). Given the extensive use of review information, it is critical for marketers and researchers to understand how these reviews impact consumers. Chapter 1 examines how summary information about reviews for a product influences perceptions of individual reviews. Specifically, we study how manipulating the mean rating influences subsequent judgments of review helpfulness and search behavior. We find evidence of confirmation bias (Nickerson, 1998). Reviews with ratings close to or at the mean (i.e., confirmed the mean) are rated as more helpful, lead to more extreme belief updating, and are more likely to be searched than reviews with ratings further from the mean. We also find process evidence that suggests the mean rating significantly influences how consumers weight the information in reviews, with greater weight being placed on information that confirms the mean rating. Lastly, we find participants are more likely to search for reviews near the mean when they could freely select which reviews to read. Taken together, these results suggest there is significant confirmation bias in consumers’ judgments and behaviors when they are exposed to a product’s mean rating. Chapter 2 examines the role of emotion in product reviews and the effect it has on purchase behavior. Consumers consider the content or text of a review to be a highly influential feature of online reviews, above and beyond star ratings and total number of reviews (Podium, 2017). Additionally, sentiment analysis tools have surged in popularity, especially in marketing. However, these tools often provide a simplistic view of the emotional content and how it may impact consumers. Thus, Chapter 2 studies how the emotional content of a review influences the emotions experienced by consumers as they read the review, as well as their eventual product evaluations. First, we find the emotion experienced by the consumer reading the review to be a stronger predictor of perceived product quality than the emotion expressed by the author of the review. Second, we demonstrate the need to measure positive and negative emotion on separate scales, as opposed to treating them as opposite ends of a single scale. When measured with a single scale, it is ambiguous whether the midpoint refers to a review that is fairly bland or one with a high degree of conflicting emotions. Lastly, we establish the need to consider arousal as an additional dimension when measuring emotions in reviews. Valence and arousal jointly impact product evaluations by influencing the amount of positive and negative emotion felt by the reader. These results highlight the advantage of going beyond a single, unidimensional scale when measuring emotion in product reviews.