This dissertation examined (1) the influence of affective states on consumers’ selective attention to different types of ads that are categorized based on theoretically-derived attention-inducing characteristics; and (2) the influence of affective states on consumers’ ad processing style and evaluation of the ads that received attention. A computational research approach was used cross-analyzing proxy measures of real-time affective fluctuation of TV viewers during the 2018 and 2019 Super Bowl broadcast and their tweets regarding the ads aired during the Super Bowl broadcast. The results demonstrated some supports for the linkage between consumers’ temporary affective states, induced by the performance of the team they cheer for, and their selective attention to different types of ads even when they are exposed to the same set of ads during commercial breaks. Consistent with Mood Management Theory and prior psychology research evidence connecting affective states to visual attention, consumers in a negative affective state tend to pay more attention to positive ads and ads with emotional appeals than do those in a positive affective state. Furthermore, consumers in a positive affective state tend to pay more attention to exciting ads, compared to those in a negative affective state. However, this study’s data did not show significant relationship between consumers’ affective state and their selective attention to ads with different semantic affinity levels, nor any significant effects of affective state on ad processing style or evaluation of ads. The study contributes to advancing the ad attention and mood management research by testing the largely untested effects of consumers’ temporary affective states on selective attention and reactions to ads. The computational research approach developed in this study also offers significant methodological contributions to advertising scholarship, opening new avenue of research to apply the computational research approach to advertising theory building, especially theory regarding the role of consumers’ affective factors. Additionally, this study provides useful practical implications for ad targeting and ad placement strategies based on consumers’ temporary affective states. This study’s findings suggest a new promising way to target consumers and personalize ads based on individual consumers’ real-time, temporary affective states that can be captured by appropriate proxy measure data.