Online auctions have become a major e-commerce strategy in terms of both number, diversity of participants and revenue. Recent research has characterized online auctions as synchronous interactive computer systems, considering successive interactions as a "loop feedback" mechanism, called reactivity, where the user behavior affects the system behavior and vice-versa. Although some factors that explain user behavior in terms of instantaneous bidding conditions are identified by previous research, there has been no effort to study how bidders' behavior changes over time. This work presents a longitudinal analysis of bidding behavior over a series of auctions. The results show bidding behavior evolves over time and these changes are not random. The identifiable evolution patterns can be partially explained by the presence of instantaneous reactivity patterns that bidders experience throughout the series of auctions they participate. Bidders learn from these reactivity instances and adapt their future participation.