Viral marketing, marketing techniques that use pre-existing social networks, has experienced a significant encouragement in the last years. In this scope, Twitter is the most studied social network in viral marketing and the rumor spread is a widely researched problem. This paper contributes with a (1) novel agent-based social simulation model for rumors spread in Twitter. This model relies on the hypothesis that (2) when a user is recovered, this user will not influence his or her neighbors in the social network to recover. To support this hypothesis: (3) two Twitter rumor datasets are studied; (4) a baseline model which does not include the hypothesis is revised, reproduced, and implemented; (5) and a number of experiments are conducted comparing the real data with the two models results.