Measuring the number of "likes" in Twitter and the number of bills voted in favor by the members of the Chilean Chambers of Deputies. We empirically study how signals of agreement in Twitter translates into cross-cutting voting during a high political polarization period of time. Our empirical analysis is guided by a spatial voting model that can help us to understand Twitter as a market of signals. Our model, which is standard for the public choice literature, introduces authenticity, an intrinsic factor that distort politicians' willigness to agree (Trilling, 2009). As our main contribution, we document empirical evidence that "likes" between opponents are positively related to the number of bills voted by the same pair of politicians in Congress, even when we control by politicians' time-invariant characteristics, coalition affiliation and following links in Twitter. Our results shed light into several contingent topics, such as polarization and disagreement within the public sphere.