There is a general consensus of the good freshness and sensing characteristics of Twitter as an information media for the complex financial market. However, the provenance of contributions, their different levels credibility and quality and even the purpose or intention behind them makes Twitter nor reliable enough as single source for decision taking. Our medium-term objective is a collaboration project among the University of Vigo and the Manchester Metropolitan University to deploy an architecture for real-time monitoring of irregularities in the stock market. That architecture will apply data mining and fusion technologies from a pool of social feeders related with the stock market. In order to design the architecture, the permeability of the different feeders should be analyzed, that means, to what extent a specific financial information feeder is permeable to fraudulent and common irregularities in the financial market. The Intelligent System Group has worked in the detection of irregularities form Financial Discussion Forums, meanwhile the Information & Computing Lab of the University of Vigo has a relevant know-how in applying Twitter analytics to a variety of real life problems.