Decision support systems (DSS) are beginning to use content sourced from social networks such as Twitter to provide decision makers with information to make timely and critical decisions. Misleading information obtained from Twitter can lead to adverse outcomes as well as cause trust issues within DSSs. In this paper, we propose and investigate a context-aware Twitter validator (CATVal) system to validate credibility and authenticity of Twitter content at run-time for use in DSS. We build, store and update a credibility index for Twitter users and verify user's context information each time a user tweets. The proposed system can benefit a DSS by providing credible and dependable information while detecting misleading and false information sourced from Twitter and possible other social media.