  Veracity of data posted on the microblog platforms has in recent years been a
subject of intensive study by professionals specializing in various fields of
informatics as well as sociology, particularly in the light of increasing
importance of online tools for news spreading. On Twitter and similar sites, it
is possible to report on ongoing situations globally with minimal delay, while
the cost of such reporting remains negligible. One of the most important
features of this social network is that content delivery can be customized to
allow users to focus only on news items covering subject matters they find
interesting. With this in mind, it becomes necessary to create verification
mechanisms that can ascertain whether the claims made on Twitter can be taken
seriously and prevent false content from spreading too far. This study
demonstrates an innovative System for verification of information that can
fulfill the role described above. The System is comprised of four mutually
connected modules: a legacy module, a trustworthiness classifier; a module
managing user authority, and a ranking procedure. All of the modules function
within an integrated framework and jointly contribute to an accurate
classification of messages and authors. Effectiveness of the solution was
evaluated empirically on a sample of Twitter users, with a strict 10-fold
evaluation procedure applied for each module. The findings indicate that the
solution successfully meets the primary objectives of the study and performs
its function as expected.
