  Internet provides a growing variety of social data sources: calendars, event
aggregators, social networks, browsers, etc. Also, the mechanisms to gather
information from these sources, such as web services, semantic web and big data
techniques have become more accessible and efficient. This allows a detailed
prediction of the main expected events and their associated crowds. Due to the
increasing requirements for service provision, particularly in urban areas,
having information on those events would be extremely useful for Operations,
Administration and Maintenance (OAM) tasks, since the social events largely
affect the cellular network performance. Therefore, this paper presents a
framework for the automatic acquisition and processing of social data, as well
as their association with network elements (NEs) and their performance. The
main functionalities of this system, which have been devised to directly work
in real networks, are defined and developed. Different OAM applications of the
proposed approach are analyzed and the system is evaluated in a real
deployment.
