As Facebook becomes a quite relevant tool for companies marketing and sales it is important to analyze and understand posting activity. Propagation of relevant episodes in Facebook is quite fast and companies must not only plan, monitor and control the posting activities in their own Facebook page but also understand what is happening in their competitors Facebook. This paper presents a model and algorithm that allows the implementation of automated monitoring of Facebook posting activity, identifying normal and outliers in their activity, and hence enhancing companies' Facebook competitive intelligence. The model is validated with a data sample of 27924 public publications from the 550 companies Facebook pages.
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
Tel.: +1 703 830 6300
Fax: +1 703 830 2300 email@example.com
(Corporate matters and books only) IOS Press c/o Accucoms US, Inc.
For North America Sales and Customer Service
West Point Commons
Lansdale PA 19446
Tel.: +1 866 855 8967
Fax: +1 215 660 5042 firstname.lastname@example.org