Paper Info
Title
Modeling Facebook Posting Life-Cycle.
Abstract
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.
Year
DOI
Venue
2014
10.3233/978-1-61499-405-3-17
Frontiers in Artificial Intelligence and Applications
Keywords
DocType
Volume
Online Social Networks,Facebook,Regression Model
Conference
262
ISSN
Citations 
PageRank 
0922-6389
0
0.34
References 
Authors
0
2
Name
Order
Citations
PageRank
Joaquim Castro-Fonseca100.34
António Grilo200.68