Modeling Facebook Posting Life-Cycle

被引：0
|
作者：
Castro-Fonseca, Joaquim [1 ]
Grilo, Antonio [1 ]
机构：
[1] Univ Nova Lisboa, UNIDEMI, Fac Ciencias & Tecnol, Dept Engn Mecan & Ind, Caparica, Portugal
来源：
SMART DIGITAL FUTURES 2014 | 2014年 / 262卷
关键词：
Online Social Networks; Facebook; Regression Model;
D O I：
10.3233/978-1-61499-405-3-17
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
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页码：17 / 24
页数：8
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