DocumentCode
3105443
Title
Who Thinks Who Knows Who? Socio-cognitive Analysis of Email Networks
Author
Pathak, Nishith ; Mane, Sandeep ; Srivastava, Jaideep
Author_Institution
Dept. of Comput. Sci., Univ. of Minnesota, Minneapolis, MN
fYear
2006
fDate
18-22 Dec. 2006
Firstpage
466
Lastpage
477
Abstract
Interpersonal interaction plays an important role in organizational dynamics, and understanding these interaction networks is a key issue for any organization, since these can be tapped to facilitate various organizational processes. However, the approaches of collecting data about them using surveys/interviews are fraught with problems of scalability, logistics and reporting biases, especially since such surveys may be perceived to be intrusive. Widespread use of computer networks for organizational communication provides a unique opportunity to overcome these difficulties and automatically map the organizational networks with a high degree of detail and accuracy. This paper describes an effective and scalable approach for modeling organizational networks by tapping into an organization´s email communication. The approach models communication between actors as non-stationary Bernoulli trials and Bayesian inference is used for estimating model parameters over time. This approach is useful for socio-cognitive analysis (who knows who knows who) of organizational communication networks. Using this approach, novel measures for analysis of (i) closeness between actors´ perceptions about such organizational networks (agreement), (ii) divergence of an actor´s perceptions about organizational network from reality (misperception) are explained. Using the Enron email data, we show that these techniques provide sociologists with a new tool to understand organizational networks.
Keywords
Bayes methods; business communication; computer networks; electronic mail; organisational aspects; parameter estimation; social sciences computing; Bayesian inference; Enron email data; computer networks; email networks; interpersonal interaction; logistics problems; model parameter estimation; nonstationary Bernoulli trials; organizational communication; organizational dynamics; reporting biases problems; scalability problems; socio-cognitive analysis; sociologists; Bayesian methods; Communication networks; Computer networks; Computer science; Electronic mail; Logistics; Professional communication; Resource management; Scalability; Social network services;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Mining, 2006. ICDM '06. Sixth International Conference on
Conference_Location
Hong Kong
ISSN
1550-4786
Print_ISBN
0-7695-2701-7
Type
conf
DOI
10.1109/ICDM.2006.168
Filename
4053073
Link To Document