Authors:
Corey Taylor
1
;
Richard Leibbrandt
2
and
David Powers
2
Affiliations:
1
Flinders University and Philips-University Marburg, Germany
;
2
Flinders University, Germany
Keyword(s):
Sentiment Analysis, Conditional Random Field, Topic Model, Information Retrieval, Text Processing, Enron.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Bayesian Networks
;
Computational Intelligence
;
Data Mining
;
Databases and Information Systems Integration
;
Enterprise Information Systems
;
Evolutionary Computing
;
Knowledge Discovery and Information Retrieval
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Machine Learning
;
Natural Language Processing
;
Pattern Recognition
;
Sensor Networks
;
Signal Processing
;
Soft Computing
;
Symbolic Systems
Abstract:
The emotional states of employees under stress are likely to manifest themselves in ways other in inter-personal interactions, namely, emails. The Enron Email Corpus was mined by both supervised and unsupervised methods to determine the degree to which this was true for Enron employees whilst the corporation was under investigation. Changes in language patterns were then compared against the timelines of the investigation. The method as described validates both the use of a subset of a very large corpus and the use of tagging methods to understand the patterns in various phrase types as used by Enron employees.