Award Abstract #0713548
RI: Email, Social Networks, and Organizations: Investigating How We Use Language to Create and Navigate Social and Organizational Relations

NSF Org:	IIS Division of Information & Intelligent Systems
Initial Amendment Date:	August 10, 2007
Latest Amendment Date:	August 6, 2008
Award Number:	0713548
Award Instrument:	Continuing grant
Program Manager:	Tatiana D. Korelsky IIS Division of Information & Intelligent Systems CSE Directorate for Computer & Information Science & Engineering
Start Date:	September 1, 2007
Expires:	August 31, 2011 (Estimated)
Awarded Amount to Date:	$493679
Investigator(s):	Owen Rambow rambow@cs.columbia.edu (Principal Investigator)
Sponsor:	Columbia University 2960 Broadway NEW YORK, NY 10027 212/854-6851
NSF Program(s):	ROBUST INTELLIGENCE
Field Application(s):
Program Reference Code(s):	HPCC, 9218, 7495
Program Element Code(s):	7495

ABSTRACT

This project studies three aspects of human linguistic communication: the language used in the communication (for example, whether formal or informal), the topology of the social network of the communicators (for example, whether the the speaker is embedded in a single tight-knit group), and the roles the communicators occupy in an organization (for example, whether the speaker is an upper-level manager, or an administrative assistant). In the past, computer scientists and sociologists have analyzed these aspects in isolation, while sociolinguists and linguistic anthropologists have elaborated qualitative joint models. The ever-increasing flow of electronic communication offers new opportunities to analyze and quantitatively model these aspects of communication.

The project uses the Enron email corpus as a testbed for the development of computational joint models of these three aspects of communication, focusing on linguistic features (such as topic, genre, and speech act) and topological abstractions (such as subgroup analysis) that can be reliably and automatically analyzed in electronic communication. The work is being evaluated via concrete prediction tasks, such as the prediction of a person's organizational role based on the topology and linguistic content of their communication, and the prediction of how likely two people are to communicate in the future based on a limited sample of their communications.

The work is expected to have various potential applications, both for the general public, in the form of improved human-computer interaction for email clients and software that accesses email, and for the law enforcement and intelligence communities, in the development of automated techniques for discovering leadership and predicting communicative behavior.

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