Home

About

Advanced Search

Browse by Discipline

Scientific Societies

E-print Alerts

Add E-prints

E-print Network
FAQHELPSITE MAPCONTACT US


  Advanced Search  

 
LEXICAL PREDICTORS OF PERSONALITY TYPE Shlomo Argamon1
 

Summary: LEXICAL PREDICTORS OF PERSONALITY TYPE
Shlomo Argamon1
, Sushant Dhawle1
, Moshe Koppel2
, James W. Pennebaker3
1. Dept. of Computer Science, Illinois Institute of Technology, Chicago, IL 60616
2. Dept. of Computer Science, Bar-Ilan University, Ramat Gan 52900, Israel
3. Dept. of Psychology, The University of Texas, Austin, TX 78712
Abstract
We are currently pursuing methods for "author profiling" in which various aspects
of the author's identity might be identified from a text, without necessarily having a
corpus of documents from the same individual. A key component of such an identity
profile is personality; this paper addresses distinguishing high from low neuroticism
and extraversion in authors of informal text. We consider four different sets of lexical
features for this task: a standard function word list, conjunctive phrases, modality indi-
cators, and appraisal adjectives and modifiers. SMO, a support vector machine learner,
was used to learn linear separators for the high and low classes in each of the two tasks.
We find that appraisal use is the best predictor for neuroticism, and that function words
work best for extraversion. Further, examination of the specifically most important fea-
tures yields insight into how neuroticism and extraversion differentially affect language

  

Source: Argamon, Shlomo - Department of Computer Science, Illinois Institute of Technology

 

Collections: Computer Technologies and Information Sciences