Authors:
Noriyuki Okumura
1
and
Manabu Okumura
2
Affiliations:
1
National Institute of Technology and Kagawa College, Japan
;
2
Tokyo Institute of Technology, Japan
Keyword(s):
Personality Estimation, Twitter, Blog, Emotion Judgment
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Artificial Intelligence
;
Communication and Software Technologies and Architectures
;
Data Engineering
;
e-Business
;
Enterprise Information Systems
;
Enterprise Ontology
;
Knowledge Acquisition
;
Knowledge Engineering
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Natural Language Processing
;
Ontologies and the Semantic Web
;
Pattern Recognition
;
Symbolic Systems
Abstract:
The personality that is estimated based on documents of blogs or tweets in Twitter can not agree in the sender’s
real personality. It is important that we recognize the difference between these estimated and real personalities.
This paper constructs a knowledge-base for extracting the sender’s virtual personality in customer-generated
media. We focus on sender’s emotions that are included in sender’s posts for automatic personality estimation.
We examined the correlation between the ratio of each emotion term (anger, sadness, fear, disappointment,
regret, guilt, shame, pleasure, and ease) in all sentences of each participant and the values of NEO-FFI (Extraversion,
Agreeableness, Conscientiousness, Neuroticism, and Openness to Experience) based on the experiment
that human subjects who stayed in each sender’s character answered to NEO-FFI.As an evaluation result,
we find out that the sender’s virtual personality is potentially-correlated with emotions in sender’s posts.