Paper Info
Title
Using association rules to discover color-emotion relationships based on social tagging
Abstract
Relationships between colors and emotions have been studied for a long time in several domains, such as psychology and artistic theories. In this paper, we extract such relations appearing in social tagging systems, in which users can freely choose the images they upload and annotate, as well as the annotation tags. We first study two color representations that can be used to encode the chromatic contents of such images and select the most appropriate one for discovering coloremotion relationships, based on their performance for a classification task. We then extract, from this image corpus and based on the selected encoding, association rules characterizing relations between colors and emotions. We use the Apriori algorithm with a particular focus on the implications of color presence and absence on the emotion presences, commenting and discussing the obtained results.
Year
DOI
Venue
2010
10.1007/978-3-642-15387-7_58
KES (1)
Keywords
Field
DocType
chromatic content,annotation tag,social tagging,artistic theory,color representation,emotion presence,coloremotion relationship,classification task,color presence,color-emotion relationship,association rule,apriori algorithm,association rules,affective computing
ENCODE,Annotation,Chromatic scale,Information retrieval,Computer science,Apriori algorithm,Upload,Association rule learning,Affective computing,Encoding (memory)
Conference
Volume
ISSN
ISBN
6276
0302-9743
3-642-15386-0
Citations 
PageRank 
References 
3
0.37
5
Authors
3
Name
Order
Citations
PageRank
Haifeng Feng130.37
Marie-Jeanne Lesot222032.41
Marcin Detyniecki333039.95