Friend recommendation based on the Luscher color theory: Twitter use case

Tajbakhsh, Mir Saman; Aghababa, Mohammad Pourmahmood; Solouk, Vahid; Akbari-Moghanjoughi, Ayyoub

doi:10.1109/micc.2013.6805828

Cited by 4 publications

(2 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, this is a very efficient test yet designed simply, and it is very suitable for analyzing abstract works since it is designed for personality and mood analysis. This test has been used in other areas [24], [25] and has shown its effectiveness. In this paper, we intend to study Iranian-Islamic authentic paintings and more specifically extract their emotions with the help of an expert system based on image processing and psychology knowledge.…”

Section: Paintings and Emotions Relationshipmentioning

confidence: 99%

A Novel Method for Emotion Extraction From Paintings Based on Luscher’s Psychological Color Test: Case Study Iranian-Islamic Paintings

et al. 2019

View full text Add to dashboard Cite

Paintings evoke certain emotions in the viewers. Colors, shape, texture, and many other factors affect the feeling conveyed by paintings, but colors seem to have a stronger effect due to a century-long study of color-emotion association in various fields of psychology, art, and color science. There are many color-emotion theories and most of them have been implemented, however, the Luscher Color Test is untouched amongst them. Based on several reasons, discussed in detail inside the paper, we believe this theory can cover problems in this domain of emotion extraction. The main motivation for choosing the Luscher test was that this method is designed for personality and mood analysis and it can better study abstract paintings. In this paper, a set of paintings from Iranian-Islamic cultural heritage is chosen as a dataset. We have proposed the L-EEP method based on Culture Technology (CT) concept to extract emotions from paintings with image processing techniques and psychology knowledge. This method extracts specific colors from paintings and by performing the Luscher test automatically, is able to determine eight emotions. For this matter, paintings are assessed in two moods: 1. The full extent of the painting 2. Cropped interest area of the painting that attracts more attention. Then, the color palette which is extracted colors ordered based on their coverage extent enters search engine. The search engine performs the searching process in the 3D knowledge base of Luscher color-emotion layers to extract relative values of emotions in both scenarios. For the evaluation of the results, three steps were taken. First, we compared the output results of ancient Persian painting with literature and text of their background stories. Then a viewer evaluation is done to compare the results with human viewpoint. Finally, a set of modern abstract paintings peer-rated in the IAPS standard system to further examine the proposed method. The results of the three forms of evaluation indicate the applicability of the L-EEP approach.

show abstract

Section: Paintings and Emotions Relationshipmentioning

confidence: 99%

A Novel Method for Emotion Extraction From Paintings Based on Luscher’s Psychological Color Test: Case Study Iranian-Islamic Paintings

et al. 2019

View full text Add to dashboard Cite

show abstract

“…Current paper extends the novel approach introduced in the former work [4] and models the friend recommendation problem in SNs as choosing friends among some alternatives using Analytic Hierarchy Process (AHP). It utilizes a psychology color similarity approach for finding and recommending friends and indicates that users with common color interest may have close interests.…”

Section: Introductionmentioning

confidence: 99%

AHP Celebrity Recommendation Based On Luscher Color Theory: Twitter Use Case

Tajbakhsh,

Solouk

2024

Preprint

View full text Add to dashboard Cite

Social Networks are among the emerging services in the current virtual world which are used as a connecting medium between users over the Internet. Users generally connect to social networks to interact with their family members, coworkers, or even for commercial goals. Hence, the key for the success of every social network provider lies on satisfying user interest and thereby, expanding the network. Accordingly, one way to increase users' interest toward a social network is introducing them to other users with the similar characteristics using recommender systems. The current article introduces a recommender system based on AHP method and semantic similarities as well as color psychology between users in an online social network. To evaluate the proposed system, we used 5705 real Twitter celebrity profiles as alternative for recommendation, together with 100 virtual profiles as ordinary users. The experimental results indicate maximum recommendations error rate as low as 12.5.

show abstract

An Approach for Opinion-Demographic-Topology Based Microblog Friend Recommendation

Moussa

2016

Advances in Intelligent Systems and Computing

View full text Add to dashboard Cite

Friend recommendation based on the Luscher color theory: Twitter use case

Cited by 4 publications

References 12 publications

A Novel Method for Emotion Extraction From Paintings Based on Luscher’s Psychological Color Test: Case Study Iranian-Islamic Paintings

A Novel Method for Emotion Extraction From Paintings Based on Luscher’s Psychological Color Test: Case Study Iranian-Islamic Paintings

AHP Celebrity Recommendation Based On Luscher Color Theory: Twitter Use Case

An Approach for Opinion-Demographic-Topology Based Microblog Friend Recommendation

Contact Info

Product

Resources

About