What Color as an Integrated Pictorial Element in Himalayan Art Can Communicate: Cross-Cultural Congruence of Color-Emotion Conceptualizations in Himalayan Art

2019 ◽  
Vol 39 (1) ◽  
pp. 36-60 ◽  
Author(s):  
Melissa J. Dolese ◽  
Natalie A. Kacinik
Keyword(s):  
Latent Semantic Analysis ◽  
Semantic Analysis ◽  
Verbal Material ◽  
Cross Cultural ◽  
Cultural Congruence ◽  
Emotional Information ◽  
Word Meanings ◽  
Pictorial Element ◽  
Color Emotion ◽  
Different Cultures

The idea of art as a language of emotion has historical roots. This study asked if color, as an integrated pictorial element in Himalayan art, can communicate the intended emotions to North American viewers. To investigate the extent to which those emotions are congruent cross-culturally, participants were assigned to four conditions of varying levels of informativeness, based on whether they did or did not receive an informational brochure and a checklist of emotional terms to reference. Results were analyzed using Latent Semantic Analysis to assess the similarity of word meanings. Participant responses were compared to the emotions that should be conveyed according to Himalayan culture and curators of an exhibit on Himalayan art. Cosine values were generally high in all conditions, indicating that certain colors (i.e., red, black, and gold) can convey consistent emotional information to viewers from very different cultures, even with little or no corresponding verbal material.

Task Estimation Using Latent Semantic Analysis of Visual Scenes and Spoken Words

2012 ◽  
Vol 132 (9) ◽  
pp. 1473-1480
Author(s):  
Masashi Kimura ◽  
Shinta Sawada ◽  
Yurie Iribe ◽  
Kouichi Katsurada ◽  
Tsuneo Nitta
Keyword(s):  
Latent Semantic Analysis ◽  
Semantic Analysis ◽  
Spoken Words ◽  
Visual Scenes

Similarity Detection Using Latent Semantic Analysis Algorithm

2018 ◽  
Vol 6 (8) ◽  
pp. 102
Author(s):  
Priyanka R. Patil ◽  
Shital A. Patil
Keyword(s):  
Latent Semantic Analysis ◽  
Latent Dirichlet Allocation ◽  
Semantic Analysis ◽  
Mining Method ◽  
Research Papers ◽  
Information Measures ◽  
Automated Software ◽  
Day By Day ◽  
Ways Of Life ◽  
Dirichlet Allocation

Similarity View is an application for visually comparing and exploring multiple models of text and collection of document. Friendbook finds ways of life of clients from client driven sensor information, measures the closeness of ways of life amongst clients, and prescribes companions to clients if their ways of life have high likeness. Roused by demonstrate a clients day by day life as life records, from their ways of life are separated by utilizing the Latent Dirichlet Allocation Algorithm. Manual techniques can't be utilized for checking research papers, as the doled out commentator may have lacking learning in the exploration disciplines. For different subjective views, causing possible misinterpretations. An urgent need for an effective and feasible approach to check the submitted research papers with support of automated software. A method like text mining method come to solve the problem of automatically checking the research papers semantically. The proposed method to finding the proper similarity of text from the collection of documents by using Latent Dirichlet Allocation (LDA) algorithm and Latent Semantic Analysis (LSA) with synonym algorithm which is used to find synonyms of text index wise by using the English wordnet dictionary, another algorithm is LSA without synonym used to find the similarity of text based on index. LSA with synonym rate of accuracy is greater when the synonym are consider for matching.

Across Culture Communication Style Choices in Western and British Culture in The Leap Year movie.

2018 ◽  
Vol 7 (2) ◽  
Author(s):  
Nargis - ◽  
Imtihan - Hanim
Keyword(s):  
Intercultural Communication ◽  
Research Method ◽  
Power Distance ◽  
Cross Cultural ◽  
Communication Style ◽  
Cultural Communication ◽  
High Culture ◽  
Cross Cultural Communication ◽  
Different Cultures ◽  
British Culture

The different cultures, power distance could be the obstacle in intercultural communication. The aim of this research to identify the types of Cross-Cultural Communication Style Choice between British and American in the Leap Year movie. The researchers attempt to reveal kinds of Cross-Cultural Communication Style Choice between Declan as British and Anna as American for three days. This Qualitative research method analyses data of utterances and are classified into four types of Cross-Cultural Communication Style Choice. The result shows that there are 356 utterances of Anna and Declan. for three days. Anna has 204 utterances with 44,3 % direct style and indirect 5,8 %.. Declan uses 155 utterance with 37 % and 12 % indirect style. British tend to use more indirect styles in expressing their intention to save the interlocutor’s face.Meanwhile, American use direct styles to reveal their intentions as they belong to the high culture communication.Key words: across culture communication,direct style, indirectstyle

LATENT-SEMANTIC ANALYSIS, SOCIAL NETWORKS AND NON-STRUCTURED DATA: INTERACTION METHOD

2019 ◽  
Keyword(s):  
Social Networks ◽  
Latent Semantic Analysis ◽  
Semantic Analysis ◽  
Statistical Processing ◽  
Unstructured Data ◽  
Average Score ◽  
Text Type ◽  
Internet Users ◽  
The Matrix ◽  
Human Thinking

This article examines the method of latent-semantic analysis, its advantages, disadvantages, and the possibility of further transformation for use in arrays of unstructured data, which make up most of the information that Internet users deal with. To extract context-dependent word meanings through the statistical processing of large sets of textual data, an LSA method is used, based on operations with numeric matrices of the word-text type, the rows of which correspond to words, and the columns of text units to texts. The integration of words into themes and the representation of text units in the theme space is accomplished by applying one of the matrix expansions to the matrix data: singular decomposition or factorization of nonnegative matrices. The results of LSA studies have shown that the content of the similarity of words and text is obtained in such a way that the results obtained closely coincide with human thinking. Based on the methods described above, the author has developed and proposed a new way of finding semantic links between unstructured data, namely, information on social networks. The method is based on latent-semantic and frequency analyzes and involves processing the search result received, splitting each remaining text (post) into separate words, each of which takes the round in n words right and left, counting the number of occurrences of each term, working with a pre-created semantic resource (dictionary, ontology, RDF schema, ...). The developed method and algorithm have been tested on six well-known social networks, the interaction of which occurs through the ARI of the respective social networks. The average score for author's results exceeded that of their own social network search. The results obtained in the course of this dissertation can be used in the development of recommendation, search and other systems related to the search, rubrication and filtering of information.

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