• Korean Association for Visual Culture
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• v.23
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• pp.463-524
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• 2013

En exprimant 'la découverte de l'homme', Valéry, dans la Philosophie de la danse, représente «un plaisir qui allait jusqu'à une sorte d'ivresse, et si intense parfois, qu'un épuisement total de ses forces, une sorte d'extase d'épuisement pouvait seule interrompre son délire, sa dépense motrice exaspérée». Dans le même sens du plaisir, Jayadéva, dans son dithyrambe du Gîta-Govinda, représente la danse de Harî, une des nombreuses formes de Vichnou. Excités par le brûlant désir des jeux de la volupté, Hari et son amante Râdhâ cherchent au cours de la danse Râsa l'énergie vitale. Voilà la source du plaisir mystérieux valéryen. Ensuite l'eau, «élément essentiel de toute vie», est la mesure du temps de même que le soleil, l'eau est le principe de l'harmonie comme celui du monde. Finalement, chez Valéry, sous les diverses infleunces de l'eau mythique, la mer devient l'Océan de lait, soit le lieu de naissance, soit la substance maternelle, soit l'essence da la création universelle. Or tout au long de 「La Dormeuse」, Valéry évoque l'image de 'Vichnou-Narayana' sous l'influence de la mythologie indienne. Et sous une autre influence de Flaubert, Valéry évoque « d'étranges mondes abstraits». Malgré tout, Valéry crée lui-même, dans 「La Dormeuse」, une nouvelle image d'un monde abstrait : 'Vichnou-Narayana' couché sur un lit de lotus, porté par les replis du grand serpent Ananta, qui élève au-dessus du dieu endormi méditant, ses sept têtes formant une éspèce de dais - du sein de Narayana, richement décoré d'un collier d'étoiles et d'une couronne de pierres précieuses en forme de disque, croit un lotus qui porte Brahma dans son calice ; Lakchmi est aux pieds de son divin époux. L'épisode des dieux indiens est à un stade encore plus avancé de la destruction du symbole. Ils sont réduits à des formes symboliques obscures, non commentées et même difficilement identifiables. Le dieu rose qui mord son orteil dans une attitude à la fois mystérieuse et grotesque, c'est Vichnou qui a, selon le vichnouisme, le premier rôle dans la création du monde. Il flottait avant la création sur les eaux, couché sur une feuille de figuier, sous la forme d'un jeune enfant qui porte son pied vers sa bouche. Cette scène évoque la méditation et le repli sur soi de la divinité avant le commencement. Valéry désigne la cosmogonie particulière d'une religion bien déterminée(le vichnouisme) sans la nommer et en la vidant de son sens pouratnt capital, laissant subsister un symbole guetté par le grotesque, un dieu en enfance ; d'autre part, cette cosmogonie est télescopée et intégrée par une cosmogonie d'origine différente : le désemboîtement des trois dieux renvoie à la théorie sivaiste du Lingam, l'arbre de vie. Les dieux de la tirinité iendienne se détachent les un après les autres et il ne reste plus que la fleur sous la garde de Vichnou. Le désemboîtement des dieux paraît bien se référer à cette conception, malgré l'absence du lingam. Enfin toute la forme veille ; et tous les yeux sont ouverts.

• Asia Marketing Journal
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• v.13 no.4
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• pp.159-189
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• 2012

What attracts consumers to bloggers' reviews? Consumers would be attracted both by the Bloggers' expertise (i.e., knowledge and experience) and by his/her unbiased manner of delivering information. Expertise and trustworthiness are both virtues of information sources, particularly when there is uncertainty in decision-making. Noting this point, we postulate that consumers' motives determine the relative weights they place on expertise and trustworthiness. In addition, our hypotheses assume that tie strength moderates consumers' expectation on bloggers' expertise and trustworthiness: with expectation on expertise enhanced for power-blog user-group (weak-ties), and an expectation on trustworthiness elevated for personal-blog user-group (strong-ties). Finally, we theorize that the effect of credibility on willingness to accept a review is moderated by tie strength; the predictive power of credibility is more prominent for the personal-blog user-groups than for the power-blog user groups. To support these assumptions, we conducted a field survey with blog users, collecting retrospective self-report data. The "gourmet shop" was chosen as a target product category, and obtained data analyzed by structural equations modeling. Findings from these data provide empirical support for our theoretical predictions. First, we found that the purposive motive aimed at satisfying instrumental information needs increases reliance on bloggers' expertise, but interpersonal connectivity value for alleviating loneliness elevates reliance on bloggers' trustworthiness. Second, expertise-based credibility is more prominent for power-blog user-groups than for personal-blog user-groups. While strong ties attract consumers with trustworthiness based on close emotional bonds, weak ties gain consumers' attention with new, non-redundant information (Levin & Cross, 2004). Thus, when the existing knowledge system, used in strong ties, does not work as smoothly for addressing an impending problem, the weak-tie source can be utilized as a handy reference. Thus, we can anticipate that power bloggers secure credibility by virtue of their expertise while personal bloggers trade off on their trustworthiness. Our analysis demonstrates that power bloggers appeal more strongly to consumers than do personal bloggers in the area of expertise-based credibility. Finally, the effect of review credibility on willingness to accept a review is higher for the personal-blog user-group than for the power-blog user-group. Actually, the inference that review credibility is a potent predictor of assessing willingness to accept a review is grounded on the analogy that attitude is an effective indicator of purchase intention. However, if memory about established attitudes is blocked, the predictive power of attitude on purchase intention is considerably diminished. Likewise, the effect of credibility on willingness to accept a review can be affected by certain moderators. Inspired by this analogy, we introduced tie strength as a possible moderator and demonstrated that tie strength moderated the effect of credibility on willingness to accept a review. Previously, Levin and Cross (2004) showed that credibility mediates strong-ties through receipt of knowledge, but this credibility mediation is not observed for weak-ties, where a direct path to it is activated. Thus, the predictive power of credibility on behavioral intention - that is, willingness to accept a review - is expected to be higher for strong-ties.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.59-83
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• 2018

With the increasing importance of sentiment analysis to grasp the needs of customers and the public, various types of deep learning models have been actively applied to English texts. In the sentiment analysis of English texts by deep learning, natural language sentences included in training and test datasets are usually converted into sequences of word vectors before being entered into the deep learning models. In this case, word vectors generally refer to vector representations of words obtained through splitting a sentence by space characters. There are several ways to derive word vectors, one of which is Word2Vec used for producing the 300 dimensional Google word vectors from about 100 billion words of Google News data. They have been widely used in the studies of sentiment analysis of reviews from various fields such as restaurants, movies, laptops, cameras, etc. Unlike English, morpheme plays an essential role in sentiment analysis and sentence structure analysis in Korean, which is a typical agglutinative language with developed postpositions and endings. A morpheme can be defined as the smallest meaningful unit of a language, and a word consists of one or more morphemes. For example, for a word '예쁘고', the morphemes are '예쁘(= adjective)' and '고(=connective ending)'. Reflecting the significance of Korean morphemes, it seems reasonable to adopt the morphemes as a basic unit in Korean sentiment analysis. Therefore, in this study, we use 'morpheme vector' as an input to a deep learning model rather than 'word vector' which is mainly used in English text. The morpheme vector refers to a vector representation for the morpheme and can be derived by applying an existent word vector derivation mechanism to the sentences divided into constituent morphemes. By the way, here come some questions as follows. What is the desirable range of POS(Part-Of-Speech) tags when deriving morpheme vectors for improving the classification accuracy of a deep learning model? Is it proper to apply a typical word vector model which primarily relies on the form of words to Korean with a high homonym ratio? Will the text preprocessing such as correcting spelling or spacing errors affect the classification accuracy, especially when drawing morpheme vectors from Korean product reviews with a lot of grammatical mistakes and variations? We seek to find empirical answers to these fundamental issues, which may be encountered first when applying various deep learning models to Korean texts. As a starting point, we summarized these issues as three central research questions as follows. First, which is better effective, to use morpheme vectors from grammatically correct texts of other domain than the analysis target, or to use morpheme vectors from considerably ungrammatical texts of the same domain, as the initial input of a deep learning model? Second, what is an appropriate morpheme vector derivation method for Korean regarding the range of POS tags, homonym, text preprocessing, minimum frequency? Third, can we get a satisfactory level of classification accuracy when applying deep learning to Korean sentiment analysis? As an approach to these research questions, we generate various types of morpheme vectors reflecting the research questions and then compare the classification accuracy through a non-static CNN(Convolutional Neural Network) model taking in the morpheme vectors. As for training and test datasets, Naver Shopping's 17,260 cosmetics product reviews are used. To derive morpheme vectors, we use data from the same domain as the target one and data from other domain; Naver shopping's about 2 million cosmetics product reviews and 520,000 Naver News data arguably corresponding to Google's News data. The six primary sets of morpheme vectors constructed in this study differ in terms of the following three criteria. First, they come from two types of data source; Naver news of high grammatical correctness and Naver shopping's cosmetics product reviews of low grammatical correctness. Second, they are distinguished in the degree of data preprocessing, namely, only splitting sentences or up to additional spelling and spacing corrections after sentence separation. Third, they vary concerning the form of input fed into a word vector model; whether the morphemes themselves are entered into a word vector model or with their POS tags attached. The morpheme vectors further vary depending on the consideration range of POS tags, the minimum frequency of morphemes included, and the random initialization range. All morpheme vectors are derived through CBOW(Continuous Bag-Of-Words) model with the context window 5 and the vector dimension 300. It seems that utilizing the same domain text even with a lower degree of grammatical correctness, performing spelling and spacing corrections as well as sentence splitting, and incorporating morphemes of any POS tags including incomprehensible category lead to the better classification accuracy. The POS tag attachment, which is devised for the high proportion of homonyms in Korean, and the minimum frequency standard for the morpheme to be included seem not to have any definite influence on the classification accuracy.