• English Language & Literature Teaching
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• v.15 no.4
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• pp.365-382
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• 2009

This study aims to examine the reading materials of high school English textbooks to propose the integration of the literary texts into reading materials in the classroom for development of communicative competence. Five kinds of high school English textbooks were critically examined in terms of three factors -limited text types, deficit of emotional adjectives and non-authenticity- selected by the author as characteristics of non-communicative language teaching materials. With regard to text types, more than half of the reading materials were expository and simple narratives. This imbalance of text types led materials to the deficit of emotional vocabulary. These factors seem to be closely related to the issue of authenticity of reading materials. Compared to the authentic texts, fabricated texts are likely to make reading vapid and boring task. On the basis of these results, some pedagogical suggestions are made.

• Smart Media Journal
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• v.9 no.4
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• pp.144-151
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• 2020

In a mobile environment, communication takes place via SMS text messages. Vocabularies used in SMS texts can be expected to use vocabularies of different classes from those used in general Korean literary style sentence. For example, in the case of a typical literary style, the sentence is correctly initiated or terminated and the sentence is well constructed, while SMS text corpus often replaces the component with an omission and a brief representation. To analyze these vocabulary usage characteristics, the existing colloquial style corpus and the literary style corpus are used. The experiment compares and analyzes the vocabulary use characteristics of the colloquial corpus SMS text corpus and the Naver Sentiment Movie Corpus, and the written Korean written corpus. For the comparison and analysis of vocabulary for each corpus, the part of speech tag adjective (VA) was used as a standard, and a distinctive collexeme analysis method was used to measure collostructural strength. As a result, it was confirmed that adjectives related to emotional expression such as'good-','sorry-', and'joy-' were preferred in the SMS text corpus, while adjectives related to evaluation expressions were preferred in the Naver Sentiment Movie Corpus. The word embedding was used to automatically construct a sentiment lexicon based on the extracted adjectives with high collostructural strength, and a total of 343,603 sentiment representations were automatically built.

• Journal of Korea Multimedia Society
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• v.18 no.11
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• pp.1391-1399
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• 2015

In recent times, studies sentiment analysis are being actively conducted by implementing natural language processing technologies for analyzing subjective data such as opinions and attitudes of users expressed on the Web, blogs, and social networking services (SNSs). Conventionally, to classify the sentiments in texts, most studies determine positive/negative/neutral sentiments by assigning polarity values for sentiment vocabulary using sentiment lexicons. However, in this study, sentiments are classified based on Thayer's model, which is psychologically defined, unlike the polarity classification used in opinion mining. In this paper, as a method for classifying the sentiments, sentiment categories are proposed by extracting sentiment keywords for major sentiments by using hashtags, which are essential elements of Instagram. By applying sentiment categories to user posts, sentiments can be determined through the similarity measurement between the sentiment adjective candidates and the sentiment keywords. The test results of the proposed method show that the average accuracy rate for all the sentiment categories was 90.7%, which indicates good performance. If a sentiment classification system with a large capacity is prepared using the proposed method, then it is expected that sentiment analysis in various fields will be possible, such as for determining social phenomena through SNS.

• The Journal of the Korea Contents Association
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• v.8 no.3
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• pp.138-145
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• 2008

The development of human-friendly game technologies understanding and responding to human emotion is a very crucial element in designing games. Out of emotion derived from games, this study attempted to define characteristics of games as a meaning representing the degree of reaching the targeted emotion. When examining most of researches regarding emotion, it has been noted that they tried to extract the most representative emotion through the systematization of emotional vocabulary and evaluate it by the association with the design elements in question. However, this definition would be beneficial only to understanding the direction of game entity and it could not express the emotion of concrete and objective players. Therefore, this study attempted to analyze the sense correlation of adjectives so as for emotional expressions to be represented accurately corresponding to players' intention, by using adjective thesaurus for the systematic understanding of such game entity.

• Journal of the Korea Fashion and Costume Design Association
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• v.17 no.3
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• pp.85-98
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• 2015

Modern fashion shows the trend of various styles and the period focusing on only product functions is changed to the period focusing on consumer's sensibility. Consumers show different sensitivities and preference by individual at the stage cognizing and recognizing the stimulation of given image and the method of objective measurement based on the fashion sensible vocabularies is necessary to measure fashion sensibility. Therefore, this research is significant to examine differences of preference to classic fashion by generation and awareness for sensible vocabularies and suggest methodology of design sensible evaluation research through the quantitative evaluation objectifying subjective sensibility. For the method of research, precedent theses related to classic, concept and characteristics of classic in books and definition and characteristics by generation were examined, the best 3 domestic portal sites were selected and adjective vocabularies and images related to classic were collected from 2010 to 2014. Among the 206 adjectives collected, vocabularies whose average is more than 3.5 were drawn by 5-point Likert scale for fashion expert group. And, among the total 306 images collected, 21 representative images were selected by preliminary investigation of fashion expert group. For the classic images and vocabularies selected, frequency analysis, factor analysis and variance analysis were conducted by SPSS 19.0. The results of analysis are as follows. Preference to classic fashion image by generation was analyzed. As a result, both of two generations selected classic fashion as the most classic one. The images of the next orders were analyzed. As a result, Y generation selected basic classic fashion image which is casual with high activity as a classic one. Baby boom generation selected ancient classic fashion image, so there were differences in preference for classic by generation. As a factor analysis on classic adjective vocabularies, they could be divided into 5 factors such as basic form, attractive form, traditional form, vintage form and active form and they verified that credibility of all measuring variables for classic sensible vocabularies was achieved. Differences of classic sensible vocabularies by classic fashion image and generation were examined. As a result, generation and classic fashion image made a significant effect on five factors. Therefore, there were differences of the awareness on classic fashion images and sensible vocabularies among the generations and this thesis can be a fundamental material which objectifies subjective sensibility and suggests the methodology of new research.