• 재활복지
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• v.22 no.4
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• pp.43-58
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• 2018

Swallowing disorders that can affect nutrient intakes and quality of life are commonly shown among the elderly as well as patients with neurogenic disorder. This study verifies the reliability and validity of the Swallowing Disturbance Questionnaire (SDQ), a subjective swallowing disability assessment tool, modified for Koreans' eating habit and cultural sentiment, against 105 stroke patients, in order to help identify early swallowing problems of the elderly. Reliability of internal consistency in the Korean version of SDQ is .601, test-retest reliability is .97, and concurrent validity is .956. Based on 8 points of cut-off score, 46.8% of sensitivity and 81.6% of specificity. Comparing the results of video fluoroscopic study (VFSS), an objective swallowing disorder test with those of Korean version of SDQ, negative predictive value (NPV) and positive predictive value (PPV) was shown as 81% and 53%. The Korean version of SDQ is expected to be a useful testing tool to discriminate swallowing disorders in stroke patients. It has great clinical significance in that swallowing difficulties shown by subjects can be sorted out to request a diagnostic assessment before clinical evaluation by a rehabilitation therapist or ruling out unnecessary exposure to additional tests by accurately identifying stroke patients without swallowing problems.

• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.53-59
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• 2021

In this paper, we propose a BERGPT-chatbot, a domestic AI chatbot that can alleviate negative emotions based on text input such as 'Replika'. We made BERGPT-chatbot into a chatbot capable of mitigating negative emotions by pipelined two models, KR-BERT and KoGPT2-chatbot. We applied a creative method of giving emotions to unrefined everyday datasets through KR-BERT, and learning additional datasets through KoGPT2-chatbot. The development background of BERGPT-chatbot is as follows. Currently, the number of people with depression is increasing all over the world. This phenomenon is emerging as a more serious problem due to COVID-19, which causes people to increase long-term indoor living or limit interpersonal relationships. Overseas artificial intelligence chatbots aimed at relieving negative emotions or taking care of mental health care, have increased in use due to the pandemic. In Korea, Psychological diagnosis chatbots similar to those of overseas cases are being operated. However, as the domestic chatbot is a system that outputs a button-based answer rather than a text input-based answer, when compared to overseas chatbots, domestic chatbots remain at a low level of diagnosing human psychology. Therefore, we proposed a chatbot that helps mitigating negative emotions through BERGPT-chatbot. Finally, we compared BERGPT-chatbot and KoGPT2-chatbot through 'Perplexity', an internal evaluation metric for evaluating language models, and showed the superity of BERGPT-chatbot.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.9-15
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• 2019

Large global online shopping malls, such as Amazon, offer services in English or in the language of a country when their products are sold. Since many customers purchase products based on the product reviews, the shopping malls actively utilize the sentimental analysis technique in judging preference of each product using the large amount of review data that the customer has written. And the result of such analysis can be used for the marketing to look the potential shoppers. However, it is difficult to apply this English-based semantic analysis system to different languages used around the world. In this study, more than 500,000 data from Amazon fine food reviews was used for training a deep learning based system. First, sentiment analysis evaluation experiments were carried out with three models of English test data. Secondly, the same data was translated into seven languages (Korean, Japanese, Chinese, Vietnamese, French, German and English) and then the similar experiments were done. The result suggests that although the accuracy of the sentimental analysis was 2.77% lower than the average of the seven countries (91.59%) compared to the English (94.35%), it is believed that the results of the experiment can be used for practical applications.

• Journal of Global Scholars of Marketing Science
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• v.17 no.3
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• pp.61-81
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• 2007

Recently, use of foreign models and foreign language in advertising is a general trend in Korea even though the effect has not been well-known..Most of the previous research shows rather an opposite effect claiming marketing communication is more effective when higher congruity between marketing communication and consumer's cultural values are achieved. However, the introduction of global culture due to the expansion of new media such as Internet or cable television makes the congruity not the best choice of marketing strategy. In addition, use of highly attractive models in advertising to increase the effect of advertising is general. However, recent studies show that targeted women audience tend to compare themselves to the highly attractive models and do experience negative sentiment. Bower (2001) proved the difference between 'comparer' and 'noncomparer' when women face highly attractive models. The results show that a comparer who has an intention to compare highly attractive model (HAM) with herself has a significantly negative effect on model expertise, product argument, product evaluation and buying intention. Therefore, HAM is not always a good choice and model attractiveness plays a role in the processing other cues or changing the advertising effect from result of processing other cues. The purpose of this study is to investigate the effect of the use of foreign language on the advertising response of the audience with regard of the model attractiveness. For the empirical study, the virtual advertising using foreign models (HAM, NAM), brand names and slogans(Korean, English) were used as stimuli. The respondents of each stimulus were 75('HAM-Korean'), 75('NAM-Korean'), 66('HAM-English') and 66 ('NAM-English') respectively. To establish the effect of marketing communication, the attitude for media(AM), the attitude for product(AP), targetedness(TD), overall quality(OQ), and purchase intention(PI) with 7 point likert scale were measured. The manipulation was verified to check the difference between HAM attractiveness assessment (m=3.27) and NAM attractiveness assessment (m=5.12). The mean difference was statiscally significant (p<.05). As a result, all consequences were significantly changed with model attractiveness, and overall quality evaluation(OQ) were significantly changed with language. The interaction effect from model attractiveness and language was significant on attitude toward the product(AP) and purchase intention(PI). To analyze the difference, the mean values and standard deviation of consequences were compared. The result was more positive when model attractiveness was high for all consequences. For language effect, the assessment was more positive when English was used for OQ. Considering model attractiveness and language simultaneously, HAM-Korean was more positive for AP and PI, and NAM-English was more positive for AP and PI. In other words, the interaction effect was confirmed by model attractiveness and language. As mentioned above, use of foreign models and foreign language in advertising was explained by cultural match up hypothesis (Leclerc et al. 1994) which claimed that culture of origin effect. In other words, in advertising, use of same cultural language with the foreign model could make positive assessment for OQ. But this effect was moderated by model attractiveness. When the model attractiveness was low, the use of English makes PI high because of the effect of foreign language which supported the cultural match up hypothesis. When the model attractiveness was low, the use of Korean made AP and PI high because the effect of foreign language was diluted. It was a general notion that the visual cues got processed before (Holbrook and Moore, 1981; Sholl et al, 1995) compared to linguistic cues. Therefore, when consumers were faced HAM, so much perception was already consumed at processing visual cues making their native language of Korean to strongly and positively connected with the advertising concept. On the contrary, when consumers were faced with NAM, less perception was consumed compared to HAM, making English to accompany cultural halo effect which affected more positively. Therefore, when foreign models were employed in advertising, the language must be carefully selected according to the level of model attractiveness.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.343-355
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• 2022

This study investigated the consumption tendency and awareness of paprika in order to expand and promote the consumption of Capsicum annuum L. The research investigated the relationship of preference and loyalty based on emotional response of paprika according to the semantic differential scale. The survey was conducted from January to February 2022 using a random sampling method targeting 155 general people, and a total of 142 questionnaires were analyzed excluding 13 wrong answers. The nine items on the awareness of paprika showed to be consisted of three factors such as 'Food taste', 'Usability', and 'Economics' by factor analysis. Regarding to the awareness of paprika the positive answer that 'I think paprika is good for health' among the nine questions was the highest at 92.3%. In the preference aspect of shape, blocky type had the highest preference for the shape of paprika, followed by mini and conical types in order of preference (p < 0.001). As for color preference, yellow paprika was the most preferred, followed by orange, red, and green, showing statistical significance. The emotional response of paprika by paprika image showed a statistically significant difference in the four colors. The words such as 'bright', 'clean', and 'spirited' appeared as representative emotional vocabulary for paprika. Multiple regression analysis was performed to examine the effect of paprika on the three factors of awareness, preference, and loyalty due to the quality of life. As a result, the higher the paprika preference and quality of life, and the higher the taste and availability factors, the higher the paprika awareness and loyalty. As the variable that has the most influence on the loyalty of the survey respondents, preference was found to have the highest explanatory power at 43%. From these results, it was judged as a very important factor in the survey on the shape and color preference of paprika. Therefore, the recent increase in awareness that paprika is good for health is thought to act as a positive factor in revitalizing the domestic market and increasing consumption of paprika in the future. Also, among the three types of paprika, the yellow blunt type showed the highest preference. Therefore, in order to produce and promote this type of paprika, it is also important to increase the cultivation to suit the purchasing propensity of consumers.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.227-252
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• 2018

The evolution of instant communication has mirrored the development of the Internet and messenger applications are among the most representative manifestations of instant communication technologies. In messenger applications, senders use emoticons to supplement the emotions conveyed in the text of their messages. The fact that communication via messenger applications is not face-to-face makes it difficult for senders to communicate their emotions to message recipients. Emoticons have long been used as symbols that indicate the moods of speakers. However, at present, emoticon-use is evolving into a means of conveying the psychological states of consumers who want to express individual characteristics and personality quirks while communicating their emotions to others. The fact that companies like KakaoTalk, Line, Apple, etc. have begun conducting emoticon business and sales of related content are expected to gradually increase testifies to the significance of this phenomenon. Nevertheless, despite the development of emoticons themselves and the growth of the emoticon market, no suitable emoticon recommendation system has yet been developed. Even KakaoTalk, a messenger application that commands more than 90% of domestic market share in South Korea, just grouped in to popularity, most recent, or brief category. This means consumers face the inconvenience of constantly scrolling around to locate the emoticons they want. The creation of an emoticon recommendation system would improve consumer convenience and satisfaction and increase the sales revenue of companies the sell emoticons. To recommend appropriate emoticons, it is necessary to quantify the emotions that the consumer sees and emotions. Such quantification will enable us to analyze the characteristics and emotions felt by consumers who used similar emoticons, which, in turn, will facilitate our emoticon recommendations for consumers. One way to quantify emoticons use is metadata-ization. Metadata-ization is a means of structuring or organizing unstructured and semi-structured data to extract meaning. By structuring unstructured emoticon data through metadata-ization, we can easily classify emoticons based on the emotions consumers want to express. To determine emoticons' precise emotions, we had to consider sub-detail expressions-not only the seven common emotional adjectives but also the metaphorical expressions that appear only in South Korean proved by previous studies related to emotion focusing on the emoticon's characteristics. We therefore collected the sub-detail expressions of emotion based on the "Shape", "Color" and "Adumbration". Moreover, to design a highly accurate recommendation system, we considered both emotion-technical indexes and emoticon-emotional indexes. We then identified 14 features of emoticon-technical indexes and selected 36 emotional adjectives. The 36 emotional adjectives consisted of contrasting adjectives, which we reduced to 18, and we measured the 18 emotional adjectives using 40 emoticon sets randomly selected from the top-ranked emoticons in the KakaoTalk shop. We surveyed 277 consumers in their mid-twenties who had experience purchasing emoticons; we recruited them online and asked them to evaluate five different emoticon sets. After data acquisition, we conducted a factor analysis of emoticon-emotional factors. We extracted four factors that we named "Comic", Softness", "Modernity" and "Transparency". We analyzed both the relationship between indexes and consumer attitude and the relationship between emoticon-technical indexes and emoticon-emotional factors. Through this process, we confirmed that the emoticon-technical indexes did not directly affect consumer attitudes but had a mediating effect on consumer attitudes through emoticon-emotional factors. The results of the analysis revealed the mechanism consumers use to evaluate emoticons; the results also showed that consumers' emoticon-technical indexes affected emoticon-emotional factors and that the emoticon-emotional factors affected consumer satisfaction. We therefore designed the emoticon recommendation system using only four emoticon-emotional factors; we created a recommendation method to calculate the Euclidean distance from each factors' emotion. In an attempt to increase the accuracy of the emoticon recommendation system, we compared the emotional patterns of selected emoticons with the recommended emoticons. The emotional patterns corresponded in principle. We verified the emoticon recommendation system by testing prediction accuracy; the predictions were 81.02% accurate in the first result, 76.64% accurate in the second, and 81.63% accurate in the third. This study developed a methodology that can be used in various fields academically and practically. We expect that the novel emoticon recommendation system we designed will increase emoticon sales for companies who conduct business in this domain and make consumer experiences more convenient. In addition, this study served as an important first step in the development of an intelligent emoticon recommendation system. The emotional factors proposed in this study could be collected in an emotional library that could serve as an emotion index for evaluation when new emoticons are released. Moreover, by combining the accumulated emotional library with company sales data, sales information, and consumer data, companies could develop hybrid recommendation systems that would bolster convenience for consumers and serve as intellectual assets that companies could strategically deploy.