• Title/Summary/Keyword: Positive Opinion

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A Survey on the Perception and Satisfaction of Korean Medicine in Children and Youth in Chungcheongbuk-do - A Survey of Parents (충북지역 소아 청소년 한의 치료에 대한 인식 및 만족도 조사 - 보호자 대상 설문 연구)

  • Kim Tae-Jeong;Sung Hyun-Kyung
    • The Journal of Pediatrics of Korean Medicine
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    • v.37 no.4
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    • pp.15-24
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    • 2023
  • Objectives This study aimed to identify the current status and satisfaction with Korean medicine treatment and analyze the perceptions of parents about Korean medicine treatment in children. Methods A Web survey (Moaform) was conducted with 52 parents whose children used Korean medicine and 53 parents who did not. We investigated the reasons why the user group chose treatment and satisfaction with each treatment and why the non-user group did not choose the treatment. Results Children in the user group were frequently prescribed herbal medicines (decoctions) and acupuncture. However, they showed low satisfaction in terms of fear of acupuncture and dissatisfaction with the unique taste of herbal medicine. Non-user parents had a favorable opinion of Korean medicine, but had relatively negative perceptions about whether their children were willing to visit in the future. Conclusions Parents who used Korean medicine for their children had positive perceptions and trust in Korean medicine. However, those who did not use Korean medicine were concerned about the safety and potential harm of its application to their children.

The Effect of Using WhatsApp on EFL Students' Medical English Vocabulary Learning During the Covid-19 Pandemic

  • Saud Alenezi;Elias Bensalem
    • International Journal of Computer Science & Network Security
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    • v.24 no.2
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    • pp.143-149
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    • 2024
  • The role of social networking mobile applications such as WhatsApp in enhancing second language vocabulary learning among English language learners continues to be a subject of interest for many scholars. The current study aimed at examining medical English vocabulary learning among undergraduate students using WhatsApp compared to learning vocabulary via the Blackboard platform during the Covid-19 pandemic. To this end, 108 medical students (51 males, 57 females) enrolled in a first semester English for a specific English course participated in the study. A quasi-experimental design was adopted for two groups. Fifty-three students participated in the WhatsApp group and 55 students formed the Blackboard group. A pretest-posttest design was employed to collect data. Results of t-test scores did not show a significant difference between the WhatsApp and Blackboard groups on a vocabulary test. Results of a survey that measured students' opinion of the use of WhatsApp as a platform for learning new vocabulary showed positive perceptions since participants thought that WhatsApp enhanced their learning experience.

Latent topics-based product reputation mining (잠재 토픽 기반의 제품 평판 마이닝)

  • Park, Sang-Min;On, Byung-Won
    • Journal of Intelligence and Information Systems
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    • v.23 no.2
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    • pp.39-70
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    • 2017
  • Data-drive analytics techniques have been recently applied to public surveys. Instead of simply gathering survey results or expert opinions to research the preference for a recently launched product, enterprises need a way to collect and analyze various types of online data and then accurately figure out customer preferences. In the main concept of existing data-based survey methods, the sentiment lexicon for a particular domain is first constructed by domain experts who usually judge the positive, neutral, or negative meanings of the frequently used words from the collected text documents. In order to research the preference for a particular product, the existing approach collects (1) review posts, which are related to the product, from several product review web sites; (2) extracts sentences (or phrases) in the collection after the pre-processing step such as stemming and removal of stop words is performed; (3) classifies the polarity (either positive or negative sense) of each sentence (or phrase) based on the sentiment lexicon; and (4) estimates the positive and negative ratios of the product by dividing the total numbers of the positive and negative sentences (or phrases) by the total number of the sentences (or phrases) in the collection. Furthermore, the existing approach automatically finds important sentences (or phrases) including the positive and negative meaning to/against the product. As a motivated example, given a product like Sonata made by Hyundai Motors, customers often want to see the summary note including what positive points are in the 'car design' aspect as well as what negative points are in thesame aspect. They also want to gain more useful information regarding other aspects such as 'car quality', 'car performance', and 'car service.' Such an information will enable customers to make good choice when they attempt to purchase brand-new vehicles. In addition, automobile makers will be able to figure out the preference and positive/negative points for new models on market. In the near future, the weak points of the models will be improved by the sentiment analysis. For this, the existing approach computes the sentiment score of each sentence (or phrase) and then selects top-k sentences (or phrases) with the highest positive and negative scores. However, the existing approach has several shortcomings and is limited to apply to real applications. The main disadvantages of the existing approach is as follows: (1) The main aspects (e.g., car design, quality, performance, and service) to a product (e.g., Hyundai Sonata) are not considered. Through the sentiment analysis without considering aspects, as a result, the summary note including the positive and negative ratios of the product and top-k sentences (or phrases) with the highest sentiment scores in the entire corpus is just reported to customers and car makers. This approach is not enough and main aspects of the target product need to be considered in the sentiment analysis. (2) In general, since the same word has different meanings across different domains, the sentiment lexicon which is proper to each domain needs to be constructed. The efficient way to construct the sentiment lexicon per domain is required because the sentiment lexicon construction is labor intensive and time consuming. To address the above problems, in this article, we propose a novel product reputation mining algorithm that (1) extracts topics hidden in review documents written by customers; (2) mines main aspects based on the extracted topics; (3) measures the positive and negative ratios of the product using the aspects; and (4) presents the digest in which a few important sentences with the positive and negative meanings are listed in each aspect. Unlike the existing approach, using hidden topics makes experts construct the sentimental lexicon easily and quickly. Furthermore, reinforcing topic semantics, we can improve the accuracy of the product reputation mining algorithms more largely than that of the existing approach. In the experiments, we collected large review documents to the domestic vehicles such as K5, SM5, and Avante; measured the positive and negative ratios of the three cars; showed top-k positive and negative summaries per aspect; and conducted statistical analysis. Our experimental results clearly show the effectiveness of the proposed method, compared with the existing method.

Issue tracking and voting rate prediction for 19th Korean president election candidates (댓글 분석을 통한 19대 한국 대선 후보 이슈 파악 및 득표율 예측)

  • Seo, Dae-Ho;Kim, Ji-Ho;Kim, Chang-Ki
    • Journal of Intelligence and Information Systems
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    • v.24 no.3
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    • pp.199-219
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    • 2018
  • With the everyday use of the Internet and the spread of various smart devices, users have been able to communicate in real time and the existing communication style has changed. Due to the change of the information subject by the Internet, data became more massive and caused the very large information called big data. These Big Data are seen as a new opportunity to understand social issues. In particular, text mining explores patterns using unstructured text data to find meaningful information. Since text data exists in various places such as newspaper, book, and web, the amount of data is very diverse and large, so it is suitable for understanding social reality. In recent years, there has been an increasing number of attempts to analyze texts from web such as SNS and blogs where the public can communicate freely. It is recognized as a useful method to grasp public opinion immediately so it can be used for political, social and cultural issue research. Text mining has received much attention in order to investigate the public's reputation for candidates, and to predict the voting rate instead of the polling. This is because many people question the credibility of the survey. Also, People tend to refuse or reveal their real intention when they are asked to respond to the poll. This study collected comments from the largest Internet portal site in Korea and conducted research on the 19th Korean presidential election in 2017. We collected 226,447 comments from April 29, 2017 to May 7, 2017, which includes the prohibition period of public opinion polls just prior to the presidential election day. We analyzed frequencies, associative emotional words, topic emotions, and candidate voting rates. By frequency analysis, we identified the words that are the most important issues per day. Particularly, according to the result of the presidential debate, it was seen that the candidate who became an issue was located at the top of the frequency analysis. By the analysis of associative emotional words, we were able to identify issues most relevant to each candidate. The topic emotion analysis was used to identify each candidate's topic and to express the emotions of the public on the topics. Finally, we estimated the voting rate by combining the volume of comments and sentiment score. By doing above, we explored the issues for each candidate and predicted the voting rate. The analysis showed that news comments is an effective tool for tracking the issue of presidential candidates and for predicting the voting rate. Particularly, this study showed issues per day and quantitative index for sentiment. Also it predicted voting rate for each candidate and precisely matched the ranking of the top five candidates. Each candidate will be able to objectively grasp public opinion and reflect it to the election strategy. Candidates can use positive issues more actively on election strategies, and try to correct negative issues. Particularly, candidates should be aware that they can get severe damage to their reputation if they face a moral problem. Voters can objectively look at issues and public opinion about each candidate and make more informed decisions when voting. If they refer to the results of this study before voting, they will be able to see the opinions of the public from the Big Data, and vote for a candidate with a more objective perspective. If the candidates have a campaign with reference to Big Data Analysis, the public will be more active on the web, recognizing that their wants are being reflected. The way of expressing their political views can be done in various web places. This can contribute to the act of political participation by the people.

A Study on the Sensibility Analysis of School Life and the Will to Farming of Students at Korea National College of Agricultural and Fisheries (한국농수산대학 재학생의 학교생활 감성 분석 및 영농의지에 관한 연구)

  • Joo, J.S.;Lee, S.Y.;Kim, J.S.;Shin, Y.K.;Park, N.B.
    • Journal of Practical Agriculture & Fisheries Research
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    • v.21 no.2
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    • pp.103-114
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    • 2019
  • In this study we examined the preferences of college life factors for students at Korea National College of Agriculture and Fisheries(KNCAF). Analytical techniques of unstructured data used opinion mining and text mining techniques, and the results of text mining were visualized as word cloud. And those results were used for statistical analysis of the students' willingness to farm after graduation. The items of the favorable survey consisted of 10 items in 5 areas including university image, self-capacity, dormitory, education system, and future vision. After classifying the emotions of positive and negative in the collected questionnaire, a dictionary of positive and negative was created to evaluate the preference. The items of 'college image' at the time of university support, 'self after 10 years' after graduation, 'self-capacity' and 'present KNCAF' showed high positive emotion. On the other hand, positive emotion was low in the items of 'college dormitory', 'educational course', 'long-term field practice' and 'future of Korean agriculture'. In the cross-analysis of the difference in the will to farming according to gender, farming base, and entrance motivation, the will to farm according to gender and entrance motivation showed statistically significant results, but it was not significant in farming base. Also in binary logistic regression analysis on the will to farming, the statistically significant variable was found to be 'motivation for admission'

An Analysis of Relationship between Social Sentiments and Cryptocurrency Price: An Econometric Analysis with Big Data (소셜 감성과 암호화폐 가격 간의 관계 분석: 빅데이터를 활용한 계량경제적 분석)

  • Sangyi Ryu;Jiyeon Hyun;Sang-Yong Tom Lee
    • Information Systems Review
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    • v.21 no.1
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    • pp.91-111
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    • 2019
  • Around the end of 2017, the investment fever for cryptocurrencies-especially Bitcoin-has started all over the world. Especially, South Korea has been at the center of this phenomenon. Sinceit was difficult to find the profitable investment opportunities, people have started to see the cryptocurrency markets as an alternative investment objects. However, the cryptocurrency fever inSouth Korea is mostly based on psychological phenomenon due to expectation of short-term profits and social atmosphere rather than intrinsic value of the assets. Therefore, this study aimed to analyze influence of people's social sentiment on price movement of cryptocurrency. The data was collected for 181 days from Nov 1st, 2017 to Apr 30th, 2018, especially focusing on Bitcoin-related post in Twitter along with price of Bitcoin in Bithumb/UPbit. After the collected data was refined into neutral, positive and negative words through sentiment analysis, the refined neutral, positive, and negative words were put into regression model in order to find out the impacts of social sentiments on Bitcoin price. After examining the relationship by the regression analyses and Granger Causality tests, we found that the positive sentiments had a positive relationship with Bitcoin price, while the negative words had a negative relation with it. Also, the causality test results show that there exist two-way causalities between social sentiment and Bitcoin price movement. Therefore, we were able to conclude that the Bitcoin investors'behaviors are affected by the changes of social sentiments.

A study on The U.S.-Korean Trade Friction Prevention and Settlement in the Fields of Information and Telecommunication Industries (한미간(韓美間) 정보통신분야(情報通信分野) 통상마찰예방(通商摩擦豫防)과 해소방안(解消方案)에 관한 연구(硏究))

  • Jung, Jay-Young
    • THE INTERNATIONAL COMMERCE & LAW REVIEW
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    • v.13
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    • pp.869-895
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    • 2000
  • The US supports the Information and Communication (IC) industry as a strategic one to wield a complete power over the World Market. However, several other countries are also eager to have the support for the IC industry because the industry produces a high added value and has a significant effect on other industries. Korea is not an exception. Korea recently succeeded in the commercialization of CDMA for the first time in the world, after the successful development of TDX. Hence, it is highly likely to get tracked by the US. Although the IC industry is a specific sector of IT, there is a concern that there might be a trade friction between the US and Korea due to a possible competition. It will be very important to prepare a solution in advance so that Korea could prevent the friction and at the same time increase its share domestically and globally. It will be our important task to solve the problem with the minimum cost if the conflict arises unfortunately in the IT area. The parties that have a strong influence on the US trade policy are the think tank group and the IT-related interest group. Therefore, it would be important to have a close relationship with them. We found some implications by analyzing the case of Japan, which has experienced trade frictions with the US over the long period of time in the high tech industry. In order to get rid of those conflicts with the US, the Japanese did the following things : (1) The Japanese government developed supporting theories and also resorted to international support so that the world could support the Japanese theories. (2) Through continual dialogue with the US business people, the Japanese business people sought after solutions to share profits among the Japanese and the US both in the domestic and in the worldwide markets. They focused on lobbying activities to influence the US public opinion to support the Japanese. The specific implementation plan was first to open culture lobby toward opinion leaders who were leaders about the US opinion. The institution, Japan Society, were formed to deliver a high quality lobbying activities. The second plan is economic lobby. They have established Japanese Economic Institute at Washington. They provide information about Japan regularly or irregularly to the US government, research institution, universities, etc., that are interested in Japan. The main objective behind these activities though is to advertise the validity of Japanese policy. Japanese top executives, practical interest groups on international trade, are trying to justify their position by direct contact with the US policy makers. The third one is political lobby. Japan is very careful about this political lobby. It is doing its best not to give impression that Japan is trying to shape the US policy making. It is collecting a vast amount of information to make a correct judgment on situation. It is not tilted toward one political party or the other, and is rather developing a long-term network of people who understand and support the Japanese policy. The following implications were drawn from the experience of Japan. First, the Korean government should develop a long-term plan and execute it to improve the Korean image perceived by American people. Second, the Korean government should begin public relation activities toward the US elite group. It is inevitable to make an effort to advertise Korea to this elite group because this group leads public opinion in the USA. Third, the Korean government needs the development of a relevant policy to elevate the positive atmosphere for advertising toward the US. For example, we need information about to whom and how to about lobbying activities, personnel network who immediately respond to wrong articles about Korea in the US press, and lastly the most recent data bank of Korean support group inside the USA. Fourth, the Korean government should create an atmosphere to facilitate the advertising toward the US. Examples include provision of incentives in tax on the expenses for the advertising toward the US and provision of rewards to those who significantly contribute to the advertising activities. Fifth, the Korean government should perform the role of a bridge between Korean and the US business people. Sixth, the government should promptly analyze the policy of IT industry, a strategic area, and timely distribute information to industries in Korea. Since the Korean government is the only institution that has formal contact with the US government, it is highly likely to provide information of a high quality. The followings are some implications for business institutions. First, Korean business organization should carefully analyze and observe the business policy and managerial conditions of US companies. It is very important to do so because all the trade frictions arise at the business level. Second, it is also very important that the top management of Korean firms contact the opinion leaders of the US. Third, it is critically needed that Korean business people sent to the USA do their part for PR activities. Fourth, it is very important to advertise to American employees in Korean companies. If we cannot convince our American employees, it would be a lot harder to convince regular American. Therefore, it is very important to make the American employees the support group for Korean ways. Fifth, it should try to get much information as early as possible about the US firms policy in the IT area. It should give an enormous effort on early collection of information because by doing so it has more time to respond. Sixth, it should research on the PR cases of foreign enterprise or non-American companies inside the USA. The research needs to identify the success factors and the failure factors. Finally, the business firm will get more valuable information if it analyzes and responds to, according to each medium.

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The Effect of Public Frame, Stereotype, and Twitter Remediation on Country Reputation: Focused on Japan and China's Country Reputation around Diaoyudao Issue (공중 프레임, 고정관념, 트위터의 재매개(remediation)가 국가명성에 미치는 영향: 댜오위다오 이슈를 둘러싼 일본 및 중국 명성을 중심으로)

  • Cha, Hee-Won;Chang, Seo-Jin;Jang, Hyun-Ji
    • Korean journal of communication and information
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    • v.62
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    • pp.286-314
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    • 2013
  • The purpose of this paper is to explore the effect of stereotype, public frame, and Twitter remediation on country reputation. Diaoyudao/Senkaku dominium dispute was chosen which has been a lasting territorial problem between Japan and China. According to a survey conducted toward 210 Koreans aged 20 to 40, stereotype of Japan and China has effects on each reputation. Legitimacy-securing frame only affect China's country reputation. While stereotype of Japan and 'attribution to Japan's responsibility' frame significantly interacted with Japan's country reputation, stereotype of Japan and 'attribution to both sides' responsibility' frame also interacted with Japan. Also, Twitter remediation activity categorized into producing, distributing and viewing was examined. Only producing and viewing had effects on Japan's reputation. In terms of interaction, the more opinion leaders do distributing, the more they agree on attribution to both sides' responsibility frame, and recognize China's reputation more positive. Consequently, it was proved that Twitter opinion leaders interpreted public frame and recognized country reputation in a different way compared to the normal Twitterians.

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Information Flows, Differences of Opinion, and Trading Volumes : An Empirical Study (정보흐름, 의견차이, 거래량에 관한 실증연구)

  • Rhieu, Sang-Yup
    • Korean Business Review
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    • v.12
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    • pp.119-138
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    • 1999
  • In this study, we empirically investigate the relations between trading volumes and our proxies for information flows and differences of opnion. Econometric methods to analyze the relations in the equity and KOSPI 200 futures markets include Generalized Method of Moment(GMM) and Generalized Autoregressive Conditional Heteroscedasticity(GARCH) models. Major findings from our empirical analyses are summarized as follows; (i) Trading volume in both the equity and KOSPI 200 futures markets varies positively with proxies for information flows. We find that trading volumes in both markets are closely related to firm-specific information rather than market-wide information. (ii) Trading volumes in the equity and KOSPI 200 futures market have positive relations with our proxies for differences of opinion. (iii) Day-of-the-week effect is clear in both markets. Trading volumes in both the equity and KOSPI 200 futures markets tend to be relatively low early and late in the week. (IV) Futures contract life-cycle effect is clear. In other words, futures trading volume increses in the period around contract expiration. (V) In addition, ARCH effect on trading volumes is reported significant enough to take into account. The disturbance of trading volumes in both markets seem to be conditional heteroscedastic.

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Protection of Diversity through the Control of the Delimitation of the Audience Share in German Television (독일에서의 시청점유율제한을 통한 다양성 보호 연구)

  • Shim, Young-Sub
    • Korean journal of communication and information
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    • v.51
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    • pp.117-135
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    • 2010
  • The regulation of media concentration which is provided in the German Interstate Treaty on Broadcasting (RStV) is part of the rules forming the "positive broadcasting order" required by German Constitutional Law. This control ensures that the diversity of viewpoints can be articulated to the public. Broadcasting must operate independently from the state and from particular social groups if it is to be a genuine service to the public. One risk of economic competition in the media is a tendency towards the concentration of business enterprises. Moreover, economic competition is no guarantee for journalistic diversity. The aim of balanced diversity in the broadcasting sector can only be pursued by creating conditions under which different voices obtain the chance to be heard in an equitable manner. Within the framework of the meaning of section 26, it shall be assumed that there is a predominant impact on public opinion if the programs attributable to one company reach an annual audience share of 30 percent. The same shall apply if the company reaches an audience share of 25 percent and holds a dominant position in a related media-market or an overall assessment of its activities in television. The restriction of audience shares has limits such as that the audience shares of news programs and education and entertainment programs are pooled. Therefore, there is a vagueness about the productivity of different program branches.

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