• The Journal of Society for e-Business Studies
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• v.25 no.4
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• pp.61-75
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• 2020

The scope of data for understanding or predicting stock prices has been continuously widened from traditional structured format data to unstructured data. This study investigates whether commentary data collected from SNS may affect future stock prices. From "Stock Discussion Room" in Naver, we collect 20 stocks' commentary data for six months, and test whether this data have prediction power with respect to one-hour ahead price direction and price range. Deep neural network such as LSTM and CNN methods are employed to model the predictive relationship. Among the 20 stocks, we find that future price direction can be predicted with higher than the accuracy of 50% in 13 stocks. Also, the future price range can be predicted with higher than the accuracy of 50% in 16 stocks. This study validate that the investors' sentiment reflected in SNS community such as Naver's "Stock Discussion Room" may affect the demand and supply of stocks, thus driving the stock prices.

• Korean Business Review
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• v.19 no.2
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• pp.207-230
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• 2006

The study which it sees probably is the tourist' from the tourist resort, a emotional response and the change of stay hour and the follows in crowding perceived degree and it examines it does. In order to achieve the purpose of this study, carried out literature study of a related field and set up a study model. We used one method. The first method was directly distributing questionnaires to tourist' by use of one researcher who has been trained in tourist site, in order to confirm hypothesis established according to a theoretical background. And as the site of study, chose Mureung Valley which are located in the East Sea region which is one of the largest domestic vacation destinations. Through these methods, we were able to obtain participation of 450 people from across the country. Using 408 responses(42 responses removed). we derived statistics by means of Win SPSS Version 10.0 statistics program package. The analysis results ara as follows: First, Perceived Crowding affects tourists' Emotional Response and the Stay hour change. Specially, perceived Crowding is from in the Emotional Response factor it is joyful with there is relationship of excitation relationship effect. Second, There is relationship of effect even to sentimental reaction and stay hour change. This also is from in the Emotional Response factor it is joyful with there is relationship of excitation relationship effect. Finally, we discuss the results of analysis and suggest research limitation and future and future study.

• Science of Emotion and Sensibility
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• v.20 no.4
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• pp.31-40
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• 2017

This research aims to investigate 'Hallyu' contents consumption tendency of consumers from Korea, Japan, and the United States by analyzing their emotional responses. With the development of social media, research on emotion analysis by reviewing text materials has grown. Whereas environmental variables affect consumer demand towards 'Hallyu' contents, little comparative analyses have been conducted on the emotional responses of consumers from different countries. In this research, the emotional prototype model proposed by Russell(1980) used to extract and distinguish emotional words to clarify how people in the three countries differently perceive the Korean drama "Goblin". First of all, the SNS reviews were collected during a two-month period (February 12 to April 12). Second, significant factors were identified in the collected data according to Russell's emotion model. Third, random forest was applied to organize the selected variables in the order of variable importance. Fourth, the correlations among the emotional words were compared. Lastly, the accuracy of the trained model was measured using the test dataset. The results show that "Happy" was found to be the greatest factor in Korea and in the United States and "Pleased" in Japan. Emotional words correlations showed that when watching the drama "Goblin", "passive unpleasure" was the main factor associated with individual's interest in Korea whereas "passive pleasure" was associated with individual's interest in Japan and in the United States. Based on the results, this research suggests the possibility of developing evaluation guidelines for emotional responses of different countries towards 'Hallyu' contents.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.113-125
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• 2013

Every company wants to know customer's requirement and makes an effort to meet them. Cause that, communication between customer and company became core competition of business and that important is increasing continuously. There are several strategies to find customer's needs, but VOC (Voice of customer) is one of most powerful communication tools and VOC gathering by several channels as telephone, post, e-mail, website and so on is so meaningful. So, almost company is gathering VOC and operating VOC system. VOC is important not only to business organization but also public organization such as government, education institute, and medical center that should drive up public service quality and customer satisfaction. Accordingly, they make a VOC gathering and analyzing System and then use for making a new product and service, and upgrade. In recent years, innovations in internet and ICT have made diverse channels such as SNS, mobile, website and call-center to collect VOC data. Although a lot of VOC data is collected through diverse channel, the proper utilization is still difficult. It is because the VOC data is made of very emotional contents by voice or text of informal style and the volume of the VOC data are so big. These unstructured big data make a difficult to store and analyze for use by human. So that, the organization need to automatic collecting, storing, classifying and analyzing system for unstructured big VOC data. This study propose an intelligent VOC analyzing system based on opinion mining to classify the unstructured VOC data automatically and determine the polarity as well as the type of VOC. And then, the basis of the VOC opinion analyzing system, called domain-oriented sentiment dictionary is created and corresponding stages are presented in detail. The experiment is conducted with 4,300 VOC data collected from a medical website to measure the effectiveness of the proposed system and utilized them to develop the sensitive data dictionary by determining the special sentiment vocabulary and their polarity value in a medical domain. Through the experiment, it comes out that positive terms such as "칭찬, 친절함, 감사, 무사히, 잘해, 감동, 미소" have high positive opinion value, and negative terms such as "퉁명, 뭡니까, 말하더군요, 무시하는" have strong negative opinion. These terms are in general use and the experiment result seems to be a high probability of opinion polarity. Furthermore, the accuracy of proposed VOC classification model has been compared and the highest classification accuracy of 77.8% is conformed at threshold with -0.50 of opinion classification of VOC. Through the proposed intelligent VOC analyzing system, the real time opinion classification and response priority of VOC can be predicted. Ultimately the positive effectiveness is expected to catch the customer complains at early stage and deal with it quickly with the lower number of staff to operate the VOC system. It can be made available human resource and time of customer service part. Above all, this study is new try to automatic analyzing the unstructured VOC data using opinion mining, and shows that the system could be used as variable to classify the positive or negative polarity of VOC opinion. It is expected to suggest practical framework of the VOC analysis to diverse use and the model can be used as real VOC analyzing system if it is implemented as system. Despite experiment results and expectation, this study has several limits. First of all, the sample data is only collected from a hospital web-site. It means that the sentimental dictionary made by sample data can be lean too much towards on that hospital and web-site. Therefore, next research has to take several channels such as call-center and SNS, and other domain like government, financial company, and education institute.

• Journal of the Korea Convergence Society
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• v.11 no.2
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• pp.167-174
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• 2020

The social statistic was used to top 250 Korean and Japanese YouTube channels based on the number of subscribers examine its channel type (private/corporations/others), distribution of contents and private YouTube channels' date of registration. The channel examination was also used to provide practical hint to create new Youtube contents. According to the statistics, Korean channels were mainly managed by K-Culture related companies for the promotional purpose, whereas Japanese channels were mainly managed by individuals with a variety of contents. It is presumed that Japanese individuals have been engaged in creating individual video content since the early period through video uploading platforms other than YouTube such as Niconico Douga. Since the expansion of the YouTube market will continue, it is important not only to reinforce corporations' marketing on YouTube but also to promote the uniqueness and the diversity of YouTube content for the individuals to improve the economical, sentimental, and informational contents in order to create socially effective personal contents that can be competitive in the global market.

• Journal of Fashion Business
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• v.9 no.4
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• pp.59-78
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• 2005

This study aims to know the deferences of hair fashion feeling group in accordance with hair styling activities, general characteristics, life styles objecting to capital area university women students and aid to hair fashion design. So the results are as belows. 1. Frequency Analysis of Categories A. Hair fashion feeling - Natural, sexy, romantic pretty, sophisticate, ethnic are 90% in total hair fashion feeling variables in sequence of frequency, so it can be said these are in vogue. B. Hair styling activities - The objections visit the hair salon once 1-2months, spend about 42,000 won a month, perform cut & wave perm to sentimental reasens & hair style changes, determine the hair style well coordinated in her image and managed easily. In her home, they manage her hair style 12 minutes a day, spend 17,000 won to buy hair aids, do hair blow dry or pin or pony tail mainly in the morning, scarcely use the hair styling aids but if use, essence or wax mainly. And the degree of interest to hair style is high. C. General Characteristics - The objections's average age is 21.1, residence is seoul kangnam 23.3%, seoul kangbook 18.4%, other capital areas 58.4%, the degree of education is university students 94.9%, graduated student 5.1%, marriage is married 96%, unmarried 2.8%, family who live with is married are mainly man & woman and living with father & mother in low in man's, unmarried are mainly live alone & nuclear family, personal expenses a month is 300,000 won in average, income of home is 4,000,000 won a month. D. Life style - The objections are not in interest of physical exercises but if are, do yoga & health, like drama & comedies program, watch TV or meet friend in leisure time, like balad & dance music, fashion magazine, meet friend in cafe or college. 2. Relationship of hair fashion feeling & other variables Using the $x^2$-test, level p<0.05, Hair styling activities(frequency of hair salon coming in and out, ordinary time representing hair style, preferred hair styling aids, the amount of hair style interest), General Characteristics(age), Life style(leisure time) variables are meaningful.

• Sijohaknonchong
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• v.42
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• pp.93-115
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• 2015

Dynamics of Sijo was regarded as a genre of 'closed nature' once. But ironically thanks to the 'closed nature', today dynamics of Sijo is refocused in diverse fields. Sijo is quoted not only in its original field of literature, but also in writing study. Quite remarkably, it is often referred to in the field of literary therapy, further in emotional healing. This article discussed the dynamics of Sijo as a manifestation of emotion especially called Gamsung in the process of the refocus. It is to show effectively that as a literary genre, Sijo can interact and share what is reasonal as well as what is emotional and sentimental in a poem as an emotional container beyond the lyricism Sijo has. Of course, it is also clear that the concept of lyricism may limit the dynamics of Sijo itself. Thus, the key word 'Gamsung' mainly referred to in this article was used to show the dynamics which Sijo has as much as possible, overcoming the limitation. That is, the purpose of the study is to prove that Sijo is the genre to represent human emotion most dynamically by reviewing the reasonal aspect of Sijo in addition to its emotional disposition which has been estimated to focus on sentiment or emotion. In the process of reinterpreting the structure of Sijo, the specific analysis on such emotional disposition and reasonal aspect was conducted by structurizing that as '(1) Facing, (2) Feeling dynamical, (3) Interpellating by feeling, and (4) feeling by sensation'.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.179-188
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• 2023

Recently, fake news disguises the form of news content and appears whenever important events occur, causing social confusion. Accordingly, artificial intelligence technology is used as a research to detect fake news. Fake news detection approaches such as automatically recognizing and blocking fake news through natural language processing or detecting social media influencer accounts that spread false information by combining with network causal inference could be implemented through deep learning. However, fake news detection is classified as a difficult problem to solve among many natural language processing fields. Due to the variety of forms and expressions of fake news, the difficulty of feature extraction is high, and there are various limitations, such as that one feature may have different meanings depending on the category to which the news belongs. In this paper, emotional change patterns are presented as an additional identification criterion for detecting fake news. We propose a model with improved performance by applying a convolutional neural network to a fake news data set to perform analysis based on content characteristics and additionally analyze emotional change patterns. Sentimental polarity is calculated for the sentences constituting the news and the result value dependent on the sentence order can be obtained by applying long-term and short-term memory. This is defined as a pattern of emotional change and combined with the content characteristics of news to be used as an independent variable in the proposed model for fake news detection. We train the proposed model and comparison model by deep learning and conduct an experiment using a fake news data set to confirm that emotion change patterns can improve fake news detection performance.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.3
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• pp.1-10
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• 2021

This study aimed to evaluate preferences of Bukhansan dulegil using sentiment analysis, a natural language processing technique, to derive preferred and non-preferred factors. Therefore, we collected blog articles written in 2019 and produced sentimental scores by the derivation of positive and negative words in the texts for 21 dulegil courses. Then, content analysis was conducted to determine which factors led visitors to prefer or dislike each course. In blogs written about Bukhansan dulegil, positive words appeared in approximately 73% of the content, and the percentage of positive documents was significantly higher than that of negative documents for each course. Through this, it can be seen that visitors generally had positive sentiments toward Bukhansan dulegil. Nevertheless, according to the sentiment score analysis, all 21 dulegil courses belonged to both the preferred and non-preferred courses. Among courses, visitors preferred less difficult courses, in which they could walk without a burden, and in which various landscape elements (visual, auditory, olfactory, etc.) were harmonious yet distinct. Furthermore, they preferred courses with various landscapes and landscape sequences. Additionally, visitors appreciated the presence of viewpoints, such as observation decks, as a significant factor and preferred courses with excellent accessibility and information provisions, such as information boards. Conversely, the dissatisfaction with the dulegil courses was due to noise caused by adjacent roads, excessive urban areas, and the inequality or difficulty of the course which was primarily attributed to insufficient information on the landscape or section of the course. The results of this study can serve not only serve as a guide in national parks but also in the management of nearby forest green areas to formulate a plan to repair and improve dulegil. Further, the sentiment analysis used in this study is meaningful in that it can continuously monitor actual users' responses towards natural areas. However, since it was evaluated based on a predefined sentiment dictionary, continuous updates are needed. Additionally, since there is a tendency to share positive content rather than negative views due to the nature of social media, it is necessary to compare and review the results of analysis, such as with on-site surveys.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.67-88
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• 2019

Webtoon is a Korean-style digital comics platform that distributes comics content produced using the characteristic elements of the Internet in a form that can be consumed online. With the recent rapid growth of the webtoon industry and the exponential increase in the supply of webtoon content, the need for effective webtoon content recommendation measures is growing. Webtoons are digital content products that combine pictorial, literary and digital elements. Therefore, webtoons stimulate consumer sentiment by making readers have fun and engaging and empathizing with the situations in which webtoons are produced. In this context, it can be expected that the sentiment that webtoons evoke to consumers will serve as an important criterion for consumers' choice of webtoons. However, there is a lack of research to improve webtoons' recommendation performance by utilizing consumer sentiment. This study is aimed at developing consumer sentiment pattern maps that can support effective recommendations of webtoon content, focusing on consumer sentiments that have not been fully discussed previously. Metadata and consumer sentiments data were collected for 200 works serviced on the Korean webtoon platform 'Naver Webtoon' to conduct this study. 488 sentiment terms were collected for 127 works, excluding those that did not meet the purpose of the analysis. Next, similar or duplicate terms were combined or abstracted in accordance with the bottom-up approach. As a result, we have built webtoons specialized sentiment-index, which are reduced to a total of 63 emotive adjectives. By performing exploratory factor analysis on the constructed sentiment-index, we have derived three important dimensions for classifying webtoon types. The exploratory factor analysis was performed through the Principal Component Analysis (PCA) using varimax factor rotation. The three dimensions were named 'Immersion', 'Touch' and 'Irritant' respectively. Based on this, K-Means clustering was performed and the entire webtoons were classified into four types. Each type was named 'Snack', 'Drama', 'Irritant', and 'Romance'. For each type of webtoon, we wrote webtoon-sentiment 2-Mode network graphs and looked at the characteristics of the sentiment pattern appearing for each type. In addition, through profiling analysis, we were able to derive meaningful strategic implications for each type of webtoon. First, The 'Snack' cluster is a collection of webtoons that are fast-paced and highly entertaining. Many consumers are interested in these webtoons, but they don't rate them well. Also, consumers mostly use simple expressions of sentiment when talking about these webtoons. Webtoons belonging to 'Snack' are expected to appeal to modern people who want to consume content easily and quickly during short travel time, such as commuting time. Secondly, webtoons belonging to 'Drama' are expected to evoke realistic and everyday sentiments rather than exaggerated and light comic ones. When consumers talk about webtoons belonging to a 'Drama' cluster in online, they are found to express a variety of sentiments. It is appropriate to establish an OSMU(One source multi-use) strategy to extend these webtoons to other content such as movies and TV series. Third, the sentiment pattern map of 'Irritant' shows the sentiments that discourage customer interest by stimulating discomfort. Webtoons that evoke these sentiments are hard to get public attention. Artists should pay attention to these sentiments that cause inconvenience to consumers in creating webtoons. Finally, Webtoons belonging to 'Romance' do not evoke a variety of consumer sentiments, but they are interpreted as touching consumers. They are expected to be consumed as 'healing content' targeted at consumers with high levels of stress or mental fatigue in their lives. The results of this study are meaningful in that it identifies the applicability of consumer sentiment in the areas of recommendation and classification of webtoons, and provides guidelines to help members of webtoons' ecosystem better understand consumers and formulate strategies.