• Management & Information Systems Review
• /
• v.35 no.1
• /
• pp.85-116
• /
• 2016

The present study aims to explore the causes of employment difficulty on the basis of job applicant's interest from P-E (person-environment) fit perspective. Our approach relied on a textual analytic method to reveal insights from their situational interests in a job search during the change of labor market. Thus, to investigate the type of major interests and psychological responses, user-generated texts in a social community were collected for analysis between January 1, 2013 through December 31, 2015 by crawling the online-community in regard to job seeking and sharing information and opinions. The results of topic analysis indicated user's primary interests were divided into four types: perception of vocation expectation, employment pre-preparation behaviors, perception of labor market, and job-seeking stress. Specially, job applicants put mainly concerns of monetary reward and a form of employment, rather than their work values or career exploration, thus youth job applicants expressed their psychological responses using contextualized language (e.g., slang, vulgarisms) for projecting their unstable state under uncertainty in response to environmental changes. Additionally, they have perceived activities in the restricted preparation (e.g., certification, English exam) as determinant factors for success in employment and suffered form job-seeking stress. On the basis of these findings, current unemployment matters are totally attributed to the absence of pursing the value of vocation and job in individuals, organizations, and society. Concretely, job seekers are preoccupied with occupational prestige in social aspect and have undecided vocational value. On the other hand, most companies have no perception of the importance of human resources and have overlooked the needs for proper work environment development in respect of stimulating individual motivation. The attempt in this study to reinterpret the effect of environment as for classifying job applicant's interests in reference to linguistic and psychological theories not only helps conduct a more comprehensive meaning for understanding social matters, but guides new directions for future research on job applicant's psychological factors (e.g., attitudes, motivation) using topic analysis.

• Journal of Internet Computing and Services
• /
• v.22 no.1
• /
• pp.109-135
• /
• 2021

his study classified the development process of artificial intelligence (AI) speakers through analysis of the news text of artificial intelligence (AI) speakers shown in traditional news reports, and identified the characteristics of each product by period. The theoretical background used in the analysis are news frames and topic frames. As analysis methods, topic modeling and semantic network analysis using the LDA method were used. The research method was a content analysis method. From 2014 to 2019, 2710 news related to AI speakers were first collected, and secondly, topic frames were analyzed using Nodexl algorithm. The result of this study is that, first, the trend of topic frames by AI speaker provider type was different according to the characteristics of the four operators (communication service provider, online platform, OS provider, and IT device manufacturer). Specifically, online platform operators (Google, Naver, Amazon, Kakao) appeared as a frame that uses AI speakers as'search or input devices'. On the other hand, telecommunications operators (SKT, KT) showed prominent frames for IPTV, which is the parent company's flagship business, and 'auxiliary device' of the telecommunication business. Furthermore, the frame of "personalization of products and voice service" was remarkable for OS operators (MS, Apple), and the frame for IT device manufacturers (Samsung) was "Internet of Things (IoT) Integrated Intelligence System". The econd, result id that the trend of the topic frame by AI speaker development period (by year) showed a tendency to develop around AI technology in the first phase (2014-2016), and in the second phase (2017-2018), the social relationship between AI technology and users It was related to interaction, and in the third phase (2019), there was a trend of shifting from AI technology-centered to user-centered. As a result of QAP analysis, it was found that news frames by business operator and development period in AI speaker development are socially constituted by determinants of media discourse. The implication of this study was that the evolution of AI speakers was found by the characteristics of the parent company and the process of co-evolution due to interactions between users by business operator and development period. The implications of this study are that the results of this study are important indicators for predicting the future prospects of AI speakers and presenting directions accordingly.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.49 no.3
• /
• pp.1-10
• /
• 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 the Korean Institute of Landscape Architecture
• /
• v.50 no.5
• /
• pp.69-79
• /
• 2022

This study aims to assess the current understanding of the landscape of wind power facilities as renewable energy sources that supply sightseeing, tourism, and other opportunities. Therefore, social media data related to the landscape of wind power facilities experienced by visitors from different regions was analyzed. The analysis results showed that the common characteristics of the landscape of wind power facilities are based on the scale of wind power facilities, the distance between overlook points of wind power facilities, the visual openness of the wind power facilities from the overlook points, and the terrain where the wind power facilities are located. In addition, the preference for wind power facilities is higher in places where the shape of wind power facilities and the surrounding landscape can be clearly seen- flat ground or the sea are considered better landscapes. Negative keywords about the landscape appear on Gade Mountain in Taibai, Meifeng Mountain in Taibai, Taiqi Mountain, and Gyeongju Wind Power Generation Facilities on Gyeongshang Road in Gangwon. The keyword 'negation' occurs when looking at wind power facilities at close range. Because of the high angle of the view, viewers can feel overwhelmed seeing the size of the facility and the ridge simultaneously, feeling psychological pressure. On the contrary, positive landscape adjectives are obtained from wind power facilities on flat ground or the sea. Visitors think that the visual volume of the landscape is fully ensured on flat ground or the sea, and it is a symbolic element that can represent the site. This study analyzes landscape awareness based on the opinions of visitors who have experienced wind power facilities. However, wind power facilities are built in different areas. Therefore, landscape characteristics are different, and there are many variables, such as viewpoints and observers, so the research results are difficult to popularize and have limitations. In recent years, landscape damage due to the construction of wind power facilities has become a hot issue, and the domestic methods of landscape evaluation of wind power facilities are unsatisfactory. Therefore, when evaluating the landscape of wind power facilities, the scale of wind power facilities, the inherent natural characteristics of the area where wind power facilities are set up, and the distance between wind power facilities and overlook points are important elements to consider. In addition, wind power facilities are set in the natural environment, which needs to be protected. Therefore, from the landscape perspective, it is necessary to study the landscape of wind power facilities and the surrounding environment.

• Journal of Intelligence and Information Systems
• /
• v.26 no.3
• /
• pp.91-108
• /
• 2020

Korea's famous soccer players are steadily performing well in international leagues, which led to higher interests of Korean fans in the international leagues. Reflecting the growing social phenomenon of rising interests on international leagues by Korean fans, the study examined the overall consumer perception in the consumption of uniform by domestic soccer fans and compared the changes in perception following the transfers of the players. Among others, the paper examined the consumer perception and purchase factors of soccer fans shown in social media, focusing on periods before and after the recruitment of Heung-Min Son to English Premier League's Tottenham Football Club. To this end, the EPL uniform is the collection keyword the paper utilized and collected consumer postings from domestic website and social media via Python 3.7, and analyzed them using Ucinet 6, NodeXL 1.0.1, and SPSS 25.0 programs. The results of this study can be summarized as follows. First, the uniform of the club that consistently topped the league, has been gaining attention as a popular uniform, and the players' performance, and the players' position have been identified as key factors in the purchase and search of professional football uniforms. In the case of the club, the actual ranking and whether the league won are shown to be important factors in the purchase and search of professional soccer uniforms. The club's emblem and the sponsor logo that will be attached to the uniform are also factors of interest to consumers. In addition, in the decision making process of purchase of a uniform by professional soccer fan, uniform's form, marking, authenticity, and sponsors are found to be more important than price, design, size, and logo. The official online store has emerged as a major purchasing channel, followed by gifts for friends or requests from acquaintances when someone travels to the United Kingdom. Second, a classification of key control categories through the convergence of iteration correlation analysis and Clauset-Newman-Moore clustering algorithm shows differences in the classification of individual groups, but groups that include the EPL's club and player keywords are identified as the key topics in relation to professional football uniforms. Third, between 2002 and 2006, the central theme for professional football uniforms was World Cup and English Premier League, but from 2012 to 2015, the focus has shifted to more interest of domestic and international players in the English Premier League. The subject has changed to the uniform itself from this time on. In this context, the paper can confirm that the major issues regarding the uniforms of professional soccer players have changed since Ji-Sung Park's transfer to Manchester United, and Sung-Yong Ki, Chung-Yong Lee, and Heung-Min Son's good performances in these leagues. The paper also identified that the uniforms of the clubs to which the players have transferred to are of interest. Fourth, both male and female consumers are showing increasing interest in Son's league, the English Premier League, which Tottenham FC belongs to. In particular, the increasing interest in Son has shown a tendency to increase interest in football uniforms for female consumers. This study presents a variety of researches on sports consumption and has value as a consumer study by identifying unique consumption patterns. It is meaningful in that the accuracy of the interpretation has been enhanced by using a cluster analysis via convergence of iteration correlation analysis and Clauset-Newman-Moore clustering algorithm to identify the main topics. Based on the results of this study, the clubs will be able to maximize its profits and maintain good relationships with fans by identifying key drivers of consumer awareness and purchasing for professional soccer fans and establishing an effective marketing strategy.

• Journal of Intelligence and Information Systems
• /
• v.18 no.2
• /
• pp.143-156
• /
• 2012

People easily believe that news and stock index are closely related. They think that securing news before anyone else can help them forecast the stock prices and enjoy great profit, or perhaps capture the investment opportunity. However, it is no easy feat to determine to what extent the two are related, come up with the investment decision based on news, or find out such investment information is valid. If the significance of news and its impact on the stock market are analyzed, it will be possible to extract the information that can assist the investment decisions. The reality however is that the world is inundated with a massive wave of news in real time. And news is not patterned text. This study suggests the stock-index invest model based on "News Big Data" opinion mining that systematically collects, categorizes and analyzes the news and creates investment information. To verify the validity of the model, the relationship between the result of news opinion mining and stock-index was empirically analyzed by using statistics. Steps in the mining that converts news into information for investment decision making, are as follows. First, it is indexing information of news after getting a supply of news from news provider that collects news on real-time basis. Not only contents of news but also various information such as media, time, and news type and so on are collected and classified, and then are reworked as variable from which investment decision making can be inferred. Next step is to derive word that can judge polarity by separating text of news contents into morpheme, and to tag positive/negative polarity of each word by comparing this with sentimental dictionary. Third, positive/negative polarity of news is judged by using indexed classification information and scoring rule, and then final investment decision making information is derived according to daily scoring criteria. For this study, KOSPI index and its fluctuation range has been collected for 63 days that stock market was open during 3 months from July 2011 to September in Korea Exchange, and news data was collected by parsing 766 articles of economic news media M company on web page among article carried on stock information>news>main news of portal site Naver.com. In change of the price index of stocks during 3 months, it rose on 33 days and fell on 30 days, and news contents included 197 news articles before opening of stock market, 385 news articles during the session, 184 news articles after closing of market. Results of mining of collected news contents and of comparison with stock price showed that positive/negative opinion of news contents had significant relation with stock price, and change of the price index of stocks could be better explained in case of applying news opinion by deriving in positive/negative ratio instead of judging between simplified positive and negative opinion. And in order to check whether news had an effect on fluctuation of stock price, or at least went ahead of fluctuation of stock price, in the results that change of stock price was compared only with news happening before opening of stock market, it was verified to be statistically significant as well. In addition, because news contained various type and information such as social, economic, and overseas news, and corporate earnings, the present condition of type of industry, market outlook, the present condition of market and so on, it was expected that influence on stock market or significance of the relation would be different according to the type of news, and therefore each type of news was compared with fluctuation of stock price, and the results showed that market condition, outlook, and overseas news was the most useful to explain fluctuation of news. On the contrary, news about individual company was not statistically significant, but opinion mining value showed tendency opposite to stock price, and the reason can be thought to be the appearance of promotional and planned news for preventing stock price from falling. Finally, multiple regression analysis and logistic regression analysis was carried out in order to derive function of investment decision making on the basis of relation between positive/negative opinion of news and stock price, and the results showed that regression equation using variable of market conditions, outlook, and overseas news before opening of stock market was statistically significant, and classification accuracy of logistic regression accuracy results was shown to be 70.0% in rise of stock price, 78.8% in fall of stock price, and 74.6% on average. This study first analyzed relation between news and stock price through analyzing and quantifying sensitivity of atypical news contents by using opinion mining among big data analysis techniques, and furthermore, proposed and verified smart investment decision making model that could systematically carry out opinion mining and derive and support investment information. This shows that news can be used as variable to predict the price index of stocks for investment, and it is expected the model can be used as real investment support system if it is implemented as system and verified in the future.

• Journal of Intelligence and Information Systems
• /
• v.23 no.4
• /
• pp.1-31
• /
• 2017

Modern businesses are adopting new technologies to serve their markets better as well as to improve efficiency and productivity. The advertising industry has continuously experienced disruptions from the traditional channels (radio, television and print media) to new complex ones including internet, social media and mobile-based advertising. This case study focuses on proposing intelligent advertising business model in Seoul's metro network. Seoul has one of the world's busiest metro network and transports a huge number of travelers on a daily basis. The high number of travelers coupled with a well-planned metro network creates a platform where marketers can initiate engagement and interact with both customers and potential customers. In the current advertising model, advertising is on illuminated and framed posters in the stations and in-car, non-illuminated posters, and digital screens that show scheduled arrivals and departures of metros. Some stations have digital screens that show adverts but they do not have location capability. Most of the current advertising media have one key limitation: space. For posters whether illuminated or not, one space can host only one advert at a time. Empirical literatures show that there is room for improving this advertising model and eliminate the space limitation by replacing the poster adverts with digital advertising platform. This new model will not only be digital, but will also provide intelligent advertising platform that is driven by data. The digital platform will incorporate location sensing, e-commerce, and mobile platform to create new value to all stakeholders. Travel cards used in the metro will be registered and the card scanners will have a capability to capture traveler's data when travelers tap their cards. This data once analyzed will make it possible to identify different customer groups. Advertisers and marketers will then be able to target specific customer groups, customize adverts based on the targeted consumer group, and offer a wide variety of advertising formats. Format includes video, cinemagraphs, moving pictures, and animation. Different advert formats create different emotions in the customer's mind and the goal should be to use format or combination of formats that arouse the expected emotion and lead to an engagement. Combination of different formats will be more effective and this can only work in a digital platform. Adverts will be location based, ensuring that adverts will show more frequently when the metro is near the premises of an advertiser. The advertising platform will automatically detect the next station and screens inside the metro will prioritize adverts in the station where the metro will be stopping. In the mobile platform, customers who opt to receive notifications will receive them when they approach the business premises of advertiser. The mobile platform will have indoor navigation for the underground shopping malls that will allow customers to search for facilities within the mall, products they may want to buy as well as deals going on in the underground mall. To create an end-to-end solution, the mobile solution will have a capability to allow customers purchase products through their phones, get coupons for deals, and review products and shops where they have bought a product. The indoor navigation will host intelligent mobile-based advertisement and a recommendation system. The indoor navigation will have adverts such that when a customer is searching for information, the recommendation system shows adverts that are near the place traveler is searching or in the direction that the traveler is moving. These adverts will be linked to the e-commerce platform such that if a customer clicks on an advert, it leads them to the product description page. The whole system will have multi-language as well as text-to-speech capability such that both locals and tourists have no language barrier. The implications of implementing this model are varied including support for small and medium businesses operating in the underground malls, improved customer experience, new job opportunities, additional revenue to business model operator, and flexibility in advertising. The new value created will benefit all the stakeholders.

• The Journal of the Korea Contents Association
• /
• v.20 no.10
• /
• pp.89-99
• /
• 2020

In this study, we tried to produce moving-image works through sentiment analysis of music. First, Google natural language API was used for the sentiment analysis of lyrics, then the result was applied to the image visualization rules. In prior engineering researches, text-based sentiment analysis has been conducted to understand users' emotions and attitudes by analyzing users' comments and reviews in social media. In this study, the data was used as a material for the creation of artworks so that it could be used for aesthetic expressions. From the machine's point of view, emotions are substituted with numbers, so there is a limit to normalization and standardization. Therefore, we tried to overcome these limitations by linking the results of sentiment analysis of lyrics data with the rules of formative elements in visual arts. This study aims to transform existing traditional art works such as literature, music, painting, and dance to a new form of arts based on the viewpoint of the machine, while reflecting the current era in which artificial intelligence even attempts to create artworks that are advanced mental products of human beings. In addition, it is expected that it will be expanded to an educational platform that facilitates creative activities, psychological analysis, and communication for people with developmental disabilities who have difficulty expressing emotions.

• The Journal of Korean Academic Society of Nursing Education
• /
• v.9 no.2
• /
• pp.264-275
• /
• 2003

The purpose of this study were to develop a smoking preventive education program for elementary students and evaluate it's effectiveness. This study was a quasi experimental study under the nonequivalent control group with pretest-posttest design. The subjects of this study were 62 who are attending elementary school(31 for each group), 2 different district elementary school. The subjects were matched by grade, similar in anti-smoking educational background of smoking, as well as their residence and income level of their families. The instruments used in this study was 18 criterion referenced test items modeled by Dick & Carey that were developed by researchers for evaluating the subjects' knowledge and attitude about smoking. A pretest was administered a week before treatment The program given to the experimental group is composed of the texts explaining the poisonous substances in tobacco, social and cultural harmfulness of smoking to the body and psychology, indirect smoking, smoking of pregnant women, motives of smoking, refusal skills of smoking; and for the subjects' understanding and the better results of study - pictures, role play, discussion, text through computer based multi-media, puzzle searching for hidden pictures, cross-word puzzle, and finally compensation. The data were collected for 50 days form mid- September to the end of October in the year of 2000, composed of formative evaluation, pre-test and summative evaluation via 2 sessions. Accordingly, the collected data were analysed by t-test, paired t-test, repeated measure ANOVA by the SAS program. This research summarize the findings as follows; 1. There was a significant difference in knowledge between the experimental group(after 1 wks t=10.4680, p=.0001; after 4 wks t= 9.310, p=.0001) and control group(after 1 wks t=0.0420, p= .9669; after 4 wks t= -0.378 p=.7079) in between the results of 1 and 4 week after education in summative evaluation (F=27.45, P=.0001). 2. There was non statistical significant difference in attitude between the experimental group (after 1 wks t=1.2292, p=0.2286 ; after 4 wks t=1.330, p=0.1935) and control group (after 1 wks t=0.1819, p=0.8569 ; after 4 wks t=0.2970, p=0.7685) in between the results of 1 and 4 week after education in summative evaluation(F=0.71, P=0.494). To sum up, the statistics of conclusive analysis evaluative for the children under school age of the 'knowledge acquisition' about smoking harmfulness. On the other hand, as there was already sound attitude about smoking, the evaluation of attitude was non significant difference between control group and experimental group, just there was partially significant difference.

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