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Analysis of Social Trends for Electric Scooters Using Dynamic Topic Modeling and Sentiment Analysis (동적 토픽 모델링과 감성 분석을 활용한 전동킥보드에 대한 사회적 동향 분석)

  • Kyoungok, Kim;Yerang, Shin
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.1
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    • pp.19-30
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    • 2023
  • An electric scooter(e-scooter), one popularized micro-mobility vehicle has shown rapidly increasing use in many cities. In South Korea, the use of e-scooters has greatly increased, as some companies have launched e-scooter sharing services in a few large cities, starting with Seoul in 2018. However, the use of e-scooters is still controversial because of issues such as parking and safety. Since the perception toward the means of transportation affects the mode choice, it is necessary to track the trends for electric scooters to make the use of e-scooters more active. Hence, this study aimed to analyze the trends related to e-scooters. For this purpose, we analyzed news articles related to e-scooters published from 2014 to 2020 using dynamic topic modeling to extract issues and sentiment analysis to investigate how the degree of positive and negative opinions in news articles had changed. As a result of topic modeling, it was possible to extract three different topics related to micro-mobility technologies, shared e-scooter services, and regulations for micro-mobility, and the proportion of the topic for regulations for micro-mobility increased as shared e-scooter services increased in recent years. In addition, the top positive words included quick, enjoyable, and easy, whereas the top negative words included threat, complaint, and ilegal, which implies that people satisfied with the convenience of e-scooter or e-scooter sharing services, but safety and parking issues should be addressed for micro-mobility services to become more active. In conclusion, this study was able to understand how issues and social trends related to e-scooters have changed, and to determine the issues that need to be addressed. Moreover, it is expected that the research framework using dynamic topic modeling and sentiment analysis will be helpful in determining social trends on various areas.

The Characteristics and Background of Gwanyo's Production of White Porcelain with "Byeol(別)" Inscription in 16th and 17th Century Joseon (조선 16~17세기 관요(官窯) '별(別)'명 백자의 성격과 제작 배경)

  • KIM, Kwihan
    • Korean Journal of Heritage: History & Science
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    • v.55 no.2
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    • pp.214-230
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    • 2022
  • This paper discusses the characteristics and background of the production of white porcelain with the "Byeol(別)" inscription. Such porcelain was produced by the government-run porcelain kiln, Gwanyo(官窯), in the 16th and 17th centuries (from the 1560s to the 1640s), during the Joseon dynasty. The white porcelain ware, inscribed with either the term Byeol or "jwa(左)" and "u(右)," constituted a dual production system of white porcelain by Gwanyo starting in the 1560s. However, to date, few studies have examined Byeol-inscribed white porcelain. This, therefore, makes it difficult to achieve a comprehensive understanding of the evolution of inscriptions on the white porcelain produced by Gwanyo in the 15th to 17th centuries. Besides a regular annual stock of porcelain(年例進上磁器), Gwanyo also produced and supplied additional porcelain ware, or Byeol-gi, at the behest of the royal family or the court of Joseon. Byeol-inscribed white porcelain is a form of Byeol-gi, produced through extra firing, or Byeolbeon(別燔). According to use, Byeol-gi can be categorized as an item for national use(國用) or an item for internal use(內用). However, if the porcelain only carries the "Byeol(別)" inscription, it is difficult to identify its characteristics. Furthermore, as part of the annual production of porcelain was for the supply of Byeol-gi, and then for other purposes, the white porcelain came to be inscribed with dots indicating a change in ownership. In the 16th century, the royal family increased its consumption of white porcelain based on Shinyu Gongan(辛酉貢案), the government's fiscal reform measures. To guarantee a stable supply of exceptional Byeol-gi in light of Gwanyo's decline in the 1560s, the royal family benefited from the inscription of "Byeol." The white porcelain produced by Gwanyo was divided into annual offerings-those with the inscriptions "jwa(左)" and "u(右)"-and Byeol-gi, those with the inscription of "Byeol." They were managed separately from the commencement of production. Byeol-inscribed white porcelain was produced until the 1640s. During the mid-and late 1640s, Byeolbeon was temporarily suspended. Starting in the 1650s, the white clay used to produce the annual stock of white porcelain was sourced from regions other than those providing the clay for Byeol-gi production. The former used clay from Wonju(原州土) and Seosan(瑞山土), while the latter used clay from Gyeongju(慶州土) and Seoncheon(宣川土). According to the literature, the clay from Gyeongju and Seoncheon was much cleaner than that from Wonju and Seosan. Byeolbeon thus underwent a transformation, whereby production was separately managed, right from the stage of white clay mining. Ultimately, the need for the separate management of Byeol-gi through inscriptions diminished, resulting in the disappearance of Byeol-inscribed white porcelain.

A Study on the Landscape Cognition of Wind Power Plant in Social Media (소셜미디어에 나타난 풍력발전시설의 경관 인식 연구)

  • Woo, Kyung-Sook;Suh, Joo-Hwan
    • Journal of the Korean Institute of Landscape Architecture
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    • v.50 no.5
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    • pp.69-79
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    • 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.

Asbestos Trend in Korea from 1918 to 2027 Using Text Mining Techniques in a Big Data Environment (빅데이터환경에서 텍스트마이닝 기법을 활용한 한국의 석면 트렌드 (1918년~2027년))

  • Yul Roh;Hyeonyi Jeong;Byungno Park;Chaewon Kim;Yumi Kim;Mina Seo;Haengsoo Shin;Hyunwook Kim;Yeji Sung
    • Economic and Environmental Geology
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    • v.56 no.4
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    • pp.457-473
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    • 2023
  • Asbestos has been produced, imported and used in various industries in Korea over the past decades. Since asbestos causes fatal diseases such as malignant mesothelioma and lung cancer, the use of asbestos has been generally banned in Korea since 2009. However, there are still many asbestos-containing materials around us, and safe management is urgently needed. This study aims to examine asbestos-related trend changes using major asbestos-related keywords based on the asbestos trend analysis using big data for the past 32 years (1991 to 2022) in Korea. In addition, we reviewed both domestic trends related to the production, import, and use of asbestos before 1990 and asbestos-related policies from 2023 to 2027. From 1991 to 2000, main keywords related to asbestos were research, workers, carcinogens, and the environment because the carcinogenicity of asbestos was highlighted due to domestic production, import, and use of asbestos. From 2001 to 2010, the main keywords related to asbestos were lung cancer, litigation, carcinogens, exposure, and companies because lawsuits were initiated in the US and Japan in relation to carcinogenicity due to asbestos. From 2011 to 2020, the high ranking keywords related to asbestos were carcinogen, baseball field, school, slate, building, and abandoned asbestos mine due to the seriousness of the asbestos problem in Korea. From 2021 to present (2023), the main search keywords related to asbestos such as school, slate (asbestos cement), buildings, landscape stone, environmental impact assessment, apartment, and cement appeared.

Analysis on Dynamics of Korea Startup Ecosystems Based on Topic Modeling (토픽 모델링을 활용한 한국의 창업생태계 트렌드 변화 분석)

  • Heeyoung Son;Myungjong Lee;Youngjo Byun
    • Knowledge Management Research
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    • v.23 no.4
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    • pp.315-338
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    • 2022
  • In 1986, Korea established legal systems to support small and medium-sized start-ups, which becomes the main pillars of national development. The legal systems have stimulated start-up ecosystems to have more than 1 million new start-up companies founded every year during the past 30 years. To analyze the trend of Korea's start-up ecosystem, in this study, we collected 1.18 million news articles from 1991 to 2020. Then, we extracted news articles that have the keywords "start-up", "venture", and "start-up". We employed network analysis and topic modeling to analyze collected news articles. Our analysis can contribute to analyzing the government policy direction shown in the history of start-up support policy. Specifically, our analysis identifies the dynamic characteristics of government influenced by external environmental factors (e.g., society, economy, and culture). The results of our analysis suggest that the start-up ecosystems in Korea have changed and developed mainly by the government policies for corporation governance, industrial development planning, deregulation, and economic prosperity plan. Our frequency keyword analysis contributes to understanding entrepreneurial productivity attributed to activities among the networked components in industrial ecosystems. Our analyses and results provide practitioners and researchers with practical and academic implications that can help to establish dedicated support policies through forecast tasks of the economic environment surrounding the start-ups. Korean entrepreneurial productivity has been empowered by growing numbers of large companies in the mobile phone industry. The spectrum of large companies incorporates content startups, platform providers, online shopping malls, and youth-oriented start-ups. In addition, economic situational factors contribute to the growth of Korean entrepreneurial productivity the economic, which are related to the global expansions of the mobile industry, and government efforts to foster start-ups. Our research is methodologically implicative. We employ natural language processes for 30 years of media articles, which enables more rigorous analysis compared to the existing studies which only observe changes in government and policy based on a qualitative manner.

Investigating Topics of Incivility Related to COVID-19 on Twitter: Analysis of Targets and Keywords of Hate Speech (트위터에서의 COVID-19와 관련된 반시민성 주제 탐색: 혐오 대상 및 키워드 분석)

  • Kim, Kyuli;Oh, Chanhee;Zhu, Yongjun
    • Journal of the Korean Society for information Management
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    • v.39 no.1
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    • pp.331-350
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    • 2022
  • This study aims to understand topics of incivility related to COVID-19 from analyzing Twitter posts including COVID-19-related hate speech. To achieve the goal, a total of 63,802 tweets that were created between December 1st, 2019, and August 31st, 2021, covering three targets of hate speech including region and public facilities, groups of people, and religion were analyzed. Frequency analysis, dynamic topic modeling, and keyword co-occurrence network analysis were used to explore topics and keywords. 1) Results of frequency analysis revealed that hate against regions and public facilities showed a relatively increasing trend while hate against specific groups of people and religion showed a relatively decreasing trend. 2) Results of dynamic topic modeling analysis showed keywords of each of the three targets of hate speech. Keywords of the region and public facilities included "Daegu, Gyeongbuk local hate", "interregional hate", and "public facility hate"; groups of people included "China hate", "virus spreaders", and "outdoor activity sanctions"; and religion included "Shincheonji", "Christianity", "religious infection", "refusal of quarantine", and "places visited by confirmed cases". 3) Similarly, results of keyword co-occurrence network analysis revealed keywords of three targets: region and public facilities (Corona, Daegu, confirmed cases, Shincheonji, Gyeongbuk, region); specific groups of people (Coronavirus, Wuhan pneumonia, Wuhan, China, Chinese, People, Entry, Banned); and religion (Corona, Church, Daegu, confirmed cases, infection). This study attempted to grasp the public's anti-citizenship public opinion related to COVID-19 by identifying domestic COVID-19 hate targets and keywords using social media. In particular, it is meaningful to grasp public opinion on incivility topics and hate emotions expressed on social media using data mining techniques for hate-related to COVID-19, which has not been attempted in previous studies. In addition, the results of this study suggest practical implications in that they can be based on basic data for contributing to the establishment of systems and policies for cultural communication measures in preparation for the post-COVID-19 era.

History and Characteristics of Risk Perception and Response Related to Science: Focused on Blood Pressure (과학에 관련된 위험 인식과 대응의 역사와 특징 -혈압을 중심으로-)

  • Wonbin Jang;Minchul Kim
    • Journal of The Korean Association For Science Education
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    • v.43 no.6
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    • pp.549-562
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    • 2023
  • The current society is in the VUCA era, where various risks produced by humans are spread along with the development of science and technology. There is a need to increase the level of risk literacy of citizens to strengthen their daily preparedness to respond to these risks. For this on, it is necessary to reconsider the role of science education so that risks can be perceived and responded to scientifically and objectively. Accordingly, in order to investigate the role of science education in a risk society, this study reviewed the history of risk perception and response related to science and analyzed its characteristics. In this process, perception and response to risks arising from blood pressure were analyzed in three contexts (historical context, curriculum context, textbook context). For historical context, journals registered in SCIE were selected as research subjects among journals where research related to the history of knowledge of the heart and cardiovascular system was conducted. Papers with the keywords 'hypertension' and 'history' were selected from the journals, and changes in perception and responses related to blood pressure were compared and analyzed by period. The curriculum context is analyzed from the 1st national curriculum to the 2022 revised curriculum, and content elements and achievement standard related to blood pressure were compared and analyzed. It was confirmed that risks arising from blood pressure were not included from the 1st to the 6th national curriculum, and that risks arising from blood pressure were included from the 7th national curriculum (excluding the 2009 revised curriculum). For the textbook context, the 7th national curriculum BiologyⅠ, the 2015 revised curriculum Life ScienceⅠ, and Health were selected, and through text mining, keywords that representing curriculums and textbooks were selected, and the presentation of risk perception and response was analyzed based on the keywords. And by analyzing the figures and tables presented in the textbook, the characteristics of risk perception and risk response were derived. This study is meaningful in that it was able to confirm the role of risk perception and response in science education.

A study on quantification of α-quartz, cristobalite, kaolinite mixture in respirable dust using by FTIR (FTIR를 이용한 호흡성 분진중 α-quartz, cristobalite, kaolinite 혼합물 정량 분석 연구)

  • Eun Cheol Choi;Seung Ho Lee
    • Analytical Science and Technology
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    • v.36 no.6
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    • pp.315-323
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    • 2023
  • This study is to quantify α-quartz, cristobalite and kaolinite using by FTIR in respirable dust generated in the mining workplace. Various minerals in mines can interfere with peaks when quantifying respirable crystalline silica by FTIR. Therefore, for accurate quantification, it is necessary to remove interfering substances or correct the peaks that cause interference. To confirm the peaks occurring in α-quartz, cristobalite and kaolinite, each standard material was diluted with KBr and scanned in the range of 400 cm-1 to 4000 cm-1 using by FTIR. As a result of scanning the analytes, it was decided to use the peaks of 797.66 cm-1 and 695.25 cm-1 for α-quartz, 621.58 cm-1 for cristobalite, and 3696.47 cm-1 for kaolinite. When the above materials are mixed, interference occurs at the peak for quantification, which is corrected by the calculation formula. The analysis of the mixture of α-quartz and cristobalite shows the average bias (%) of 2.64 (corrected) at α-quartz (797.66 cm-1), 5.61 (uncorrected) at α-quartz (695.25 cm-1) and 1.51 (uncorrected) at cristobalite (621.58 cm-1). The analysis of the mixture of α-quartz and kaolinite shows the average bias(%) of 1.79(corrected) at α-quartz (797.66 cm-1), 3.92 (corrected) at α-quartz (695.25 cm-1) and 2.58 (uncorrected) at kaolinite (3696.47 cm-1). The analysis of the mixture of cristobalite and kaolinite shows the average bias (%) of 2.15 (corrected) at cristobalite (621.58 cm-1), 4.32 (uncorrected) at kaolinite (3696.47 cm-1). The analysis of the mixture of αquartz and cristobalite and kaolinite shows the average bias (%) of 1.93(corrected) at α-quartz (797.66 cm-1), 6.47 (corrected) at α-quartz (695.25 cm-1) and 1.77 (corrected) at cristobalite (621.58 cm-1) and 2.61 (uncorrected) at kaolinite (3696.47 cm-1). The experimental results showed that the deviation caused by peak interference by two or three substances could be corrected to less than 6 % of the average deviation. This study showed the possibility of correcting and quantifying when various interfering substances that are difficult to remove are mixed.

Distribution Patterns of Surface Sediments of the Jangan Linear Sand Ridge off the Northern Taean Peninsula, in the Mid-west Coast of Korea (서해 중부 태안반도 북부 해역의 장안사퇴 표층퇴적물 분포 특성)

  • TAE SOO CHANG;EUNIL LEE;DO-SEONG BYUN;HWAYOUNG LEE;SEUNG-GYUN BAEK
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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    • v.29 no.1
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    • pp.14-27
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    • 2024
  • Unlike the shelf sand ridges moribund in motion, nearshore sand ridges are highly mobile, sensitive to changes in ocean environments, thereby becoming of particular interest with respect to morphological changes. About 5 km off the Daesan port, the Jangan Sand Ridge has been undergoing severe subsea morphological change over the past two decades. Understanding the nature of sand ridges is critical to elucidate the causes of morphological changes. In this context, this study aims at understanding the characteristics and distribution patterns of surface sediments of the ridge and its vicinity. For this purpose, 227 sediment samples were acquired using a grab-sampler, the grain sizes being analysed by the sieve-pipette method. In addition, comparison of grain sizes in sediments between 1997 and 2021 was made in order to investigate the 25-years change in sediment composition. Surface sediments along the ridge axis are fine to medium sands with 2-3 phi in mean grain size, whereas, in the trough of ridge, the sediments are composed of gravels and muddy sandy gravels with mean sizes of -2 to -6 phi. Sediments in the crest of the ridge are well-sorted with normal distribution, on the other hand, the basal sediments are poorly-sorted and positively skewed. Along the ridge crest, the sediments are negatively skewed. From 1997 to 2021, the ridge sediments became largely coarser about 0.5 phi. Such coarsening trend in mean grain size can be explained either by elimination of fine sediments during high waves in winter or elimination of fines suspended during sand mining activities in the past. Spatial distribution pattern of surface sediments shows that ca. 30 m thick of the sand ridge itself overlies the thin relict gravels. The strong asymmetry of sand ridge, the exposure of ridge base, and reworked gravel lags suggest that Jangan sand ridge is probably sediment-deficit and hence erosive in nature at present.

Influence analysis of Internet buzz to corporate performance : Individual stock price prediction using sentiment analysis of online news (온라인 언급이 기업 성과에 미치는 영향 분석 : 뉴스 감성분석을 통한 기업별 주가 예측)

  • Jeong, Ji Seon;Kim, Dong Sung;Kim, Jong Woo
    • Journal of Intelligence and Information Systems
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    • v.21 no.4
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    • pp.37-51
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    • 2015
  • Due to the development of internet technology and the rapid increase of internet data, various studies are actively conducted on how to use and analyze internet data for various purposes. In particular, in recent years, a number of studies have been performed on the applications of text mining techniques in order to overcome the limitations of the current application of structured data. Especially, there are various studies on sentimental analysis to score opinions based on the distribution of polarity such as positivity or negativity of vocabularies or sentences of the texts in documents. As a part of such studies, this study tries to predict ups and downs of stock prices of companies by performing sentimental analysis on news contexts of the particular companies in the Internet. A variety of news on companies is produced online by different economic agents, and it is diffused quickly and accessed easily in the Internet. So, based on inefficient market hypothesis, we can expect that news information of an individual company can be used to predict the fluctuations of stock prices of the company if we apply proper data analysis techniques. However, as the areas of corporate management activity are different, an analysis considering characteristics of each company is required in the analysis of text data based on machine-learning. In addition, since the news including positive or negative information on certain companies have various impacts on other companies or industry fields, an analysis for the prediction of the stock price of each company is necessary. Therefore, this study attempted to predict changes in the stock prices of the individual companies that applied a sentimental analysis of the online news data. Accordingly, this study chose top company in KOSPI 200 as the subjects of the analysis, and collected and analyzed online news data by each company produced for two years on a representative domestic search portal service, Naver. In addition, considering the differences in the meanings of vocabularies for each of the certain economic subjects, it aims to improve performance by building up a lexicon for each individual company and applying that to an analysis. As a result of the analysis, the accuracy of the prediction by each company are different, and the prediction accurate rate turned out to be 56% on average. Comparing the accuracy of the prediction of stock prices on industry sectors, 'energy/chemical', 'consumer goods for living' and 'consumer discretionary' showed a relatively higher accuracy of the prediction of stock prices than other industries, while it was found that the sectors such as 'information technology' and 'shipbuilding/transportation' industry had lower accuracy of prediction. The number of the representative companies in each industry collected was five each, so it is somewhat difficult to generalize, but it could be confirmed that there was a difference in the accuracy of the prediction of stock prices depending on industry sectors. In addition, at the individual company level, the companies such as 'Kangwon Land', 'KT & G' and 'SK Innovation' showed a relatively higher prediction accuracy as compared to other companies, while it showed that the companies such as 'Young Poong', 'LG', 'Samsung Life Insurance', and 'Doosan' had a low prediction accuracy of less than 50%. In this paper, we performed an analysis of the share price performance relative to the prediction of individual companies through the vocabulary of pre-built company to take advantage of the online news information. In this paper, we aim to improve performance of the stock prices prediction, applying online news information, through the stock price prediction of individual companies. Based on this, in the future, it will be possible to find ways to increase the stock price prediction accuracy by complementing the problem of unnecessary words that are added to the sentiment dictionary.