• Journal of the Korea Convergence Society
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• v.11 no.5
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• pp.199-207
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• 2020

Recently, big data analysis has drawn attention in various fields as it can generate value from large amounts of data and is also used to run political campaigns or predict results. However, existing research had limitations in compiling information about candidates at a high-level by analyzing only specific SNS data. Therefore, this study analyses news trends, topics extraction, sentiment analysis, keyword analysis, comment analysis for the 2017 presidential election of South Korea. The results show that various topics had been generated, and online opinions are extracted for trending keywords of respective candidates. This study also shows that portal news and comments can serve as useful tools for predicting the public's opinion on social issues. This study will This paper advances a building strategic course of action by providing a method of analyzing public opinion across various fields.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.1
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• pp.99-107
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• 2023

Recently, the rate of death and safety accidents at construction sites is the highest among all kinds of industries. In order to apply artificial intelligence technology to construction sites, it is essential to secure a dataset which can be used as a basic training data. In this paper, a number of image data were collected through actual construction site, for which major construction equipment objects mainly operated in civil engineering sites were defined. The optimal training dataset construction was completed by annotation process of about 90,000 image dataset. Reliability of the dataset was verified with the mAP of over 90 % in use of YOLO, a representative model in the field of object detection. The construction equipment training dataset built in this study has been released which is currently available on the public data portal of the Ministry of Public Administration and Security. This dataset is expected to be freely used for any application of object detection technology on construction sites especially in the field of construction safety in the future.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.5
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• pp.903-913
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• 2015

The Korea Agency of Education, Promotion and Information Service in Food, Agriculture, Forestry and Fisheries launched a public data portal service in January 2015. The service provides customized information for consumers through an agri-food recommendation system built-in portal service. The recommendation system has fallowing characteristics. First, the system can increase recommendation accuracy by using a wide variety of agri-food related data, including SNS opinion mining, consumer's purchase data, climate data, and wholesale price data. Second, the system uses segmentation method based on consumer's lifestyle and megatrends factors to overcome the cold start problem. Third, the system recommends agri-foods to users reflecting various preference contextual factors by using recommendation algorithm, dirichlet-multinomial distribution. In addition, the system provides diverse information related to recommended agri-foods to increase interest in agri-food of service users.

• Journal of Contemporary Eastern Asia
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• v.18 no.2
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• pp.16-32
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• 2019

Media manipulation of breaking news through article selection, ranking and tweaking of social media data and comment streams is a growing concern for society. We argue that the combination of human and machine curation on media portals marks a new period for news media and journalism. Although intermediary platforms routinely claim that they are merely the neutral technological platform which facilitates news and information flows, rejecting any criticisms that they are operating as de facto media organisations; instead, we argue for an alternative, more active interpretation of their roles. In this article we provide a contemporary account of the South Korean ('Korean') online news media ecology as an exemplar of how contemporary media technologies, and in particular portals and algorithmic recommender systems, perform a powerful role in shaping the kind of news and information that citizens access. By highlighting the key stakeholders and their positions within the production, publication and distribution of news media, we argue that the overall impact of the major portal platforms of Naver and Kakao is far more consequential than simply providing an entertaining media diet for consumers. These portals are central in designing how and which news is sourced, produced and then accessed by Korean citizens. From a regulatory perspective the provision of news on the portals can be a somewhat ambiguous and moving target, subject to soft and harder regulatory measures. While we investigate a specific case study of the South Korean experience, we also trace out connections with the larger global media ecology. We have relied on policy documents, stakeholder interviews and portal user 'walk throughs' to understand the changing role of news and its surfacing on a distinctive breed of media platforms.

• Spatial Information Research
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• v.20 no.2
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• pp.35-44
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• 2012

Recently, Web map service is actively accomplished in both private companies and public offices. As a platform, it exists variously from desktop to smartphone. The technology being used has a trend to develop continuously. Also, Web map system provides various open API for people who use geospatial service and data mashup. In this paper, RIA technology which is popularly used recently in web map service w ill be applied to introduce the functions different language map services are mostly using. Based on users' feeling about different web browser's speed, test and analysis have been accomplished. The result is that there are different characteristics according to different functions such as JavaScript, Silverlight, Flex. Actual test has been personally carried out on map service in Seoul GIS portal system. The comprehensive conclusion is that Silverlight has more outstanding function compared with other RIA techniques under the test environment.

• Korean Journal of Artificial Intelligence
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• v.9 no.1
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• pp.29-35
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• 2021

In this paper, we analyzed the factors of adoption and implemented a predictive model to activate the adoption of animals. Recently, animal shelters are saturated due to the abandonment and loss of companion animals. To address this, we need to find a way to encourage adoption. In this paper, a study was conducted using two data from an open data portal provided by Austin, Texas. First, a correlation analysis was conducted to identify the attributes that affect the result value, and it was found that Animal Type Intake, Intake Type, and Age upon Outcome influence the Outcome Type with correlation coefficients of 0.4, 0.26, and -0.2, respectively. For these attributes, the analysis was conducted using Multiclass Logistic Regression. As a result, dogs had a higher probability of Adoption than cats, and animals subjected to euthanasia were more likely to adopt. In the case of Public Assist and Stray, it was found that the Missing rate was high. Also, the length of stay for cats increased to 12.5 years of age, while dogs generally adopted smoothly at all ages. These results showed an overall accuracy of 62.7% and an average accuracy of 91.7%, showing a fairly reliable result. Therefore, it seems that it can be used to develop a plan to promote the adoption of animals according to various factors. Also, it can be expanded to various services by interlocking with the webserver.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.347-351
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• 2022

Farmers E-Market is a website that allows agricultural workers to direct market their products to buyers without the use of a middleman. That theory is blockchain system will be used by authors to accomplish this. The system, which is built on a public blockchain system, supports sustainability, shippers, and consumers. Farmers can keep track of their farming activities. Customers can review the product's history and track its journey through carriers to delivery after making a purchase. Farmers are encouraged to get information about their interests promptly in a blockchain-enabled system like this. This functionality is being used by small-scale farmers to form groups based on their location to attract large-scale customers, renegotiate farming techniques or volumes, and enter into contracts with buyers. The analysis shows the use of blockchain technology with a farmer's portal that keeps the video of trading data of crops, taking into account the qualities of blockchain such as values and create or transaction data. The proposal merges python as a programming language with a blockchain system to benefit farmers, vendors, and individuals by preserving transactions.

• 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.

• Healthcare Informatics Research
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• v.24 no.4
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• pp.253-262
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• 2018

Objectives: We reviewed digital epidemiological studies to characterize how researchers are using digital data by topic domain, study purpose, data source, and analytic method. Methods: We reviewed research articles published within the last decade that used digital data to answer epidemiological research questions. Data were abstracted from these articles using a data collection tool that we developed. Finally, we summarized the characteristics of the digital epidemiological studies. Results: We identified six main topic domains: infectious diseases (58.7%), non-communicable diseases (29.4%), mental health and substance use (8.3%), general population behavior (4.6%), environmental, dietary, and lifestyle (4.6%), and vital status (0.9%). We identified four categories for the study purpose: description (22.9%), exploration (34.9%), explanation (27.5%), and prediction and control (14.7%). We identified eight categories for the data sources: web search query (52.3%), social media posts (31.2%), web portal posts (11.9%), webpage access logs (7.3%), images (7.3%), mobile phone network data (1.8%), global positioning system data (1.8%), and others (2.8%). Of these, 50.5% used correlation analyses, 41.3% regression analyses, 25.6% machine learning, and 19.3% descriptive analyses. Conclusions: Digital data collected for non-epidemiological purposes are being used to study health phenomena in a variety of topic domains. Digital epidemiology requires access to large datasets and advanced analytics. Ensuring open access is clearly at odds with the desire to have as little personal data as possible in these large datasets to protect privacy. Establishment of data cooperatives with restricted access may be a solution to this dilemma.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1259-1269
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• 2015

Recently, big data is positioning as a keyword in the academic circles. And usefulness of big data is carried into government, a local public body and enterprise as well as academic circles. Also they are endeavoring to obtain useful information in big data. This research mainly deals with analyses of box office success or failure of films using text mining. For data, it used a portal site 'D' and film review data, grade point average and the number of screens gained from the Korean Film Commission. The purpose of this paper is to propose a model to predict whether a film is success or not using these data. As a result of analysis, the correct classification rate by the prediction model method proposed in this paper is obtained 95.74%.