• Journal of Digital Convergence
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• v.18 no.1
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• pp.137-146
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• 2020

NLP means the technology that mechanically analyzes a language spoken by a human and makes it into a form that can be understood by a computer. This is important because it is a core technology for communication between humans and devices, which is the basis of artificial intelligence. In this paper, I analyzed patent information of US and Korea in order to identify technical trends related to NLP, especially semantic analysis. and the purpose of this study is to provide meaningful information for future research on NLP. In conclusion, the number of Korea patents is 7.9% compared to the USA and the different frequencies of the major keywords were found to differ from country to country in technical direction. In addition, the upward or downward keywords are twice as many in the U.S. as in Korea, and reflect the trend of the times relatively more. Based on these results, in future study, I will analysis how upward trending keywords are described in actual patents for concrete technology prediction.

• 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.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.51-66
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• 2018

As AI (Artificial Intelligence) technologies have been swiftly evolved, a lot of products and services are under development in various fields for better users' experience. On this technology advance, negative effects of AI technologies also have been discussed actively while there exists positive expectation on them at the same time. For instance, many social issues such as trolley dilemma and system security issues are being debated, whereas autonomous vehicles based on artificial intelligence have had attention in terms of stability increase. Therefore, it needs to check and analyse major social issues on artificial intelligence for their development and societal acceptance. In this paper, multi-categorical sentiment analysis is conducted over online public opinion on artificial intelligence after identifying the trending topics related to artificial intelligence for two years from January 2016 to December 2017, which include the event, match between Lee Sedol and AlphaGo. Using the largest web portal in South Korea, online news, news headlines and news comments were crawled. Considering the importance of trending topics, online public opinion was analysed into seven multiple sentimental categories comprised of anger, dislike, fear, happiness, neutrality, sadness, and surprise by topics, not only two simple positive or negative sentiment. As a result, it was found that the top sentiment is "happiness" in most events and yet sentiments on each keyword are different. In addition, when the research period was divided into four periods, the first half of 2016, the second half of the year, the first half of 2017, and the second half of the year, it is confirmed that the sentiment of 'anger' decreases as goes by time. Based on the results of this analysis, it is possible to grasp various topics and trends currently discussed on artificial intelligence, and it can be used to prepare countermeasures. We hope that we can improve to measure public opinion more precisely in the future by integrating empathy level of news comments.

• Industry Promotion Research
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• v.9 no.3
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• pp.205-212
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• 2024

This study aims to analyze the impact of catchphrases used in job postings on job applications in the context of accelerating social participation of Generation Z and changing business environments. To this end, case studies of catchphrases used in job postings by domestic and international companies were conducted. In addition, job postings for the Korea Electric Power Corporation (KEPCO), a well-known public institution, were created using four trend keywords: 'general phrases,' 'eco-friendliness,' 'employee welfare,' and 'social issues (equality).' An online survey was conducted to analyze the impact of catchphrases in job postings on job applications, and the results showed that 83% of respondents found that the catchphrases in job postings had a positive effect on their application decisions. Through in-depth interviews, the importance of design elements and catchphrases in job postings as perceived by actual job seekers was confirmed. In conclusion, this study aims to explore how catchphrases in job postings can facilitate smooth communication between companies and job seekers and strengthen corporate image promotion activities. It seeks to provide insights into how companies can effectively utilize catchphrases in job postings according to age and job type in future recruitment processes.