• Title/Summary/Keyword: 텍스트 연구

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Effective Text Question Analysis for Goal-oriented Dialogue (목적 지향 대화를 위한 효율적 질의 의도 분석에 관한 연구)

  • Kim, Hakdong;Go, Myunghyun;Lim, Heonyeong;Lee, Yurim;Jee, Minkyu;Kim, Wonil
    • Journal of Broadcast Engineering
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    • v.24 no.1
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    • pp.48-57
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    • 2019
  • The purpose of this study is to understand the intention of the inquirer from the single text type question in Goal-oriented dialogue. Goal-Oriented Dialogue system means a dialogue system that satisfies the user's specific needs via text or voice. The intention analysis process is a step of analysing the user's intention of inquiry prior to the answer generation, and has a great influence on the performance of the entire Goal-Oriented Dialogue system. The proposed model was used for a daily chemical products domain and Korean text data related to the domain was used. The analysis is divided into a speech-act which means independent on a specific field concept-sequence and which means depend on a specific field. We propose a classification method using the word embedding model and the CNN as a method for analyzing speech-act and concept-sequence. The semantic information of the word is abstracted through the word embedding model, and concept-sequence and speech-act classification are performed through the CNN based on the semantic information of the abstract word.

A Suggestion of the Direction of Construction Disaster Document Management through Text Data Classification Model based on Deep Learning (딥러닝 기반 분류 모델의 성능 분석을 통한 건설 재해사례 텍스트 데이터의 효율적 관리방향 제안)

  • Kim, Hayoung;Jang, YeEun;Kang, HyunBin;Son, JeongWook;Yi, June-Seong
    • Korean Journal of Construction Engineering and Management
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    • v.22 no.5
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    • pp.73-85
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    • 2021
  • This study proposes an efficient management direction for Korean construction accident cases through a deep learning-based text data classification model. A deep learning model was developed, which categorizes five categories of construction accidents: fall, electric shock, flying object, collapse, and narrowness, which are representative accident types of KOSHA. After initial model tests, the classification accuracy of fall disasters was relatively high, while other types were classified as fall disasters. Through these results, it was analyzed that 1) specific accident-causing behavior, 2) similar sentence structure, and 3) complex accidents corresponding to multiple types affect the results. Two accuracy improvement experiments were then conducted: 1) reclassification, 2) elimination. As a result, the classification performance improved with 185.7% when eliminating complex accidents. Through this, the multicollinearity of complex accidents, including the contents of multiple accident types, was resolved. In conclusion, this study suggests the necessity to independently manage complex accidents while preparing a system to describe the situation of future accidents in detail.

A Study on Consumer perception changes of online education before and after COVID-19 using text mining (텍스트 마이닝을 활용한 온라인 교육에 대한 소비자 인식 변화 분석: COVID-19 전후를 중심으로)

  • Sohn, Minsung;Im, Meeja;Park, Kyunghwan
    • Journal of Digital Convergence
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    • v.19 no.1
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    • pp.29-43
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    • 2021
  • Coinciding with the advent of COVID-19, online education is on the rise both domestically and globally, and has become an absolutely necessary and irreplaceable form of education. It is a very curious question what the perception of people about the suddenly growing form of education is, and how it has changed. This study investigated changes in consumers' perception of online education using big data. To this end, we divided the time into four stages: before COVID-19 (November to December 2019), after the triggering of COVID-19 (January to February 2020), right after the online classes started (March to April 2020), after experiencing some online education (May to June 2020). Then we conducted text mining, namely, keyword frequency analysis, network analysis, word cloud analysis, and sentiment analysis were performed. The implications derived as a result of the analysis can help education policy makers and educators working in the field to improve online education quality and establish its future directions.

An Analysis on Media Trends in Public Agency for Social Service Applying Text Mining (텍스트 마이닝을 적용한 사회서비스원 언론보도기사 분석)

  • Park, Hae-Keung;Youn, Ki-Hyok
    • Journal of Internet of Things and Convergence
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    • v.8 no.2
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    • pp.41-48
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    • 2022
  • This study tried to empirically explore which issues related to the social service agency for public(as below SSA), that is, social perceptions were formed, by using mess media related to the SSA. This study is meaningful in that it identifies the overall social perception and trend of SSA through public opinion. In order to extract media trend data, the search used the big data analysis system, Textom, to collect data from the representative portals Naver News and Daum News. The collected texts were 1,299 in 2020 and 1,410 in 2021, for a total of 2,709. As a result of the analysis, first, the most derived words in relation to the frequency of text appearance were 'SSA', 'establishment', and 'operation'. Second, as a result of the N-gram analysis, the pairs of words directly related to the SSA 'SSA and public', 'SSA and opening', 'SSA and launch', and 'SSA and Department Director', 'SSA and Staff', 'SSA and Caregiver' etc. Third, in the results of TF-IDF analysis and word network analysis, similar to the word occurrence frequency and N-gram results, 'establishment', 'operation', 'public', 'launch', 'provided', 'opened', ' 'Holding' and 'Care' were derived. Based on the above analysis results, it was suggested to strengthen the emergency care support group, to commercialize it in detail, and to stabilize jobs.

A Study on the Oral Characteristics in Personal Narrative Storytelling (체험 이야기하기의 구술적 특성에 대하여)

  • Kim, Kyung-Seop
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.4
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    • pp.143-150
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    • 2022
  • The folk language that lives and breathes in modern works does not just come from old stories, but it is a personal narrative which is based on the experiences of the narrator. Like many genres in oral literature, most of these personal narratives occur from the impulse of communicating and reinventing rather than from the impulse of creating. Compared to traditional folktales, stories about an individual's experiences, such as personal narratives are often performed by adding the individual tendencies of the narrator. In so doing, the phenomenon of "processing the experience by estimating it and reinterpreting the memories roughly" occurs, and this is a significant factor in making the oral literature. However, the question that arises here is: How can we deal with these significant elements that are inevitably captured when performed orally? Text linguistics, the main methodology of this paper, implies the possibility of expressing the impromptu elements of oral literature. Also, textual linguistic analysis of personal narratives provides the possibility of discussing oral characteristics from various angles which have been difficult to analyze, such as on-site atmosphere, speaker mistakes, contradictions in stories, and audience reactions. Hence, it is possible to effectively discuss oral-poetics in oral literature which are based on the one-off of 'words', the 'roughness' of the on-site atmosphere, and the stackability of the 'wisdom of crowds'. Furthermore, it is expected to contribute to the study of personal narrative storytelling that plays an important part in Veabal art in community culture.

Sentiment Analysis and Issue Mining on All-Solid-State Battery Using Social Media Data (소셜미디어 분석을 통한 전고체 배터리 감성분석과 이슈 탐색)

  • Lee, Ji Yeon;Lee, Byeong-Hee
    • The Journal of the Korea Contents Association
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    • v.22 no.10
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    • pp.11-21
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    • 2022
  • All-solid-state batteries are one of the promising candidates for next-generation batteries and are drawing attention as a key component that will lead the future electric vehicle industry. This study analyzes 10,280 comments on Reddit, which is a global social media, in order to identify policy issues and public interest related to all-solid-state batteries from 2016 to 2021. Text mining such as frequency analysis, association rule analysis, and topic modeling, and sentiment analysis are applied to the collected global data to grasp global trends, compare them with the South Korean government's all-solid-state battery development strategy, and suggest policy directions for its national research and development. As a result, the overall sentiment toward all-solid-state battery issues was positive with 50.5% positive and 39.5% negative comments. In addition, as a result of analyzing detailed emotions, it was found that the public had trust and expectation for all-solid-state batteries. However, feelings of concern about unresolved problems coexisted. This study has an academic and practical contribution in that it presented a text mining analysis method for deriving key issues related to all-solid-state batteries, and a more comprehensive trend analysis by employing both a top-down approach based on government policy analysis and a bottom-up approach that analyzes public perception.

Trend Analysis of Corona Virus(COVID-19) based on Social Media (소셜미디어에 나타난 코로나 바이러스(COVID-19) 인식 분석)

  • Yoon, Sanghoo;Jung, Sangyun;Kim, Young A
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.5
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    • pp.317-324
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    • 2021
  • This study deals with keywords from social media on domestic portal sites related to COVID-19, which is spreading widely. The data were collected between January 20 and August 15, 2020, and were divided into three stages. The precursor period is before COVID-19 started spreading widely between January 20 and February 17, the serious period denotes the spread in Daegu between February 18 and April 20, and the stable period is the decrease in numbers of confirmed infections up to August 15. The top 50 words were extracted and clustered based on TF-IDF. As a result of the analysis, the precursor period keywords corresponded to congestion of the Situation. The frequent keywords in the serious period were Nation and Infection Route, along with instability surrounding the Treatment of COVID-19. The most common keywords in all periods were infection, mask, person, occurrence, confirmation, and information. People's emotions are becoming more positive as time goes by. Cafes and blogs share text containing writers' thoughts and subjectivity via the internet, so they are the main information-sharing spaces in the non-face-to-face era caused by COVID-19. However, since selectivity and randomness in information delivery exists, a critical view of the information produced on social media is necessary.

Outdoor Healing Places Perception Analysis Using Named Entity Recognition of Social Media Big Data (소셜미디어 빅데이터의 개체명 인식을 활용한 옥외 힐링 장소 인식 분석)

  • Sung, Junghan;Lee, Kyungjin
    • Journal of the Korean Institute of Landscape Architecture
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    • v.50 no.5
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    • pp.90-102
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    • 2022
  • In recent years, as interest in healing increases, outdoor spaces with the concept of healing have been created. For more professional and in-depth planning and design, the perception and characteristics of outdoor healing places through social media posts were analyzed using NER. Text mining was conducted using 88,155 blog posts, and frequency analysis and clique cohesion analysis were conducted. Six elements were derived through a literature review, and two elements were added to analyze the perception and the characteristics of healing places. As a result, visitors considered place elements, date and time, social elements, and activity elements more important than personnel, psychological elements, plants and color, and form and shape when visiting healing places. The analysis allowed the derivation of perceptions and characteristics of healing places through keywords. From the results of the Clique, keywords, such as places, date and time, and relationship, were clustered, so it was possible to know where, when, what time, and with whom people were visiting places for healing. Through the study, the perception and characteristics of healing places were derived by analyzing large-scale data written by visitors. It was confirmed that specific elements could be used in planning and marketing.

Analysis of Twitter Post with 'Self-Iinjury' and 'Ssuicide' Using Text Mining (텍스트 마이닝기법을 활용한 '자해' 및 '자살' 관련 트위터 게시물 분석)

  • Yuri Lee;Hoin Kwon
    • Korean Journal of Culture and Social Issue
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    • v.29 no.1
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    • pp.147-170
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    • 2023
  • This study explored keywords and key topics by collecting posts related to 'self-Iinjury' and 'suicide' through Twitter. The study subjects were selected as posts containing related hashtags related to self-injury and suicide from October 29, 2019 to November 30, 2020. Text mining based on collected posts resulted in a total of 11 key topics: -6 related to 'self-Iinjury' and 5 related to 'suicide'. The main message in the topic is as follows. First, looking at the main messages contained in the topic, they honestly expressed self-harm and suicide experiences that are difficult to express offline online, and used SNS as a channelpath for requesting help requests. Second, there were common and discriminatory characteristics in posts related to 'self-Iinjury' and 'suicide'. Although topics related to 'self-Iinjury' mainly revealed emotional control and interpersonal functions of self-harm, messages related to 'suicide' showed more clearly messages about suicide prevention addressing and social problems. These results are meaningful in that they can understand the opinions of people who have experienced self-harm and suicide accidents and the public voice on self-harm and suicide-related issues could be better understood, and that this study seeks for effective self-harm and suicide prevention and intervention measures for self-harm and suicide issues.

A Comparative Study on theories of Korean Theatre and Japan Theatre : focused on 'Kwandaega(廣大歌)' and 'Poogjahwajun(風姿花傳)' (한·일 연극이론의 비교 연구 - 「광대가(廣大歌)」와 「풍자화전(風姿花傳)」을 중심으로)

  • Kim, Ikdoo
    • (The) Research of the performance art and culture
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    • no.23
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    • pp.5-36
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    • 2011
  • The purposes of this treatise are to compare theories of theatre in 'Kwandaega' with theories of theatre in 'Poongjahwajun', to recognize differences of theories between the former and the latter, and to find out the comparative characteristics of theories of Korean theatre. There are four differences between the former and the latter. These are as follows; Firstly, in the aspect of contents, the former is consisted of discussions about nature of theatre, discussions about acting, discussions about staging, and the latter is consisted of discussions about nature of theatre, discussions about acting, discussions about staging, discussions about origin, and discussions about dramaturgy. Secondly, in the aspect of nature, the nature of theatre in the former is recognition and practice as 'homo performans', the nature of theatre in the latter is realization of 'flower[花]'. Thirdly, in the aspect of acting, discussions about acting of the former are consisted of 'Sachae' theory'(Inmulchirae, Sasulchirae, Dekm, Nerumsae), discussions about acting of the latter are consisted of method of training per ages, method of training per role playings, trainings in everyday life. Fourthly, in the aspect of staging, the focus of staging in the former is realization of an endless series of changes[千變萬化], the focus of staging in the latter is realization of 'flower[花]'. There are four characteritics in the theories of Kwangdaega. These are as follows; Firstly, the contents of kwangdaega are consisted of discussions about nature of theatre, discussions about acting, discussions about staging. This theory is theory centered on actor/actress. Secondly, the nature of thestre in Kwangdaega is recognition and practice as 'homo performans', supporting of self-generational values, supporting of folk, new interpretation about secularism. Thirdly, the discussions about acting are consist of 'Sachae Theory'. Fourthly, the discussions about staging are consisted of realizations of an endless series of changes[千變萬化]