• Title/Summary/Keyword: 텍스트 빈도 분석

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A Research on the Use of Information Resources of the Humanities Scholars in Korea (인문학자의 정보자원 이용에 관한 연구)

  • Yoon, Cheong-Ok
    • Journal of the Korean Society for information Management
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    • v.26 no.1
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    • pp.7-34
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    • 2009
  • The purpose of this study is to investigate the use of information resources of the humanities scholars in Korea and suggest the strategic planning of academic library and information services to serve their needs. To collect data, a mail survey was conducted during the period of November 2007 through January 2008. Out of 799 humanities scholars sampled from 25 universities, 132 responded with the completion rate of 16%. Major findings in this study are as follows: First, the majority of the humanities scholars distribute their time equally to research and education, and conduct independent research. Second, they still largely depend on print resources, including scholarly journals, books, and manuscripts for getting information, while using some online information resource mostly in text such as electronic documents and journals. They expect that the frequency of using such print resources would not decline much, but the use of online resources could definitely increase in the next five years. Some variances in the behavior were observed among the groups of scholars according to their research experiences. It is suggested that academic libraries (1) conduct more active outreach, (2) prioritize between traditional and electronic resources, (3) plan information literacy education for traditional resources.

The Narrative Discourse of the Novel and the Film L'Espoir (소설과 영화 『희망 L'Espoir』의 서사담론)

  • Oh, Se-Jung
    • Cross-Cultural Studies
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    • v.48
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    • pp.289-323
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    • 2017
  • L'Espoir, a novel by Andre Malraux, contains traits of the genre of literacy reportage that depicts the full account of the Spanish Civil War as non-fiction based on his personal experience of participating in war; the novel has been dramatized into a semi-documentary film that corresponds to reportage literature. A semi-documentary film is the genre of film that pursues realistic illustration of social incidents or phenomenon. Despite difference in types of genre of the novel and the film L'Espoir, such creative activities deserve close relevance and considerable narrative connectivity. Therefore, $G{\acute{e}}rard$ Genette's narrative discourse of novel and film based on narrative theory carries value of research. Every kind of story, in a narrative message, has duplicate times in which story time and discourse time are different. This is because, in a narrative message, one event may occur before or later than another, told lengthily or concisely, and aroused once or repeatedly. Accordingly, analyzing differing timeliness of the actual event occurring and of recording that event is in terms of order, duration, and frequency. Since timeliness of order, duration, and frequency indicates dramatic pace that controls the passage of a story, it appears as an editorial notion in the novel and the film L'Espoir. It is an aesthetic discourse raising curiosity and shock, the correspondence of time in arranging, summarizing, deleting the story. In addition, Genette mentions notions of speech and voice to clearly distinguish position and focalization of a narrator or a speaker in text. The necessity to discriminate 'who speaks' and 'who sees' comes from difference in views of the narrator of text and the text. The matter of 'who speaks' is about who portrays narrator of the story. However, 'who sees' is related to from whose stance the story is being narrated. In the novel L'Espoir, change of focalization was ushered through zero focalization and internal focalization, and pertains to the multicamera in the film. Also, the frame story was commonly taken as metadiegetic type of voice in both film and novel of L'Espoir. In sum, narrative discourse in the novel and the film L'Espoir is the dimension of story communication among text, the narrator, and recipient.

Exploratory Big Data Analysis of Albert Camus's La Peste in Post Corona era (포스트 코로나 시대 알베르 카뮈의 『페스트』에 관한 탐색적 빅데이터 분석)

  • MIN, Jinyoung
    • The Journal of the Convergence on Culture Technology
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    • v.7 no.1
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    • pp.432-438
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    • 2021
  • This dissertation's object is to confirm the drastic popularity of La Peste of Albert Camus in Korea post-corona society using big data as the mean of inductive research. Analyzing news articles concerning Camus and investigating word frequency of the book La Peste will affirm the implications La Peste has on current Korea society as the outbreak spreads. As an analysis tool, Bigkinds of Korea Press Foundation and Nuagedemots, the French version of Word Cloud were used. For the past 30 years, Albert Camus has been known in Korea as the writer of L'étranger, but after the epidemic, he earned more reputation with La Peste. Compared to L'étranger that rebelled against the world's absurdity with ennui, La peste emphasizes the importance of resistance accompanied by solidarity. La peste conveys hope by depicting disastrous situations of citizens who confront the plague by organizing a health college. The novel delivers a lot of ethical inspiration to humanity in this exceptional circumstance of COVID-19.

Study on the Viewers' Perception of Investigative Journalism Before and After Pandemic Using Big Data (빅데이터를 활용한 팬데믹 전후 탐사보도프로그램에 대한 시청자 인식연구)

  • Kyunghee Kim;Soonchul Kwon;Seunghyun Lee
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.3
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    • pp.311-320
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    • 2023
  • This paper analyzes viewers' perception of investigative journalism before and after COVID-19, and examines the direction of investigative journalism using big data. Based on the previous research set as a social science model, the relationship between words related to big data TV current affairs programs and investigative journalism in this paper was investigated before and after the appearance of COVID-19. We visualized changes in viewers' perception of investigative journalism by analyzing text data obtained through the use of Textom, with TV current affairs programs and investigative journalism as keywords. Data was collected from 2017 to June 2022 and refined for analysis. We visualized connectivity centrality using Ucinet 6.0 and Netdraw, and clustered the number of keywords and their frequency using Concor analysis. Our study found a clear change in viewer perception before and after the pandemic. As an implication of this thesis, big data analysis was conducted with the investigative journalism as the main keyword, and the direction of the investigative journalism was presented based on the analysis. Furthermore, based on previous research, we suggest effective approaches for investigative journalism after the pandemic to better engage viewers.

Sensitivity Identification Method for New Words of Social Media based on Naive Bayes Classification (나이브 베이즈 기반 소셜 미디어 상의 신조어 감성 판별 기법)

  • Kim, Jeong In;Park, Sang Jin;Kim, Hyoung Ju;Choi, Jun Ho;Kim, Han Il;Kim, Pan Koo
    • Smart Media Journal
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    • v.9 no.1
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    • pp.51-59
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    • 2020
  • From PC communication to the development of the internet, a new term has been coined on the social media, and the social media culture has been formed due to the spread of smart phones, and the newly coined word is becoming a culture. With the advent of social networking sites and smart phones serving as a bridge, the number of data has increased in real time. The use of new words can have many advantages, including the use of short sentences to solve the problems of various letter-limited messengers and reduce data. However, new words do not have a dictionary meaning and there are limitations and degradation of algorithms such as data mining. Therefore, in this paper, the opinion of the document is confirmed by collecting data through web crawling and extracting new words contained within the text data and establishing an emotional classification. The progress of the experiment is divided into three categories. First, a word collected by collecting a new word on the social media is subjected to learned of affirmative and negative. Next, to derive and verify emotional values using standard documents, TF-IDF is used to score noun sensibilities to enter the emotional values of the data. As with the new words, the classified emotional values are applied to verify that the emotions are classified in standard language documents. Finally, a combination of the newly coined words and standard emotional values is used to perform a comparative analysis of the technology of the instrument.

A Study on Analysis of consumer perception of YouTube advertising using text mining (텍스트 마이닝을 활용한 Youtube 광고에 대한 소비자 인식 분석)

  • Eum, Seong-Won
    • Management & Information Systems Review
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    • v.39 no.2
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    • pp.181-193
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    • 2020
  • This study is a study that analyzes consumer perception by utilizing text mining, which is a recent issue. we analyzed the consumer's perception of Samsung Galaxy by analyzing consumer reviews of Samsung Galaxy YouTube ads. for analysis, 1,819 consumer reviews of YouTube ads were extracted. through this data pre-processing, keywords for advertisements were classified and extracted into nouns, adjectives, and adverbs. after that, frequency analysis and emotional analysis were performed. Finally, clustering was performed through CONCOR. the summary of this study is as follows. the first most frequently mentioned words were Galaxy Note (n = 217), Good (n = 135), Pen (n = 40), and Function (n = 29). it can be judged through the advertisement that consumers "Galaxy Note", "Good", "Pen", and "Features" have good functional aspects for Samsung mobile phone products and positively recognize the Note Pen. in addition, the recognition of "Samsung Pay", "Innovation", "Design", and "iPhone" shows that Samsung's mobile phone is highly regarded for its innovative design and functional aspects of Samsung Pay. second, it is the result of sentiment analysis on YouTube advertising. As a result of emotional analysis, the ratio of emotional intensity was positive (75.95%) and higher than negative (24.05%). this means that consumers are positively aware of Samsung Galaxy mobile phones. As a result of the emotional keyword analysis, positive keywords were "good", "good", "innovative", "highest", "fast", "pretty", etc., negative keywords were "frightening", "I want to cry", "discomfort", "sorry", "no", etc. were extracted. the implication of this study is that most of the studies by quantitative analysis methods were considered when looking at the consumer perception study of existing advertisements. In this study, we deviated from quantitative research methods for advertising and attempted to analyze consumer perception through qualitative research. this is expected to have a great influence on future research, and I am sure that it will be a starting point for consumer awareness research through qualitative research.

Analysis of Research Trends in Tax Compliance using Topic Modeling (토픽모델링을 활용한 조세순응 연구 동향 분석)

  • Kang, Min-Jo;Baek, Pyoung-Gu
    • The Journal of the Korea Contents Association
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    • v.22 no.1
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    • pp.99-115
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    • 2022
  • In this study, domestic academic journal papers on tax compliance, tax consciousness, and faithful tax payment (hereinafter referred to as "tax compliance") were comprehensively analyzed from an interdisciplinary perspective as a representative research topic in the field of tax science. To achieve the research purpose, topic modeling technique was applied as part of text mining. In the flow of data collection-keyword preprocessing-topic model analysis, potential research topics were presented from tax compliance related keywords registered by the researcher in a total of 347 papers. The results of this study can be summarized as follows. First, in the keyword analysis, keywords such as tax investigation, tax avoidance, and honest tax reporting system were included in the top 5 keywords based on simple term-frequency, and in the TF-IDF value considering the relative importance of keywords, they were also included in the top 5 keywords. On the other hand, the keyword, tax evasion, was included in the top keyword based on the TF-IDF value, whereas it was not highlighted in the simple term-frequency. Second, eight potential research topics were derived through topic modeling. The topics covered are (1) tax fairness and suppression of tax offenses, (2) the ideology of the tax law and the validity of tax policies, (3) the principle of substance over form and guarantee of tax receivables (4) tax compliance costs and tax administration services, (5) the tax returns self- assessment system and tax experts, (6) tax climate and strategic tax behavior, (7) multifaceted tax behavior and differential compliance intentions, (8) tax information system and tax resource management. The research comprehensively looked at the various perspectives on the tax compliance from an interdisciplinary perspective, thereby comprehensively grasping past research trends on tax compliance and suggesting the direction of future research.

A Study on the Factors of Well-aging through Big Data Analysis : Focusing on Newspaper Articles (빅데이터 분석을 활용한 웰에이징 요인에 관한 연구 : 신문기사를 중심으로)

  • Lee, Chong Hyung;Kang, Kyung Hee;Kim, Yong Ha;Lim, Hyo Nam;Ku, Jin Hee;Kim, Kwang Hwan
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.5
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    • pp.354-360
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    • 2021
  • People hope to live a healthy and happy life achieving satisfaction by striking a good work-life balance. Therefore, there is a growing interest in well-aging which means living happily to a healthy old age without worry. This study identified important factors related to well-aging by analyzing news articles published in Korea. Using Python-based web crawling, 1,199 articles were collected on the news service of portal site Daum till November 2020, and 374 articles were selected which matched the subject of the study. The frequency analysis results of text mining showed keywords such as 'elderly', 'health', 'skin', 'well-aging', 'product', 'person', 'aging', 'female', 'domestic' and 'retirement' as important keywords. Besides, a social network analysis with 45 important keywords revealed strong connections in the order of 'skin-wrinkle', 'skin-aging' and 'old-health'. The result of the CONCOR analysis showed that 45 main keywords were composed of eight clusters of 'life and happiness', 'disease and death', 'nutrition and exercise', 'healing', 'health', and 'elderly services'.

A Study on the Semantic Network Structure of the Regime in the Image Contents (영상콘텐츠분야의 정권별 의미연결망 연구)

  • Hwang, Go-Eun;Moon, Shin-Jung
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.28 no.3
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    • pp.217-240
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    • 2017
  • The purpose of this study was to investigate the semantic network analysis to understand image contents and to examine the degree to which words, word clusters contributed to the formation of semantic map within image contents. For this research, from 1993 until 2016 the field of the image contents were collected for a total of 2,624 cases papers. The word appeared in Title analyzed the social network by using the R program of Big Data. The results were as follows: First, The field of image contents is based on researches related to 'image', 'media' and 'contents'. Second, there is a three-step flow ('education' -> 'media' -> 'contents') of research in the field of image contents. Third, researches related to 'broadcasting', 'digital', 'technology', and 'production' were continuously carried out. Finally, There were new research subjects for each regime.

Exploration of the Emotion for Daily Conversation on Facebook (페이스북 일상담화의 감정 탐색)

  • Hwang, Yoosun
    • The Journal of the Korea Contents Association
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    • v.16 no.2
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    • pp.1-13
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    • 2016
  • The purpose of this study is to explore the emotions of Facebook. Various types of emotions are being exchanged on Facebook. The emotional reactions make the Facebook different from previous electronic bulletin board. According to previous researches, computer-mediated communication can deliver visual symbols and non-verbal cues to enhance the abundance of meanings. Data were collected from 205 Facebook users and the number of users' posts were total 10308. The contents analysis was conducted to explore emotions of the 10308 Facebook posts. The results showed that the most frequent emotion was pleasure. The emotional distributions were different according to the contents types; text, video, photo, and link. For the text content type, emotion of curiosity was apparent and for the photo content type, emotion of love was more frequent than others, and for the video content type, emotion of surprise was salient. The results of the analysis for the shared contents also revealed that pleasure and hope were more frequent emotions than other emotions.