• Title/Summary/Keyword: 감정어

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Increase of Spoken Number of Syllables Using MIT(Melody Intonation Therapy) : Case Studies on older adult with stroke and aphasia (MIT(Melodic Intonation Therapy) 중심의 음악활동을 이용한 실어증을 가진 뇌졸중 노인의 음절 수 증가에 대한 사례 연구)

  • Hong, Do Kyoung
    • Journal of Music and Human Behavior
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    • v.2 no.2
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    • pp.57-67
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    • 2005
  • Most of stroke patients have not only physical difficulty but speech and neurological disorder because of hemiplegia and such unexpected changes cause psychologic disadaptability and absent-mindedness. Particularly, lowering of physical ability can lead to serious emotional problem from failure or frustration in daily life. Generally, treatment of patient with stroke put emphasis on physical rehabilitation but actually this patient had considerable speech disorder such as aphasia or articulation disorder. Moreover, failing of recognition function, mental disorder as hypochondria, and even visual and auditory disorder are represented. So it is effective to integrate verbal remediation and other treatments in medical care environment. In particular, patients with language disorder very often wither psychologically therefore it is efficient to use of music therapy that gives opulent emotion to aphasia patients. And primarily to investigate the effects of 10 sessions treatments; change in spoken total number of syllables, to confirm their own value by success of given task and reassure about themselves ability. All of 10 sessions stages were scored by MIT manual and its improvement were measured, that is, accomplishment was analyzed within each level in order to prove detail change of spoken total number of syllables. The result of this program organized from 2 syllables to 4 syllables is summarized as follows. Subject A completed in preliminary stage Level I, in 2 syllables case advanced to Level III in fifth session and to Level IV in seventh session, in 3 syllables case advanced to Level III in seventh session and to Level IV in ninth session, and in 4 syllables case showed 8% low success rate in first session but after repeated practice increased considerably in sixth session and in advanced to Level III in eighth session to Level IV in tenth session. Subject B also completed in preliminary stage Level I, in 2 syllables case advanced to Level III in forth session and to Level IV in sixth session, in 3 syllables case advanced to Level III in fifth session and to Level IV in seventh session, and in 4 syllables case showed 10% low success rate in first session and increased considerably in fifth session and in advanced to Level III in seventh session but could not reach to Level IV until tenth session. As a result, it was shown that music therapy using MIT was not statistically meaningful but improved spoken total number of syllables and success rate of task had improved as a whole. Therefore, music intervention using MIT it has positive affect on verbal ability of patients with Broca's Aphasia and their language rehabilitation.

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Value and Prosect of individual diary as research materials : Based on the "The 12th May Diaries Collection" (개인 일기의 연구 자료로서의 가치와 전망 "5월12일 일기컬렉션"을 중심으로)

  • Choi, Hyo Jin;Yim, Jin Hee
    • The Korean Journal of Archival Studies
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    • no.46
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    • pp.95-152
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    • 2015
  • "Archives of Everyday Life" refers to an organization or facility which collects, appraises, selects and preserves the document from the memory of individuals, groups, or a society through categorizing and classifying lives and cultures of ordinary people. The document includes materials such as diaries, autobiography, letters, and notes. It also covers any digital files or hypertext like posts from blogs and online communities, or photos uploaded on Social Network Services. Many research fields including the Records Management Studies has continuously claimed the necessity of collection and preservation of ordinary people's records on daily life produced every moment. Especially diary is a written record reflecting the facts experienced by an individual and his self-examination. Its originality, individuality and uniqueness are considered truly valuable as a document regardless of the era. Lately many diaries have been discovered and presented to the historical research communities, and diverse researchers in human and social studies have embarked more in-depth research on diaries, their authors, and social background of the time. Furthermore, researchers from linguistics, educational studies, and psychology analyze linguistic behaviors, status of cultural assimilation, and emotional or psychological changes of an author. In this study, we are conducting a metastudy from various research on diaries in order to reaffirm the value of "The 12th May Diaries Collection" as everyday life archives. "The 12th May Diaries Collection" consists of diaries produced and donated directly by citizens on the 12th May every year. It was only 2013 when Digital Archiving Institute in Univ. of Myungji organized the first "Annual call for the 12th May". Now more than 2,000 items were collected including hand writing diaries, digital documents, photos, audio and video files, etc. The age of participants also varies from children to senior citizens. In this study, quantitative analysis will be made on the diaries collected as well as more profound discoveries on the detailed contents of each item. It is not difficult to see stories about family and friends, school life, concerns over career path, daily life and feelings of citizens ranging all different generations, regions, and professions. Based on keyword and descriptors of each item, more comprehensive examination will be further made. Additionally this study will also provide suggestions to examine future research opportunities of these diaries for different fields such as linguistics, educational studies, historical studies or humanities considering diverse formats and contents of diaries. Finally this study will also discuss necessary tasks and challenges for "the 12th May Diaries Collection" to be continuously collected and preserved as Everyday Life Archives.

On the Problem of Virtue in Confucian and Neoconfucian Philosophy (유학 및 신유학 철학에서의 덕의 문제)

  • Gabriel, Werner
    • (The)Study of the Eastern Classic
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    • no.50
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    • pp.89-120
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    • 2013
  • The concept of virtue seems to be one of the rare cases where the European and the Chinese traditions coincide. The meaning of the Latin word virtus and of Greek $aret{\acute{e}}$ seems to be similar to the Chinese $d{\acute{e}}$德. Most striking in virtue is that it is a capacity for self-realisation through action which is unique to man. On the other hand, there is something physical about it. It is the strength to do something. This strength overcomes the resistance of what is naturally given, it transforms the world, turns the natural world into a human one. In the Chinese tradition, $d{\acute{e}}$ 德, i.e. virtue, is therefore always connected with $da{\grave{o}}$ 道, the totality of natural forces. In the Chinese tradition, as opposed to the European one, virtue is itself considered to be a natural force that is present in man. This force sustains man's connectedness, unity and harmony with the surrounding world. Things exist through the unity of principle理 and ether氣. But the knowledge of this unity is due to principle. Moral and legal norms are shifted totally to the sphere of principle. Therefore their have found the final dissolution from a heroic models. Above all the classical Confucians, but also the other schools, would reply to this that there is nothing more precise than a concrete successful action. Its result fits the world perfectly. The difference is due to the differing interest of ethical thought. In the case of the Confucians the path is more direct. The actor establishes a precise pattern for other actions. Education therefore lies in detailed knowledge about forms of behaviour, not so much in conceptual differentiation. It is quite possible that generalisation may be a methodical prerequisite for success in this endeavour. That problem, too, is discussed. But the success of conceptualisation lies in the successful performance of individual actions, not in shaping actions in accordance with normative concepts.

Popularization of Marathon through Social Network Big Data Analysis : Focusing on JTBC Marathon (소셜 네트워크 빅데이터 분석을 통한 마라톤 대중화 : JTBC 마라톤대회를 중심으로)

  • Lee, Ji-Su;Kim, Chi-Young
    • Journal of Korea Entertainment Industry Association
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    • v.14 no.3
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    • pp.27-40
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    • 2020
  • The marathon has long been established as a representative lifestyle for all ages. With the recent expansion of the Work and Life Balance trend across the society, marathon with a relatively low barrier to entry is gaining popularity among young people in their 20s and 30s. By analyzing the issues and related words of the marathon event, we will analyze the spottainment elements of the marathon event that is popular among young people through keywords, and suggest a development plan for the differentiated event. In order to analyze keywords and related words, blogs, cafes and news provided by Naver and Daum were selected as analysis channels, and 'JTBC Marathon' and 'Culture' were extracted as key words for data search. The data analysis period was limited to a three-month period from August 13, 2019 to November 13, 2019, when the application for participation in the 2019 JTBC Marathon was started. For data collection and analysis, frequency and matrix data were extracted through social matrix program Textom. In addition, the degree of the relationship was quantified by analyzing the connection structure and the centrality of the degree of connection between the words. Although the marathon is a personal movement, young people share a common denominator of "running" and form a new cultural group called "running crew" with other young people. Through this, it was found that a marathon competition culture was formed as a festival venue where people could train together, participate together, and escape from the image of a marathon run alone and fight with themselves.

KNU Korean Sentiment Lexicon: Bi-LSTM-based Method for Building a Korean Sentiment Lexicon (Bi-LSTM 기반의 한국어 감성사전 구축 방안)

  • Park, Sang-Min;Na, Chul-Won;Choi, Min-Seong;Lee, Da-Hee;On, Byung-Won
    • Journal of Intelligence and Information Systems
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    • v.24 no.4
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    • pp.219-240
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    • 2018
  • Sentiment analysis, which is one of the text mining techniques, is a method for extracting subjective content embedded in text documents. Recently, the sentiment analysis methods have been widely used in many fields. As good examples, data-driven surveys are based on analyzing the subjectivity of text data posted by users and market researches are conducted by analyzing users' review posts to quantify users' reputation on a target product. The basic method of sentiment analysis is to use sentiment dictionary (or lexicon), a list of sentiment vocabularies with positive, neutral, or negative semantics. In general, the meaning of many sentiment words is likely to be different across domains. For example, a sentiment word, 'sad' indicates negative meaning in many fields but a movie. In order to perform accurate sentiment analysis, we need to build the sentiment dictionary for a given domain. However, such a method of building the sentiment lexicon is time-consuming and various sentiment vocabularies are not included without the use of general-purpose sentiment lexicon. In order to address this problem, several studies have been carried out to construct the sentiment lexicon suitable for a specific domain based on 'OPEN HANGUL' and 'SentiWordNet', which are general-purpose sentiment lexicons. However, OPEN HANGUL is no longer being serviced and SentiWordNet does not work well because of language difference in the process of converting Korean word into English word. There are restrictions on the use of such general-purpose sentiment lexicons as seed data for building the sentiment lexicon for a specific domain. In this article, we construct 'KNU Korean Sentiment Lexicon (KNU-KSL)', a new general-purpose Korean sentiment dictionary that is more advanced than existing general-purpose lexicons. The proposed dictionary, which is a list of domain-independent sentiment words such as 'thank you', 'worthy', and 'impressed', is built to quickly construct the sentiment dictionary for a target domain. Especially, it constructs sentiment vocabularies by analyzing the glosses contained in Standard Korean Language Dictionary (SKLD) by the following procedures: First, we propose a sentiment classification model based on Bidirectional Long Short-Term Memory (Bi-LSTM). Second, the proposed deep learning model automatically classifies each of glosses to either positive or negative meaning. Third, positive words and phrases are extracted from the glosses classified as positive meaning, while negative words and phrases are extracted from the glosses classified as negative meaning. Our experimental results show that the average accuracy of the proposed sentiment classification model is up to 89.45%. In addition, the sentiment dictionary is more extended using various external sources including SentiWordNet, SenticNet, Emotional Verbs, and Sentiment Lexicon 0603. Furthermore, we add sentiment information about frequently used coined words and emoticons that are used mainly on the Web. The KNU-KSL contains a total of 14,843 sentiment vocabularies, each of which is one of 1-grams, 2-grams, phrases, and sentence patterns. Unlike existing sentiment dictionaries, it is composed of words that are not affected by particular domains. The recent trend on sentiment analysis is to use deep learning technique without sentiment dictionaries. The importance of developing sentiment dictionaries is declined gradually. However, one of recent studies shows that the words in the sentiment dictionary can be used as features of deep learning models, resulting in the sentiment analysis performed with higher accuracy (Teng, Z., 2016). This result indicates that the sentiment dictionary is used not only for sentiment analysis but also as features of deep learning models for improving accuracy. The proposed dictionary can be used as a basic data for constructing the sentiment lexicon of a particular domain and as features of deep learning models. It is also useful to automatically and quickly build large training sets for deep learning models.