• Title/Summary/Keyword: 댓글 분석

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Children's Writing on the Screen : Focused on the PAIR Strategies for the Audiences and the Feature of Communication Reflected in Comments ('스크린 위의 글쓰기' 과정에 나타난 아동의 예상독자 고려 전략 및 댓글에 반영된 의사소통 특성)

  • Hyun, Eunja;Kim, Hyeonkyeong;You, Jinkyoung
    • The Journal of the Korea Contents Association
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    • v.14 no.12
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    • pp.1100-1116
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    • 2014
  • The purpose of this study is to investigate how children use the PAIR strategy for their audiences in the writing on the screen and how the comments play a role to communicate between an author and audiences. In order to perform this research, 7 elementary school students(4th-6th grade) participated in the literary education program designed to promote to write on the screen. As a result, 42 body texts(635 sentences) and 424 comments of children's writing on the screen were collected and analyzed according to the PAIR strategies and performance behaviour. The findings are as follows: first, 'attracting' is used the most among PAIR strategies and second, the most frequent performance behavior of comment is 'expression'. These findings indicate that children's writing strategy considering audiences tends to be emotionally appealing and performance behavior of comment is likely to focus on affective expression.

User Characterization from Replying Comment Structures in Online Discussion (온라인 토론의 댓글 응답 구조를 이용한 사용자 특성 분석)

  • Kim, Sung-Hwan;Tak, Haesung;Cho, Hwan-Gue
    • The Journal of the Korea Contents Association
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    • v.18 no.11
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    • pp.135-145
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    • 2018
  • In online communities, users use comments to exchange their opinions and feelings on various subjects. Communication based on comments is quick and convenient, but sometimes this light-weight characteristic makes users use impolite and aggressive words, which leads to an online conflict. Therefore, it is important to analyze and classify users according to their characteristics in order to predict and take action for this kind of troubles. In this paper, we present several quantitative measures for describing the structures of comments trees based on the assumption that the user characteristics be observed as a form of some structural feature in comment trees of articles in which they posted comments. We examine the distribution of the proposed measures over article posters and commenters, and in addition, we show the effectiveness of the presented structural features by conducting experiments to classify users who have received warnings of the administrator from benign users.

A Survey on Aware of University Students for Internet Ethics and Malicious Replay (인터넷 윤리와 악성댓글에 대한 대학생들의 인식에 관한 조사)

  • Park, Hee-Sook
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.16 no.9
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    • pp.2043-2049
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    • 2012
  • Because of the growth of internet and development of smart phone technology, peoples are able to connect the internet easily and convenient at anytime, and anywhere. The other hand, that take place many serious social side-effect and one of a typical cases is the problem of malicious replay in weaken of netizen's internet ethics. The problem of malicious replay is increasing more and more the seriousness of the problem and the victims are suffering from much the pains of the trauma by a malicious replay. Therefore, in this paper, we investigate and analyze actual on aware of internet ethics and malicious replay for university students and then we propose the improvement of the problem.

Analysis of Opinion Social Data on the SNS (Social Network Service) by Analyzing of Collective Damage Reply (악성 집단 댓글 분석에 의한 SNS 여론 소셜데이터 분석)

  • Hwang, Yun Chan;Koh, Chan
    • Journal of Digital Convergence
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    • v.11 no.5
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    • pp.41-51
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    • 2013
  • A lots of social data are distributed, utilized and opened through the social media. They have characterized effectiveness and pleasure of information to the media by social data but it is ignored about excessive exposure of information and damage from collective reply of personal attack type. In this paper, we study about analysis of opinion social data on the SNS (Social Network Service) by analyzing of collective damage reply. It is analysed by diverse measurement method for distribution and disuse of the amount of Buzz data that is analysed data from structured social network.

Study on Effective Extraction of New Coined Vocabulary from Political Domain Article and News Comment (정치 도메인에서 신조어휘의 효과적인 추출 및 의미 분석에 대한 연구)

  • Lee, Jihyun;Kim, Jaehong;Cho, Yesung;Lee, Mingu;Choi, Hyebong
    • The Journal of the Convergence on Culture Technology
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    • v.7 no.2
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    • pp.149-156
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    • 2021
  • Text mining is one of the useful tools to discover public opinion and perception regarding political issues from big data. It is very common that users of social media express their opinion with newly-coined words such as slang and emoji. However, those new words are not effectively captured by traditional text mining methods that process text data using a language dictionary. In this study, we propose effective methods to extract newly-coined words that connote the political stance and opinion of users. With various text mining techniques, I attempt to discover the context and the political meaning of the new words.

Abusive Detection Using Bidirectional Long Short-Term Memory Networks (양방향 장단기 메모리 신경망을 이용한 욕설 검출)

  • Na, In-Seop;Lee, Sin-Woo;Lee, Jae-Hak;Koh, Jin-Gwang
    • The Journal of Bigdata
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    • v.4 no.2
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    • pp.35-45
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    • 2019
  • Recently, the damage with social cost of malicious comments is increasing. In addition to the news of talent committing suicide through the effects of malicious comments. The damage to malicious comments including abusive language and slang is increasing and spreading in various type and forms throughout society. In this paper, we propose a technique for detecting abusive language using a bi-directional long short-term memory neural network model. We collected comments on the web through the web crawler and processed the stopwords on unused words such as English Alphabet or special characters. For the stopwords processed comments, the bidirectional long short-term memory neural network model considering the front word and back word of sentences was used to determine and detect abusive language. In order to use the bi-directional long short-term memory neural network, the detected comments were subjected to morphological analysis and vectorization, and each word was labeled with abusive language. Experimental results showed a performance of 88.79% for a total of 9,288 comments screened and collected.

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A Malicious Comments Detection Technique on the Internet using Sentiment Analysis and SVM (감성분석과 SVM을 이용한 인터넷 악성댓글 탐지 기법)

  • Hong, Jinju;Kim, Sehan;Park, Jeawon;Choi, Jaehyun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.20 no.2
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    • pp.260-267
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    • 2016
  • The Internet has brought lots of changes to us sharing information mutually. However, as all social symptom have double-sided character, it has serious social problem. Vicious users have been taking advantage of anonymity on the Internet, stating comments aggressively for defamation, personal attacks, privacy violation and more. Malicious comments on the Internet are creating the biggest problem regarding unlawful acts and insults which occur on the Internet. In order to solve the issues, several studies have been done to efficiently manage the comments. However, there are limitations to recognize modified malicious vocabulary in previous research. So, in this paper, we propose a malicious comments detection technique by improving limitation of previous studies. The experimental result has shown accuracy of 87.8% providing higher accuracy as compared to previous studies done.

A Study on Corporate Reputation and Profitability Focus on Online News and Comments (기업평판과 수익성에 관한 연구 온라인 뉴스와 뉴스댓글을 중심으로)

  • Jin, Zhilong;Han, Eun-Kyoung
    • Journal of Digital Convergence
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    • v.17 no.9
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    • pp.399-406
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    • 2019
  • The purpose of this study is to examine the relationship between corporate reputation and the profitability. In this study, Big Data Analysis was conducted for Hyundai Motor, Shinsegae Department Store, SK Telecom, and Amorepacific to solve research problems. The results of this study show that the effect of each corporate reputation on the profitability is different according to the company. For products such as Hyundai Motor and Amorepacific that are used directly by consumers, the corporate reputation formed by the comments was more influential. In addition, distribution Service company such as Shinsegae Department Store showed more influence by online news. On the other hand, SK Telecom did not have a significant effect on profitability. Based on the results, this study emphasizes the importance of online news and comments on corporate reputation management, and aims to contribute to establishing an efficient reputation management strategy by examining the relationship between corporate reputation and profitability.

Convergence of Korean Traditional Dance and K-Pop Dance : An Analysis of Comments on 2018 MMA BTS 'IDOL' Videos on YouTube (한국 전통춤과 K-pop 댄스의 융합 : 2018 MMA 방탄소년단 'IDOL' 유튜브 댓글 분석)

  • Yoo, Ji-Young;Kim, Mi-Kyung
    • Journal of Korea Entertainment Industry Association
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    • v.13 no.8
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    • pp.189-198
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    • 2019
  • This study aims to make meaning of the reactions of the Korean people through the text mining of comments on videos of the December 2018 MMA performance of intro on YouTube. For this, comments on 15 YouTube videos were collected over the past 10 months. With the collected data, a total of 5,135 comments were analyzed through crawling using the Python and BeautifulSoup programs, data was refined over a total of 3 sessions, and a final total of 5,080 comments were used as analysis material. A mining technique was used for data analysis and the process of refinement, analysis, and visualization was achieved using the Textom program. Research results showed that keyword analysis showed the keywords of 'performance', 'Korea', 'video', 'top', 'cool', 'dance', 'idol', 'legend', 'love', and 'gratitude' in that order and keywords such as 'patriotism' and 'Olympics' also appeared frequently. N-gram analysis showed that comments with contexts such as 'a top performance that will remain a legend among Korean idol performances', and 'an idol performance that displayed the traditional culture of Korea' were in higher ranks. Based on such keyword analysis results, topic modeling was applied and 5 top keywords were extracted from a total of 5 topics. Analysis results of topic contents and distribution showed that topics in the comments of this performance's videos largely consisted of the 3 reactions of 'high praise regarding the stage performance', 'affection towards the fusion and artistic sublimation of Korean traditional dance', and 'gratitude towards the uploading of cool dance videos'

Consumers Perceptions on Sodium Saccharin in Social Media (소셜미디어 분석을 통한 삭카린나트륨 소비자 인식 조사)

  • Lee, Sooyeon;Lee, Wonsung;Moon, Il-Chul;Kwon, Hoonjeong
    • Journal of Food Hygiene and Safety
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    • v.30 no.4
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    • pp.329-342
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    • 2015
  • The purpose of this study was to investigate consumers' perceptions of sodium saccharin in social media. Data was collected from Naver blogs and Naver web communities (Korean representative portal web-site), and media reports including comment sections on a Yonhap news website (Korean largest news agency). The results from Naver blogs and Naver web communities showed that it was primarily mentioned 'sodium saccharin-no added' products, properties of sodium saccharin, and methods of reducing sodium saccharin in food. When media reported the expansion of food categories permitted to use sodium saccharin, search volume for sodium saccharin has increased in both PC and mobile search engines. Also, it was mainly commented about distrust of government, criticism of food product price, and distrust of food companies below the news on the news site. The label of sodium saccharin-no added products in market emphasized "no added-sodium saccharin". These results suggest that consumers are interested in sodium saccharin and especially when media reported the expansion of food categories permitted to use it. Consumers were able to search various information on sodium saccharin except safety or acceptable daily intake through social media. Therefore media or competent authority should report item on sodium saccharin with information including safety or acceptable daily intake based on scientific background and reference or experts' interview for consumers to get reliable information.