• 아동학회지
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• 제38권1호
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• pp.77-93
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• 2017

Objective: The purpose of this study was to develop a text-based media literacy program and to examine its effects on young children's understanding and expression of media text. Methods: The participants were 54 5-year-old kindergarteners assigned to an experimental or a control group, with 27 children per group. The text-based media literacy program was based on the ADDIE model and was administered to the experimental group for 8 weeks. The pre- and post-test instruments measured media text understanding and expression ability and were patterned after those used by British Film Institute (2003) and other major studies. Results: The experimental group showed higher levels of media text understanding and expression than the control group. Conclusion: The results are discussed with respect to their implications for educational practice and future research.

• Asian Journal for Public Opinion Research
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• 제9권1호
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• pp.25-47
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• 2021

This study analyzes 419 fake news items published in India, a fake-news-prone country, to identify the major themes, content types, and sources of social media fake news. The results show that fake news shared on social media has six major themes: health, religion, politics, crime, entertainment, and miscellaneous; eight types of content: text, photo, audio, and video, text & photo, text & video, photo & video, and text & photo & video; and two main sources: online sources and the mainstream media. Health-related fake news is more common only during a health crisis, whereas fake news related to religion and politics seems more prevalent, emerging from online media. Text & photo and text & video have three-fourths of the total share of fake news, and most of them are from online media: online media is the main source of fake news on social media as well. On the other hand, mainstream media mostly produces political fake news. This study, presenting some novel findings that may help researchers to understand and policymakers to control fake news on social media, invites more academic investigations of religious and political fake news in India. Two important limitations of this study are related to the data source and data collection period, which may have an impact on the results.

• Asia pacific journal of information systems
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• 제9권3호
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• pp.1-23
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• 1999

The objective of this study is to examine the media richness theory and the social information processing model by analyzing the effect of media experience on media perception and communication process. To accomplish this objective, a laboratory experiment was conducted. The independent variable was text medium experience and a face-to-face medium was added as a control group. The dependent variables were medium perception and communication process. Medium perception includes perceived richness, medium feeling, task satisfaction, and communication satisfaction. Communication processes were also analyzed to compare each treatment group. The results can be summarized into two facts. First, face-to-face group showed higher perceived richness than text medium group. And experienced text medium group perceived their text medium richer than inexperienced text medium group. Second, experienced text medium groups showed more interactions between subjects than inexperienced text medium group. Experienced text medium group also showed more agreements and meta-communication which could be found in face-to-face group. The result of this study supported media richness theory by finding that face-to-face medium was perceived richer than text medium, And the results also proved social information processing model by comparing experienced text medium group and inexperienced text medium group. The text medium, although thought to be the leanest one, could be perceived richer if users had lots of experience on it.

• International Journal of Contents
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• 제14권4호
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• pp.86-91
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• 2018

Text has evolved along with the history of art as a means of communicating human intentions and emotions. In addition, text visualization artworks have been combined with the social form and contents of new media to produce social messages and related meanings. Recently, in text visualization artworks combined with digital media, communication forms with viewers are changing instantly and interactively, and viewers are actively participating in creating artworks by direct engagement. Interactive text visualization with additional viewer's interaction, generates external dynamics from text shapes and internal dynamics from embedded meanings of text. The purpose of this study is to propose a visual dynamics model to express the dynamics of text and to implement a text visualization system based on the model. It uses the deconstruction of the imaged text to create an interactive text visualization system that reacts to the gestures of the viewer in real time. Visual Transformation synchronized with the intentions of the viewer prevent the text from remaining in the interpretation of language symbols and extend the various meanings of the text. The visualized text in various forms shows visual dynamics that interpret the meaning according to the cultural background of the viewer.

• 스마트미디어저널
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• 제1권4호
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• pp.27-34
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• 2012

In this paper, a novel text binarization is presented that can deal with some complex conditions, such as shadows, non-uniform illumination due to highlight or object projection, and messy backgrounds. To locate the target text region, a focus line is assumed to pass through a text region. Next, connected component analysis and stroke width estimation based on location information of the focus line is used to locate the bounding box of the text region, and each box of connected components. A series of classifications are applied to identify whether each CC(Connected component) is text or non-text. Also, a modified K-means clustering method based on an HCL color space is applied to reduce the color dimension. A text binarization procedure based on location of text component and seed color pixel is then used to generate the final result.

• 패션비즈니스
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• 제27권5호
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• pp.78-92
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• 2023

Fashion trends are actively disseminated through social media, which influences both their propagation and consumption. This study explored how users perceive subversive basic fashion in social media videos, by examining the associated concepts and characteristics. In addition, the factors contributing to the style's social media dissemination were identified and its distinctive features were analyzed. Through text mining analysis, 80 keywords were selected for semantic network and CONCOR analysis. TF-IDF and N-gram results indicate that subversive basic fashion involves transformative design techniques such as cutting or layering garments, emphasizing the body with thin fabrics, and creating bold visual effects. Topic modeling suggests that this fashion forms a subculture that resists mainstream norms, seeking individuality by creatively transforming the existing garments. CONCOR analysis categorized the style into six groups: forward-thinking unconventional fashion, bold and unique style, creative reworking, item utilization and combination, pursuit of easy and convenient fashion, and contemporary sensibility. Consumer actions, linked to social media, were shown to involve easily transforming and pursuing personalized styles. Furthermore, creating new styles through the existing clothing is seen as an economic and creative activity that fosters network formation and interaction. This study is significant as it addresses language expression limitations and subjectivity issues in fashion image analysis, revealing factors contributing to content reproduction through user-perceived design concepts and social media-conveyed fashion characteristics.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2000년도 추계종합학술대회
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• pp.337-340
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• 2000

인터넷을 이용한 정보검색이 일반화되면서, 보다 정확하고 꼭 필요한 정보의 요구가 일반화되었다. 정확한 정보의 제공을 위해, 된 정보에 대한 중심어(keyword) 검색뿐만 아니라 전문(Full-Text)에 대한 검색 요구가 일반화되었다. 본 연구에서는 전문 검색을 위한 설계 방안을 제안한다. 기존에 제안된 전문 검색 방안과 오라클에서 제공하는 interMedia Text를 이용한 전문 검색 방안을 비교한다. 이를 기반으로 정보 검색 시스템에서 구현 방안을 제시한다.

• 스마트미디어저널
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• 제4권3호
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• pp.44-49
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• 2015

Text line segmentation is a preprocessing step in OCR, which can significantly influence the accuracy of document analysis applications. This paper proposes a novel methodology for the text line segmentation of handwritten documents. First, the average width of the connected components is used to form a 1-D Gaussian kernel and a smoothing operation is then applied to the input binary image. The adaptive binarization of the smoothed image forms the final text lines. In this work, the segmentation method involves two stages: firstly, the large connected components are labelled as a unique text line using text line area mapping. Secondly, the final refinement of the segmentation is performed using the Euclidean distance between the text line and small connected components. The group of uniquely labelled text candidates achieves promising segmentation results. The proposed approach works well on Korean and English language handwritten documents captured using a camera.

• 한국콘텐츠학회논문지
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• 제11권6호
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• pp.385-396
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• 2011

인터넷의 웹페이지는 다양한 형태로 존재하지만, 크게 텍스트 중심의 웹페이지, 텍스트와 이미지로 구성된 웹페이지, 그리고 텍스트와 동영상으로 구성된 웹페이지로 구분할 수 있다. 본 연구에서는 콘텐츠 제작방식에 따라서 변하는 소비자들의 지각된 위험 수준과 미디어 풍부성이 미치는 영향을 분석하며, 이들 요인이 고객만족에 미치는 영향을 분석한다. 분석결과, 텍스트 형식의 웹페이지가 텍스트와 이미지 혹은 동영상으로 구성된 웹페이지에 비해서 지각된 위험 중 성능위험, 심리적 위험, 시간 위험 등으로 구성된 개인적 위험을 더 크게 느끼는 것으로 나타났다. 또한, 미디어 풍부성 측면에서는 텍스트와 이미지 혹은 동영상으로 구성된 웹페이지가 텍스트 위주의 웹페이지에 비해서 상징성 및 사회적 실재감이 높은 것으로 조사되었다. 그리고 개인적 위험 및 텍스트 형식의 웹페이지는 고객 만족에 음의 영향을 미치며, 상징성 및 사회적 실재감은 양의 효과를 가진다. 본 연구는 지각된 위험과 미디어 풍부성의 개념을 콘텐츠 제작방식과 연결시킴으로써 기대와는 달리 동영상 콘텐츠가 폭발적으로 성장하지 못한 점에 대해서 규명한데 의의를 둔다.

• 스마트미디어저널
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• 제6권4호
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• pp.32-40
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• 2017

In this paper, a robust text detection method based on edge enhanced contrasting extremal region (CER) is proposed using stroke width transform (SWT) and tensor voting. First, the edge enhanced CER extracts a number of covariant regions, which is a stable connected component from input images. Next, SWT is created by the distance map, which is used to eliminate non-text regions. Then, these candidate text regions are verified based on tensor voting, which uses the input center point in the previous step to compute curve salience values. Finally, the connected component grouping is applied to a cluster closed to characters. The proposed method is evaluated with the ICDAR2003 and ICDAR2013 text detection competition datasets and the experiment results show high accuracy compared to previous methods.