• Korean Journal of Child Studies
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• v.38 no.1
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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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• v.9 no.1
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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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• v.9 no.3
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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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• v.14 no.4
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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.

• Smart Media Journal
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• v.1 no.4
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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.

• Journal of Fashion Business
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• v.27 no.5
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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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.337-340
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• 2000

Using the Information Retrieval systems on the Internet, the demand of exact and specific information has also been popularized. To offer exact information, there k3 been generalized demand of searching from the keyword of the shortened text and also of the full-text. This study is to suggest a scheme for full-text searches. It is to compare the existing scheme of information search and full-text information search with interMedia text. We suggest search methods for the full-text.

• Smart Media Journal
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• v.4 no.3
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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.

• The Journal of the Korea Contents Association
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• v.11 no.6
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• pp.385-396
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• 2011

Internet web pages can be classified by three major types such as texts only, images with texts and videos with texts. The purpose of this paper is to analyze how customers recognize and respond perspective of perceived risk and media richness with regard to design patterns of internet web pages. Additionally, we will examine the extent to which aforementioned factors affect customer satisfaction. Analyses with perceived risks revealed that customers feel less personal risks including performance, psychology and time/convenience when used web pages of text-images and text-videos, compared to text only based web pages. However, customers feel that web pages consisting of image-text or video-text have higher points in terms of symbolism and social presence in media richness, compared to text only based web pages. Finally, we showed that personal risk and text-based Web page negatively affect but symbolism and social presence positively impact on customer satisfaction. Therefore, this study suggests a clue that why video-based Web content did not grow different from many people's expectation.

• Smart Media Journal
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• v.6 no.4
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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.