• Journal of Digital Convergence
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• v.16 no.12
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• pp.197-206
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• 2018

The harmful effects of online malicious comments are continuously increasing. Many previous studies have confirmed that neutralization of malicious comments is a key predictor. Neutralization is theoretically composed of seven multidimensional concepts, and the significance of neutralization factors varies depending on the type of deviant behavior. This study focuses on the fact that the malicious comment researches have considered the neutralization techniques in a single dimension as opposed to demonstrating the multidimensional neutralization techniques in the deviant behavior research. On the other hand, the role of arbitrator in deviant behavior can contribute to restraining deviant behavior, but the research of intervention intention is relatively lacking in malicious comments research. This study, composed of two complementary studies, tried to find out the related factors of malicious comments and intervention intention. As a result of study, This study revealed that malicious commentator uses the neutralization techniques of condemn the condemners and denial of responsibility. In addition, we found that affective empathy has a significant effect on the intervention intention in malicious comments.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.2
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• pp.25-34
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• 2022

With the development of online services, the ripple effect of negative comments is increasing, and the damage of cyber violence is rising. Various methods such as filtering based on forbidden words and reporting systems prevent this, but it is challenging to eradicate negative comments. Therefore, this study aimed to increase the accuracy of the classification of negative comments using deep learning and blur the parts corresponding to profanity. Two different conditional training helped decide the number of deep learning layers and filters. The accuracy of 88% confirmed with 90% of the dataset for training and 10% for tests. In addition, Grad-CAM enabled us to find and blur the location of swear words in negative comments. Although the accuracy of classifying comments based on simple forbidden words was 56%, it was found that blurring negative comments through the deep learning model was more effective.

• Journal of Information Technology Applications and Management
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• v.21 no.4
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• pp.157-171
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• 2014

As electronic word of mouth plays an important role in purchase behavior among consumers, the number of studies on the impact of electronic word of mouth is rapidly increasing. Nevertheless, it is difficult to discover comparative studies on the mass media which had a great impact on consumer's purchase behavior before the impact of electronic word of mouth becomes greater versus the social media where electronic words of mouth are created and distributed. It is considered that it seems to be necessary to find an appropriate mutual supplement point between the media designed for a successful marketing by comparing and analyzing the existing mass media versus the social media, major media for electronic word of mouth. Therefore, this study aims to compare and analyze the impact of comments on movie revenue in the representative forms of mass media such as online news and social media blogs. In particular, this study also considers an appropriate media for promoting movies by period by comparing and analyzing the two media before and after film release. For analysis, this study collects the information on the number of comments on online news and blogs in 70 Korean movies released in 2011 and 2012 from five weeks before film release to eight weeks after film release on a daily basis via Naver. This study also collects the information on the movie revenue using the statistical data of movie industry from Korean Film Commission. As a result of empirical data analysis, it is found that the two media showed no difference in movie revenue before film release, but after film release, the impact of blogs was more significant than that of online news.

• Journal of the Korea Convergence Society
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• v.11 no.6
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• pp.23-28
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• 2020

A comment system is essential for communication on the Internet. However, there are also malicious comments such as inappropriate expression of others by exploiting anonymity online. In order to protect users from malicious comments, classification of malicious / normal comments is necessary, and this can be implemented as text classification. Text classification is one of the important topics in natural language processing, and studies using pre-trained models such as BERT and graph structures such as GCN and GAT have been actively conducted. In this study, we implemented a comment classification system using BERT, GCN, and GAT for actual published comments and compared the performance. In this study, the system using the graph-based model showed higher performance than the BERT.

• Journal of Contemporary Eastern Asia
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• v.20 no.1
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• pp.1-23
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• 2021

With regard to the recent developments in public diplomacy, the increasing fusion of strategic communication appears necessary. China engages in public diplomacy with a strategic purpose to shape its national image abroad. Hosting diplomatic advocacy event is regarded as an instrument with expectations to present reliable and responsible image and promote international collaborations. The present research focuses on the Belt and Road Forum (BRF) in May 2017 with the objective to analyze its outcomes and influence on the international news agenda, news frames, and foreign citizens' comments online. The quantitative content analyses are used to compare the media reports (N=364) and Facebook users' comments on the selected news (N=957) between the US and Pakistan. Results reveal that Pakistani media provided more diverse frames and attributed more positive evaluations to the BRF than the US media. However, Facebook comments expressed more unfavorable opinions toward the BRF and China's image with rare differences between two countries. In conclusion, the BRF has served as an eye-catching advocacy of Chinese foreign policy, as it influenced the news agenda in two selected countries. However, news frames vary due to the differences in media system and the involvement in the BRF. China's public diplomacy practices follow a traditional top-down communication which needs meticulous subdivision of target stakeholders, delicate messaging strategies, and integrated tactics.

• Informatization Policy
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• v.28 no.4
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• pp.19-35
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• 2021

The purpose of this research is to investigate the attributes of the online world and to analyze their influence on democracy. The research focuses on the mayoral by-elections that were held in Seoul and Busan, South Korea, on April 4, 2021. The study demonstrates the characteristics of online spaces and the polarization of the online public through news articles and user comments from the Internet. The research includes topic modeling to measure the diversity of media reports, sentiment analysis to measure online public opinion, and interrupted time series analysis to understand how a particular event influences online attitudes. A combination of these methods is used to attempt to estimate the strength of political polarity in the online environment. The study shows diverse media reports by election region and candidate, where the online public repeatedly reveals high negative and low positive attitudes towards each candidate. Moreover, political polarity can differ based on the level of interest in an election. Although voters pay less attention to a by-election than a presidential election, there is a solid political polarity in the online world. Hence, the research recommends preparing measures to alleviate the polarization as politics requires significant online participation.

• Journal of Korea Game Society
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• v.18 no.5
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• pp.83-92
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• 2018

Many studies in deep learning show results as good as human's decision in various fields. And importance of activation of online-community and SNS grows up in game industry. Even it decides whether a game can be successful or not. The purpose of this study is to construct a system which can read texts and create comments according to schedule in online-community and SNS using deep learning. Using recurrent neural network, we constructed models generating a comment and a schedule of writing comments, and made program choosing a news title and uploading the comment at twitter in calculated time automatically. This study can be applied to activating an online game community, a Q&A service, etc.

• Fashion & Textile Research Journal
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• v.25 no.4
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• pp.449-459
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• 2023

This study focuses on online communities and the ritual conversations of users when participating in sharing activities. The study aims to understand the social and psychological phenomena that occur between users within the context of Erving Goffman's impression management theory. Case studies and a content analysis were conducted by collecting posts and comments related to fashion products in the sharing activities category on Naver Cafe "Family Sale." On the one hand, the study identified various disposition motives among givers, including a desire for recognition, self-expression, activation of the community, emotional sympathy, goodwill, play, and simple disposition. On the other hand, receivers' purchase motives included the need for a product, reciprocation based on a sense of belonging, play, gift-giving, and simple response. Analyzing the posts of givers and the comments of receivers of fashion products using impression management strategies and dramaturgical analysis, the study interpreted users' impression management and revealed propensities in fashion consumption: fashionability, conspicuousness, value orientation, and economic feasibility. Through ritual conversations, users managed to attain emotional stability on an individual level, while they reinforced collective bonds on a social level. They fulfilled their roles with their own narratives to achieve personal and collective goals in a non-face-to-face situations and non-monetary transactions. This study is significant in that it examines normative communication in an online community and user relationships to understand a recent phenomenon in the fashion industry.

• Journal of Contemporary Eastern Asia
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• v.16 no.1
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• pp.1-21
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• 2017

The Jakarta Provincial Government utilizes the YouTube channel to interact with citizens and enhance transparency. The purpose of this study is to explore online perceptions of local government image perceived by online audiences through the YouTube platform. The concepts of organizational image and credibility in the political image are adapted to analyze online public perceptions on the Jakarta Provincial Government image. Using the video summarization approach on Three hundred and forty-six official YouTube videos, which were uploaded from 1 March 2016 to 31 May 2016, and content analysis of Eight thousand two hundred and thirty-seven comments, this study shows both political and bureaucratic image emerge concurrently in the Jakarta Provincial Government case. The typology model is proposed to describe and explain the four image variations that occurred in the case study. Practical recommendations are suggested to manage YouTube channel as one of the social media used in the local government context.

• The Journal of the Korea Contents Association
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• v.18 no.5
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• pp.367-375
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• 2018

The study aims to determine which groups leave longer(more active) online reviews(comments) on the film by separating groups, one that satisfied with the movie while the other group dissatisfied with the movie. The data used were rating scores and reviews(comments) from Naver Movie API, and break-even point data provided by Korea Film Commission. We analyzed the relationship between movie rating and review length, before and after movie opening, the characteristics of review length according to the box office, and whether the movie rating affects the review length.