• Journal of Digital Convergence
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• v.20 no.5
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• pp.733-739
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• 2022

The study investigated the users' functional requirement, degree of acceptance and preference of game broadcast real-time review .Secondly it comparatively analyzed the types and locations of game broadcast real-time review through eye tracking tech. The results show that users have high functional requirements and high acceptance for game broadcast real-time review but their preference has no significant correlation with the feature. Among the types of game broadcast real-time review the type with translucent text bubble took the highest visual attention. The above shows that the users' visual behavior has the tendency of special style. The visual attention analysis results of different types and locations of game broadcast real-time review in the study can play a guiding role in the interface design of real-time review feature in the future.

• 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.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.27 no.4
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• pp.63-84
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• 2016

This study aimed to investigate the extent that users participated in Facebook of U.S. state archives and the types of user responses to posts on the Facebook. For the purpose, data created between August 1st and September 30th in 2016 were collected from Facebook continuously operated by 27 state archives. The extent of user participation was measured based on the number of user comments, the number of unique commenters, and the average number of comments per post. According to the measures, top 10 Facebook of state archives were selected. Out of these, Facebook of Ohio (1st), Florida (5th) and Arkansas (10th) state archives were chosen to collect 687 user comments and 132 posts. The analysis showed that comments regarding users' emotional opinion and judgement, adding explanations to a post, and sharing personal stories occupied a large portion. Interactions among users or between a user and an archivist were also identified. With regard to posts, those for sharing information/knowledge of records held in archives were identified as a high percentage. The study suggested that archives should collect and present historical information and related records connected to users' lives, examine methods for effective communication with users via social media and facilitate publicity and outreach services of archives based on shaping and maintaining online user community through social media.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.3
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• pp.103-110
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• 2023

With the spread of the Internet, anonymous communities emerged along with the activation of communities for communication between people, and many users are doing harm to others, such as posting aggressive posts and leaving comments using anonymity. In the past, administrators directly checked posts and comments, then deleted and blocked them, but as the number of community users increased, they reached a level that managers could not continue to monitor. Initially, word filtering techniques were used to prevent malicious writing from being posted in a form that could not post or comment if a specific word was included, but they avoided filtering in a bypassed form, such as using similar words. As a way to solve this problem, deep learning was used to monitor posts posted by users in real-time, but recently, the community uses words that can only be understood by the community or from a human perspective, not from a general Korean word. There are various types and forms of characters, making it difficult to learn everything in the artificial intelligence model. Therefore, in this paper, we proposes a preprocessing technique in which each character of a sentence is imaged using a CNN model that learns the consonants, vowel and spacing images of Korean word and converts characters that can only be understood from a human perspective into characters predicted by the CNN model. As a result of the experiment, it was confirmed that the performance of the LSTM, BiLSTM and CNN-BiLSTM models increased by 3.2%, 3.3%, and 4.88%, respectively, through the proposed preprocessing technique.

• Journal of Industrial Convergence
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• v.20 no.12
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• pp.135-143
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• 2022

This paper aims to grasp what propensity users have in their ideology from the comments in the Web Portal News and the Press Website News. Through these analytical results, the political propensities of not only the Web Portal News and the Press Website News but also the voters who use these news media could be grasped. The collection of data necessary for this study has been made from the comments of 174 news stories for about 90 days before the election day. For the analysis, T-test has been used in order to compare Naver News with Daum News, the Minjoo Party of Korea with the People Power Party, and the Press Web Site News with Naver News. As a result of the analysis, the comments of Naver News took the higher percentage in the positive writings about the candidates of the conservative party. but, in contrast, those of Daum News in that percentage were higher about the ones of the progressive party. Accordingly, it can be found that Naver News is mainly used by users with the politically conservative propensity, while Daum News is mostly used by those with progressive one.

• Journal of Digital Convergence
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• v.19 no.7
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• pp.113-127
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• 2021

This study classifies review attributes into ratings, number of comments and image information in online shopping mall to verify their impact on brand attitude and purchase decision and e-WOM intention. Use SPSS 23.0 for frequency analysis, factor analysis and regression analysis. The results showed that review attributes have a positive effect on brand attitudes, purchase decision and e-WOM intention, but the number of comments has not affect on purchase decision. Brand attitude has a positive effect on purchase decision and e-WOM intention. Brand attitude has media effect in the relationship between ratings, image information and purchase decision, and in the relationship between review attributes and e-WOM intention. As these results, consumers don't always like to have a lot of comments. and should allow to focus on high ratings and photo reviews as much as possible when writing reviews.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.199-219
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• 2018

With the everyday use of the Internet and the spread of various smart devices, users have been able to communicate in real time and the existing communication style has changed. Due to the change of the information subject by the Internet, data became more massive and caused the very large information called big data. These Big Data are seen as a new opportunity to understand social issues. In particular, text mining explores patterns using unstructured text data to find meaningful information. Since text data exists in various places such as newspaper, book, and web, the amount of data is very diverse and large, so it is suitable for understanding social reality. In recent years, there has been an increasing number of attempts to analyze texts from web such as SNS and blogs where the public can communicate freely. It is recognized as a useful method to grasp public opinion immediately so it can be used for political, social and cultural issue research. Text mining has received much attention in order to investigate the public's reputation for candidates, and to predict the voting rate instead of the polling. This is because many people question the credibility of the survey. Also, People tend to refuse or reveal their real intention when they are asked to respond to the poll. This study collected comments from the largest Internet portal site in Korea and conducted research on the 19th Korean presidential election in 2017. We collected 226,447 comments from April 29, 2017 to May 7, 2017, which includes the prohibition period of public opinion polls just prior to the presidential election day. We analyzed frequencies, associative emotional words, topic emotions, and candidate voting rates. By frequency analysis, we identified the words that are the most important issues per day. Particularly, according to the result of the presidential debate, it was seen that the candidate who became an issue was located at the top of the frequency analysis. By the analysis of associative emotional words, we were able to identify issues most relevant to each candidate. The topic emotion analysis was used to identify each candidate's topic and to express the emotions of the public on the topics. Finally, we estimated the voting rate by combining the volume of comments and sentiment score. By doing above, we explored the issues for each candidate and predicted the voting rate. The analysis showed that news comments is an effective tool for tracking the issue of presidential candidates and for predicting the voting rate. Particularly, this study showed issues per day and quantitative index for sentiment. Also it predicted voting rate for each candidate and precisely matched the ranking of the top five candidates. Each candidate will be able to objectively grasp public opinion and reflect it to the election strategy. Candidates can use positive issues more actively on election strategies, and try to correct negative issues. Particularly, candidates should be aware that they can get severe damage to their reputation if they face a moral problem. Voters can objectively look at issues and public opinion about each candidate and make more informed decisions when voting. If they refer to the results of this study before voting, they will be able to see the opinions of the public from the Big Data, and vote for a candidate with a more objective perspective. If the candidates have a campaign with reference to Big Data Analysis, the public will be more active on the web, recognizing that their wants are being reflected. The way of expressing their political views can be done in various web places. This can contribute to the act of political participation by the people.

• Korean Journal of Culture and Social Issue
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• v.26 no.3
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• pp.283-301
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• 2020

In Korean society, words related to misogyny are being created and spread out in the Internet communities and the Internet news posts comments. This study was conducted to investigate if exposure to misogynistic words affects misogynistic attitudes toward women. Study 1 examined the relationship between exposure of misogynistic words (the number of misogynistic words known and the level of Internet comments viewed) and explicit misogynistic attitudes. As a result, the greater the exposure of misogynistic words, the less explicit misogynistic attitudes were found among men. The result can be explained as a desensitization of stimuli caused by repetitive exposure to media. In Study 2, experiments were conducted to manipulate the exposure of misogynistic words and to identify the relationship between implicit misogynistic attitudes through implicit association tests. Results of analysis show that implicit misogyny attitude is stronger as male participants are exposed to misogynistic words. The finding of this study suggests that explicit and implicit attitudes toward misogyny can diverge. It also implies that the exposure to misogynistic words can affect men's and women's attitudes in a different manner.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.11
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• pp.521-526
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• 2016

As on-line informal text data have massive in its volume and have unstructured characteristics in nature, there are limitations in applying traditional relational data model technologies for data storage and data analysis jobs. Moreover, using dynamically generating massive social data, social user's real-time reaction analysis tasks is hard to accomplish. In the paper, to capture easily the semantics of massive and informal on-line documents with unsupervised learning mechanism, we design and implement automatic topic extraction systems according to the mass of the words that consists a document. The input data set to the proposed system are generated first, using N-gram algorithm to build multiple words to capture the meaning of the sentences precisely, and Hadoop and Spark (In-memory distributed computing framework) are adopted to run topic model. In the experiment phases, TB level input data are processed for data preprocessing and proposed topic extraction steps are applied. We conclude that the proposed system shows good performance in extracting meaningful topics in time as the intermediate results come from main memories directly instead of an HDD reading.

• The Journal of Society for e-Business Studies
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• v.23 no.4
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• pp.127-136
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• 2018

With the increased value in digital contents, the influence of social media has increased exponentially over the past years. Focused around those in their teens and twenties, social media has spread its influence to people regardless of one's age or gender. This increased attention is reflected by the public's interest in pets, especially those dealt with in the personal media sector. This paper will focus on the two most popular Korean cat youtube channels called "CreamHeroes" and "SuriNoel." By analyzing the top thirty most viewed videos on each channel, real time streaming, goods based on the cats starring on the channel, and comments left by the channels' subscribers, it can be concluded that people watching videos categorized as "Viewnimal" derive surrogate pleasure from their viewings. The following creates the potential for increased conversation regarding the subject of shelter animals and animal abuse.