• Korea Science and Art Forum
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• v.35
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• pp.281-292
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• 2018

Crowd funding is also called social funding because of SNS that it helps early start-up founder and makers to raise money for idea product production. Recently, the funding platform has recorded high growth rates. As a result, the government in Korea has introduced various support policies for the crowd funding. The purpose of this study is to develop a diagnostic design guideline for product design oriented makers based on the historical situation. The paper writer applied literature survey and expert interview as research methods. The literature survey focused on internet news and previous research studies. The expert interview was conducted for 10 specialist people and divided for the second time. As a result of the text survey, the current guideline was lacking in design and in detail. Researchers have been informed through previous paper that information transfer text and images are important factors for funding success. In the first interview with seven special participants, we made a draft design guideline for social funding with a two-step process and nine themes. We, research and three professional people having a evaluation experience, conducted verification and supplementation for establishing the design guider with a three-step process and eight themes in the next interview. The design guideline for crowd funding, it can be used by money funding manager apart from design makers. Through the results of this paper, researchers are expected to prevent problems and contribute to healthy crowd funding ecosystem development.

• Korean Journal of Culture and Social Issue
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• v.16 no.2
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• pp.179-195
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• 2010

Media reports of suicides has been found to increase suicide cases that were temporally and spacially proximal to the reports, but the psychological mechanisms, social learning, underlying the negative effects was not directly tested. The present study examined the cognitive processes of social learning that media reports of suicides, especially positive contents toward suicides, might change people's perception, memory, and attitudes toward suicides positively and subsequently increase subsequent suicide intentions and behaviors. Through an internet survey, 300 adults reported their perception, memory, and attitudes toward news reports of suicides, and rated whether the suicides were described positively or negatively in the reports. Finally they reported their suicide intentions and behaviors. The results revealed that people tended to remember more the contents of suicide reports suggested to increase copycat suicides. Also, people were found to have an ironic view to suicide reports of media that they acknowledged the dangers of suicides reports and approached the reports with curiosity. More importantly, the perception of the positive reward that suicides might achieved through suicides was related with positive attitudes toward suicides and behavioral intention to suicides. The present findings was discussed in the social learning understanding of copycat suicides and their implications for suicide-prevention strategies.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.179-200
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• 2019

Word-of-mouth (WoM) is defined by consumer activities that share information concerning consumption. WoM activities have long been recognized as important in corporate marketing processes and have received much attention, especially in the marketing field. Recently, according to the development of the Internet, the way in which people exchange information in online news and online communities has been expanded, and WoM is diversified in terms of word of mouth, score, rating, and liking. Social media makes online users easy access to information and online WoM is considered a key source of information. Although various studies on WoM have been preceded by this phenomenon, there is no meta-analysis study that comprehensively analyzes them. This study proposed a method to extract major researches by applying text mining techniques and to grasp the main issues of researches in order to find the trend of WoM research using scholarly big data. To this end, a total of 4389 documents were collected by the keyword 'Word-of-mouth' from 1941 to 2018 in Scopus (www.scopus.com), a citation database, and the data were refined through preprocessing such as English morphological analysis, stopwords removal, and noun extraction. To carry out this study, we adopted main path analysis (MPA) and word co-occurrence network analysis. MPA detects key researches and is used to track the development trajectory of academic field, and presents the research trend from a macro perspective. For this, we constructed a citation network based on the collected data. The node means a document and the link means a citation relation in citation network. We then detected the key-route main path by applying SPC (Search Path Count) weights. As a result, the main path composed of 30 documents extracted from a citation network. The main path was able to confirm the change of the academic area which was developing along with the change of the times reflecting the industrial change such as various industrial groups. The results of MPA revealed that WoM research was distinguished by five periods: (1) establishment of aspects and critical elements of WoM, (2) relationship analysis between WoM variables, (3) beginning of researches of online WoM, (4) relationship analysis between WoM and purchase, and (5) broadening of topics. It was found that changes within the industry was reflected in the results such as online development and social media. Very recent studies showed that the topics and approaches related WoM were being diversified to circumstantial changes. However, the results showed that even though WoM was used in diverse fields, the main stream of the researches of WoM from the start to the end, was related to marketing and figuring out the influential factors that proliferate WoM. By applying word co-occurrence network analysis, the research trend is presented from a microscopic point of view. Word co-occurrence network was constructed to analyze the relationship between keywords and social network analysis (SNA) was utilized. We divided the data into three periods to investigate the periodic changes and trends in discussion of WoM. SNA showed that Period 1 (1941~2008) consisted of clusters regarding relationship, source, and consumers. Period 2 (2009~2013) contained clusters of satisfaction, community, social networks, review, and internet. Clusters of period 3 (2014~2018) involved satisfaction, medium, review, and interview. The periodic changes of clusters showed transition from offline to online WoM. Media of WoM have become an important factor in spreading the words. This study conducted a quantitative meta-analysis based on scholarly big data regarding WoM. The main contribution of this study is that it provides a micro perspective on the research trend of WoM as well as the macro perspective. The limitation of this study is that the citation network constructed in this study is a network based on the direct citation relation of the collected documents for MPA.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.57-77
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• 2013

Social media has become one of the most popular media in web and mobile application. In 2011, social networks and blogs are still the top destination of online users, according to a study from Nielsen Company. In their studies, nearly 4 in 5active users visit social network and blog. Social Networks and Blogs sites rule Americans' Internet time, accounting to 23 percent of time spent online. Facebook is the main social network that the U.S internet users spend time more than the other social network services such as Yahoo, Google, AOL Media Network, Twitter, Linked In and so on. In recent trend, most of the companies promote their products in the Facebook by creating the "Facebook Page" that refers to specific product. The "Like" option allows user to subscribed and received updates their interested on from the page. The film makers which produce a lot of films around the world also take part to market and promote their films by exploiting the advantages of using the "Facebook Page". In addition, a great number of streaming service providers allows users to subscribe their service to watch and enjoy movies and TV program. They can instantly watch movies and TV program over the internet to PCs, Macs and TVs. Netflix alone as the world's leading subscription service have more than 30 million streaming members in the United States, Latin America, the United Kingdom and the Nordics. As the matter of facts, a million of movies and TV program with different of genres are offered to the subscriber. In contrast, users need spend a lot time to find the right movies which are related to their interest genre. Recent years there are many researchers who have been propose a method to improve prediction the rating or preference that would give the most related items such as books, music or movies to the garget user or the group of users that have the same interest in the particular items. One of the most popular methods to build recommendation system is traditional Collaborative Filtering (CF). The method compute the similarity of the target user and other users, which then are cluster in the same interest on items according which items that users have been rated. The method then predicts other items from the same group of users to recommend to a group of users. Moreover, There are many items that need to study for suggesting to users such as books, music, movies, news, videos and so on. However, in this paper we only focus on movie as item to recommend to users. In addition, there are many challenges for CF task. Firstly, the "sparsity problem"; it occurs when user information preference is not enough. The recommendation accuracies result is lower compared to the neighbor who composed with a large amount of ratings. The second problem is "cold-start problem"; it occurs whenever new users or items are added into the system, which each has norating or a few rating. For instance, no personalized predictions can be made for a new user without any ratings on the record. In this research we propose a clustering method according to the users' genre interest extracted from social network service (SNS) and user's movies rating information system to solve the "cold-start problem." Our proposed method will clusters the target user together with the other users by combining the user genre interest and the rating information. It is important to realize a huge amount of interesting and useful user's information from Facebook Graph, we can extract information from the "Facebook Page" which "Like" by them. Moreover, we use the Internet Movie Database(IMDb) as the main dataset. The IMDbis online databases that consist of a large amount of information related to movies, TV programs and including actors. This dataset not only used to provide movie information in our Movie Rating Systems, but also as resources to provide movie genre information which extracted from the "Facebook Page". Formerly, the user must login with their Facebook account to login to the Movie Rating System, at the same time our system will collect the genre interest from the "Facebook Page". We conduct many experiments with other methods to see how our method performs and we also compare to the other methods. First, we compared our proposed method in the case of the normal recommendation to see how our system improves the recommendation result. Then we experiment method in case of cold-start problem. Our experiment show that our method is outperform than the other methods. In these two cases of our experimentation, we see that our proposed method produces better result in case both cases.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.89-105
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• 2014

After emergence of Internet, social media with highly interactive Web 2.0 applications has provided very user friendly means for consumers and companies to communicate with each other. Users have routinely published contents involving their opinions and interests in social media such as blogs, forums, chatting rooms, and discussion boards, and the contents are released real-time in the Internet. For that reason, many researchers and marketers regard social media contents as the source of information for business analytics to develop business insights, and many studies have reported results on mining business intelligence from Social media content. In particular, opinion mining and sentiment analysis, as a technique to extract, classify, understand, and assess the opinions implicit in text contents, are frequently applied into social media content analysis because it emphasizes determining sentiment polarity and extracting authors' opinions. A number of frameworks, methods, techniques and tools have been presented by these researchers. However, we have found some weaknesses from their methods which are often technically complicated and are not sufficiently user-friendly for helping business decisions and planning. In this study, we attempted to formulate a more comprehensive and practical approach to conduct opinion mining with visual deliverables. First, we described the entire cycle of practical opinion mining using Social media content from the initial data gathering stage to the final presentation session. Our proposed approach to opinion mining consists of four phases: collecting, qualifying, analyzing, and visualizing. In the first phase, analysts have to choose target social media. Each target media requires different ways for analysts to gain access. There are open-API, searching tools, DB2DB interface, purchasing contents, and so son. Second phase is pre-processing to generate useful materials for meaningful analysis. If we do not remove garbage data, results of social media analysis will not provide meaningful and useful business insights. To clean social media data, natural language processing techniques should be applied. The next step is the opinion mining phase where the cleansed social media content set is to be analyzed. The qualified data set includes not only user-generated contents but also content identification information such as creation date, author name, user id, content id, hit counts, review or reply, favorite, etc. Depending on the purpose of the analysis, researchers or data analysts can select a suitable mining tool. Topic extraction and buzz analysis are usually related to market trends analysis, while sentiment analysis is utilized to conduct reputation analysis. There are also various applications, such as stock prediction, product recommendation, sales forecasting, and so on. The last phase is visualization and presentation of analysis results. The major focus and purpose of this phase are to explain results of analysis and help users to comprehend its meaning. Therefore, to the extent possible, deliverables from this phase should be made simple, clear and easy to understand, rather than complex and flashy. To illustrate our approach, we conducted a case study on a leading Korean instant noodle company. We targeted the leading company, NS Food, with 66.5% of market share; the firm has kept No. 1 position in the Korean "Ramen" business for several decades. We collected a total of 11,869 pieces of contents including blogs, forum contents and news articles. After collecting social media content data, we generated instant noodle business specific language resources for data manipulation and analysis using natural language processing. In addition, we tried to classify contents in more detail categories such as marketing features, environment, reputation, etc. In those phase, we used free ware software programs such as TM, KoNLP, ggplot2 and plyr packages in R project. As the result, we presented several useful visualization outputs like domain specific lexicons, volume and sentiment graphs, topic word cloud, heat maps, valence tree map, and other visualized images to provide vivid, full-colored examples using open library software packages of the R project. Business actors can quickly detect areas by a swift glance that are weak, strong, positive, negative, quiet or loud. Heat map is able to explain movement of sentiment or volume in categories and time matrix which shows density of color on time periods. Valence tree map, one of the most comprehensive and holistic visualization models, should be very helpful for analysts and decision makers to quickly understand the "big picture" business situation with a hierarchical structure since tree-map can present buzz volume and sentiment with a visualized result in a certain period. This case study offers real-world business insights from market sensing which would demonstrate to practical-minded business users how they can use these types of results for timely decision making in response to on-going changes in the market. We believe our approach can provide practical and reliable guide to opinion mining with visualized results that are immediately useful, not just in food industry but in other industries as well.

• The Journal of Society for e-Business Studies
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• v.25 no.3
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• pp.41-61
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• 2020

China's rapid development and commercialization of high-tech technologies in the fourth industrial revolution has led to effective technology exchanges between Korean and Chinese firms becoming more important to Korea's mid-term and long-term industrial development. However, there is still a lack of empirical research on how technology exchanges between Korean and Chinese firms proceed and their effectiveness. In response, this study conducted a social network analysis based on text mining data of Korea-China business technology exchange and cooperation articles introduced in the news from 2018 to March 2020 on the current status and effects of Korea-China technology exchanges related to the fourth industrial revolution, and conducted a regression analysis how network centrality effect on the firm performance. According to the results, most of the Korean major electronic firms are actively networking with Chinese firms and institutions, showing high centrality in the centrality index. Korean telecommunication firms showed high betweenness centrality and subgraph centrality, and Korean Internet service providers and broadcasting contents firms showed high eigenvector centrality. In addition, Chinese firms showed higher betweenness centrality than Korean firms, and Chinese service firms showed higher closeness centrality than manufacturing firms. As a result of regression analysis, this network centrality had a positive effect on firm performance. To the best of our knowledge, this is the first to analyze the impact of the technical cooperation between Korean and Chinese firms under the fourth industrial revolution context. This study has theoretical implications that suggested the direction of social network analysis-based empirical research in global firm cooperation. Also, this study has practical implications that the guidelines for network analysis in setting the direction of technical cooperation between Korea and China by firms or governments.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.25-41
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• 2014

Recently, the number of social media users has increased rapidly because of the prevalence of smart devices. As a result, the amount of real-time data has been increasing exponentially, which, in turn, is generating more interest in using such data to create added value. For instance, several attempts are being made to analyze the relevant search keywords that are frequently used on new portal sites and the words that are regularly mentioned on various social media in order to identify social issues. The technique of "topic analysis" is employed in order to identify topics and themes from a large amount of text documents. As one of the most prevalent applications of topic analysis, the technique of issue tracking investigates changes in the social issues that are identified through topic analysis. Currently, traditional issue tracking is conducted by identifying the main topics of documents that cover an entire period at the same time and analyzing the occurrence of each topic by the period of occurrence. However, this traditional issue tracking approach has two limitations. First, when a new period is included, topic analysis must be repeated for all the documents of the entire period, rather than being conducted only on the new documents of the added period. This creates practical limitations in the form of significant time and cost burdens. Therefore, this traditional approach is difficult to apply in most applications that need to perform an analysis on the additional period. Second, the issue is not only generated and terminated constantly, but also one issue can sometimes be distributed into several issues or multiple issues can be integrated into one single issue. In other words, each issue is characterized by a life cycle that consists of the stages of creation, transition (merging and segmentation), and termination. The existing issue tracking methods do not address the connection and effect relationship between these issues. The purpose of this study is to overcome the two limitations of the existing issue tracking method, one being the limitation regarding the analysis method and the other being the limitation involving the lack of consideration of the changeability of the issues. Let us assume that we perform multiple topic analysis for each multiple period. Then it is essential to map issues of different periods in order to trace trend of issues. However, it is not easy to discover connection between issues of different periods because the issues derived for each period mutually contain heterogeneity. In this study, to overcome these limitations without having to analyze the entire period's documents simultaneously, the analysis can be performed independently for each period. In addition, we performed issue mapping to link the identified issues of each period. An integrated approach on each details period was presented, and the issue flow of the entire integrated period was depicted in this study. Thus, as the entire process of the issue life cycle, including the stages of creation, transition (merging and segmentation), and extinction, is identified and examined systematically, the changeability of the issues was analyzed in this study. The proposed methodology is highly efficient in terms of time and cost, as it sufficiently considered the changeability of the issues. Further, the results of this study can be used to adapt the methodology to a practical situation. By applying the proposed methodology to actual Internet news, the potential practical applications of the proposed methodology are analyzed. Consequently, the proposed methodology was able to extend the period of the analysis and it could follow the course of progress of each issue's life cycle. Further, this methodology can facilitate a clearer understanding of complex social phenomena using topic analysis.

• Journal of Global Scholars of Marketing Science
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• v.20 no.1
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• pp.4-14
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• 2010

Collaboration strategies entail information sharing and other varied forms of cooperation that are mutually beneficial to the company and stakeholder groups. This study addresses the specific types of collaboration used in the fashion industry while also examining strategies that have been most successful for fashion companies and perceived benefits of collaboration from the customer perspective. In the present study we define fashion companies and brands as collaborators and their partners or stakeholders as collaboratees. We define collaboration as a cooperative relationship where more than two companies, brands or individuals provide customers with beneficial outcomes utilizing their own competitive advantages on an equal basis. Collaboration strategies entail information sharing and other varied forms of cooperation that are mutually beneficial to the company and stakeholder groups. Through collaboration, fashion companies have pursued both tangible differentiation, such as design and technology applications, and intangible differentiation such as emotional and psychological benefits to customers. As a result, collaboration within the fashion industry has become an important, value creating concept. This qualitative study utilized case studies and in-depth interview methodologies to examine customers' attitudes concerning collaboration in the fashion industry. A total of 173 collaboration cases were identified in Korean and international markets from 1998 through December 2008, focusing on fashion companies. Cases were collected from documented data including websites and industry data bases and top ranked portal search sites such as: Rankey.com; Naver, Daum, and Nate; and representative fashion information websites, Samsungdesignnet and Firstviewkorea. Cases were collected between November 2008 and February 2009. Cases were selected for the analysis where one or more partners were associated with the production of fashion products (excluding textile production), retail fashion products, or designer services. Additional collaboration case information was obtained from news articles, periodicals, internet portal sites and fashion information sites as conducted in prior studies (Jeong and Kim 2008; Park and Park 2004; Yoon 2005). In total, 173 cases were selected for analysis that clearly exhibited the benefits and outcomes of collaboration efforts and strategies between fashion companies and stakeholders. Findings show that the overall results show that for both partners (collaborator and collaboratee) participating in collaboration, that the major benefits are reduction of costs and risks by sharing resource such as design power, image, costs, technology and targets, and creation of synergy. Regarding types of collaboration outcomes, product/design was most important (55%), followed by promotion (21%), price (20%), and place (4%). This result shows that collaboration plays an important role in giving life to products and designs, particularly in the fashion industry which seeks for creative and newness. To be successful in collaboration efforts, results of the depth interviews in this study confirm that fashion companies should have a clear objective on why they are doing the collaboration. After setting the objective, they should select collaboratees that match their brand image and target market, make quality co-products that have definite concepts and differentiating factors, and also pay attention to increasing brand awareness. Based on depth interviews with customers, customer benefits were categorized into six factors: pursuit for individual character; pursuit for brand; pursuit for scarcity; pursuit for fashion; pursuit for economic efficiency; and pursuit for sociality. Customers also placed more importance on image, reputation, and trust of brands regarding the cases shown in the interviews. They also commented that strong branding should come first before other marketing strategies. However, success factors recognized by experts and customers in this study showed different results by subcategories. Thus, target customers and target market should be studied from various dimensions to develop appropriate strategies for successful collaboration.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.45-55
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• 2013

Thereby using smartphone and mobile device be more popular the more people utilize mobile device in many area such as education, news, financial. In January, 2007 Apple release i-phone it touch off rapid increasing in user of smartphone and it create new market and these broaden its utilization area. Smartphone use WiFi or 3G mobile radio communication network and it has a feature that can access to internet whenever and anywhere. Also using smartphone application people can search arrival time of public transportation in real time and application is used in mobile banking and stock trading. Computer's function is replaced by smartphone so it involves important user's information such as financial and personal pictures, videos. Present smartphone security systems are not only too simple but the unlocking methods are spreading out covertly. I-phone is secured by using combination of number and character but USA's IT magazine Engadget reveal that it is easily unlocked by using combination with some part of number pad and buttons Android operation system is using pattern system and it is known as using 9 point dot so user can utilize various variable but according to Jonathan smith professor of University of Pennsylvania Android security system is easily unlocked by tracing fingerprint which remains on the smartphone screen. So both of Android and I-phone OS are vulnerable at security threat. Compared with problem of password and pattern finger recognition has advantage in security and possibility of loss. The reason why current using finger recognition smart phone, and device are not so popular is that there are many problem: not providing reasonable price, breaching human rights. In addition, finger recognition sensor is not providing reasonable price to customers but through continuous development of the smartphone and device, it will be more miniaturized and its price will fall. So once utilization of finger recognition is actively used in smartphone and if its utilization area broaden to financial transaction. Utilization of biometrics in smart device will be debated briskly. So in this thesis we will propose fingerprint numbering system which is combined fingerprint and password to fortify existing fingerprint recognition. Consisted by 4 number of password has this kind of problem so we will replace existing 4number password and pattern system and consolidate with fingerprint recognition and password reinforce security. In original fingerprint recognition system there is only 10 numbers of cases but if numbering to fingerprint we can consist of a password as a new method. Using proposed method user enter fingerprint as invested number to the finger. So attacker will have difficulty to collect all kind of fingerprint to forge and infer user's password. After fingerprint numbering, system can use the method of recognization of entering several fingerprint at the same time or enter fingerprint in regular sequence. In this thesis we adapt entering fingerprint in regular sequence and if in this system allow duplication when entering fingerprint. In case of allowing duplication a number of possible combinations is $\sum_{I=1}^{10}\;{_{10}P_i}$ and its total cases of number is 9,864,100. So by this method user retain security the other hand attacker will have a number of difficulties to conjecture and it is needed to obtain user's fingerprint thus this system will enhance user's security. This system is method not accept only one fingerprint but accept multiple finger in regular sequence. In this thesis we introduce the method in the environment of smartphone by using multiple numbered fingerprint enter to authorize user. Present smartphone authorization using pattern and password and fingerprint are exposed to high risk so if proposed system overcome delay time when user enter their finger to recognition device and relate to other biometric method it will have more concrete security. The problem should be solved after this research is reducing fingerprint's numbering time and hardware development should be preceded. If in the future using fingerprint public certification becomes popular. The fingerprint recognition in the smartphone will become important security issue so this thesis will utilize to fortify fingerprint recognition research.

• (The)Study of the Eastern Classic
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• no.49
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• pp.431-459
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• 2012

The purpose of this article is to compare and analyze the conventional expression of Hangul Ganchal in Cheosun Dynasty and Email. Conventional expression is used remarkably in introductions and conclusions. In introduction, it is used for addressing and safety greetings while in conclusion, it is used for closing address and closing words. In Cheosun Dynasty, an envelope of Ganchal only included the details of the receiver because the letter was genuinely delivered by someone who knew the receiver and the sender very well. An envelope of Ganchal is applicable to the screen of the internet which is used for emailing. In an email, we see the name of the sender and the title of the text and once we click the title, we are able to view the text. The difference between the Ganchal and the email was reflected on how the receiver's detail showed on Ganchal and the email show the sender's details. In a case of addressing in a letter while using the conventional expression, we can see how we use "To~" in humble term and " ~께" in a honorific term. We confirmed that the conventional expression has not yet settled in both of the Gnachal and email for the seasonal greetings. The safety greetings comprised with both of the senders' and receivers' latest updates. In Ganchal, this composition is well described conventionally, whereas in emails, only the receivers' latest news are written but the senders' latest updates are hard to be seen throughout the text. In Ganchal's closing section, the closing address and closing words were expressed conventionally. However, in the case of email; those were again hard to be found throughout. To conclude, in Ganchal the conventional expression was developed and placed in 16thcentury(Sun-eon) when there was a focus in our native language. In 17thcentury(Hyeon-eon), it stood still for a sometime and moved on to 19thcentury(Jing-eon) when there was a strong in fluence of Hangul Ganchal, which resulted in regression to the conservative expression. In general, we are able to confirm that the conventional expression is slowly disappearing.