• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.49-67
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• 2015

Recently, emerging the notion of big data and social media has led us to enter data's big bang. Social networking services are widely used by people around the world, and they have become a part of major communication tools for all ages. Over the last decade, as online social networking sites become increasingly popular, companies tend to focus on advanced social media analysis for their marketing strategies. In addition to social media analysis, companies are mainly concerned about propagating of negative opinions on social networking sites such as Facebook and Twitter, as well as e-commerce sites. The effect of online word of mouth (WOM) such as product rating, product review, and product recommendations is very influential, and negative opinions have significant impact on product sales. This trend has increased researchers' attention to a natural language processing, such as a sentiment analysis. A sentiment analysis, also refers to as an opinion mining, is a process of identifying the polarity of subjective information and has been applied to various research and practical fields. However, there are obstacles lies when Korean language (Hangul) is used in a natural language processing because it is an agglutinative language with rich morphology pose problems. Therefore, there is a lack of Korean natural language processing resources such as a sentiment lexicon, and this has resulted in significant limitations for researchers and practitioners who are considering sentiment analysis. Our study builds a Korean sentiment lexicon with collective intelligence, and provides API (Application Programming Interface) service to open and share a sentiment lexicon data with the public (www.openhangul.com). For the pre-processing, we have created a Korean lexicon database with over 517,178 words and classified them into sentiment and non-sentiment words. In order to classify them, we first identified stop words which often quite likely to play a negative role in sentiment analysis and excluded them from our sentiment scoring. In general, sentiment words are nouns, adjectives, verbs, adverbs as they have sentimental expressions such as positive, neutral, and negative. On the other hands, non-sentiment words are interjection, determiner, numeral, postposition, etc. as they generally have no sentimental expressions. To build a reliable sentiment lexicon, we have adopted a concept of collective intelligence as a model for crowdsourcing. In addition, a concept of folksonomy has been implemented in the process of taxonomy to help collective intelligence. In order to make up for an inherent weakness of folksonomy, we have adopted a majority rule by building a voting system. Participants, as voters were offered three voting options to choose from positivity, negativity, and neutrality, and the voting have been conducted on one of the largest social networking sites for college students in Korea. More than 35,000 votes have been made by college students in Korea, and we keep this voting system open by maintaining the project as a perpetual study. Besides, any change in the sentiment score of words can be an important observation because it enables us to keep track of temporal changes in Korean language as a natural language. Lastly, our study offers a RESTful, JSON based API service through a web platform to make easier support for users such as researchers, companies, and developers. Finally, our study makes important contributions to both research and practice. In terms of research, our Korean sentiment lexicon plays an important role as a resource for Korean natural language processing. In terms of practice, practitioners such as managers and marketers can implement sentiment analysis effectively by using Korean sentiment lexicon we built. Moreover, our study sheds new light on the value of folksonomy by combining collective intelligence, and we also expect to give a new direction and a new start to the development of Korean natural language processing.

• Information Systems Review
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• v.20 no.2
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• pp.39-62
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• 2018

Thanks to the growth of computing power and the recent development of data analytics, researchers have started to work on the data produced by users through the Internet or social media. This study is in line with these recent research trends and attempts to adopt data analytical techniques. We focus on the impact of "internal marketing" factors on firm performance, which is typically studied through survey methodologies. We looked into the job review platform Jobplanet (www.jobplanet.co.kr), which is a website where employees and former employees anonymously review companies and their management. With web crawling processes, we collected over 40K data points and performed morphological analysis to classify employees' reviews for internal marketing data. We then implemented econometric analysis to see the relationship between internal marketing and market capitalization. Contrary to the findings of extant survey studies, internal marketing is positively related to a firm's market capitalization only within a limited area. In most of the areas, the relationships are negative. Particularly, female-friendly environment and human resource development (HRD) are the areas exhibiting positive relations with market capitalization in the manufacturing industry. In the service industry, most of the areas, such as employ welfare and work-life balance, are negatively related with market capitalization. When firm size is small (or the history is short), female-friendly environment positively affect firm performance. On the contrary, when firm size is big (or the history is long), most of the internal marketing factors are either negative or insignificant. We explain the theoretical contributions and managerial implications with these results.

• Korea Science and Art Forum
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• v.31
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• pp.21-32
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• 2017

Local festivals form the regional cultures and atmosphere of communication; they increase the demand of domestic tourism businesses and thus, have an important role in ripple effects (e.g. regional image improvement, tourist influx, job creation, regional contents development, and local product sales) and economic revitalization. IoT (Internet of Thing) technologies have been developed especially, beacon-one of the IoT services has been applied as plenty of types and forms both domestically and internationally. However, notwithstanding expansion of current digital mobile technologies, it still remains as difficult for the individual to track the information about all the local festivals and to fulfill the tourists' needs of enjoying festivals given the weak strategic approaches and advertisement activities. Furthermore, current festival-related mobile applications don't function well as delivering information and have numerous contents issues (e.g. ways of information delivery within the festival places, independent application usage for each festival, one time usage due to one time event). This research, based on the background mentioned above, aims to develop the local festival mobile application and data analysis system applying beacon technology. First of all, three algorithms were developed, namely, 'festival crowding algorithm', 'visitor stats algorithm', and 'customized information algorithm', and then beta test was followed with the developed application and data analysis system. As a result, they could form the database of visitors' types and behaviors, and provide functions and services, such as personalized information, waiting time for festival contents, and 'hot place' function. Besides, in Google Play store, they also got the titles given with more than 13,000 downloads within first three months and as the most exposed application related with festivals; and, thus, got credited with their marketability and excellence. This research follows this order: chapter 2 shows the literature review of local festival related with technology development, beacon service, and festival application. In Chapter 3, design plans and conditions are described of developing local festival mobile application and data analysis system with beacon. Chapter 4 evaluates the results of the beta performance test to verify applicability of the developed application and data analysis system, and lastly, chapter 5 explains the conclusion and suggests the future research.

• Asia pacific journal of information systems
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• v.23 no.3
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• pp.131-154
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• 2013

New internet technologies have created a revolutionary new platform which allows consumers to make decision about product price and quality quickly and provides information about themselves through the transcript of online reviews. By expressing their feelings toward products or services on virtual opinion platforms, users extend their influence into cyberspace as electronic word-of-mouth (e-WOM). Existing research indicates that an impact of eWOM on the consumer decision process is influential. For both academic researchers and practitioners, investigating this phenomenon of information sharing in online website is essential given the increasing number of consumers using them as sources of purchase decisions. It is worthwhile to examine the extent to which opinion seekers are willing to accept and adopt online reviews and which factors encourage adoption. Discerning the most motivating aspects of information adoption in particular, could help electronic marketers better promote their brand and presence on the internet. The objectives of this study are to investigate how online WOM influences a persons' purchase decision by discovering which factors encourage information adoption. Especially focused on the self-efficacy, this research investigates how self-efficacy affects on information usefulness and adoption of online information. Although people are exposed to same review or comment about product or service, some accept the reviews while others do not. We notice that accepting online reviews mainly depends on the person's preference or personal characteristics. This study empirically examines this issue by using cognitive dissonance theory. Specifically, in the movie industry, we address few questions-is always positive WOM generating positive effect? What if the movie isn't the person's favorite genre? What if the person who is very self-assertive so doesn't take other's opinion easily? In these cases of cognitive dissonance, is always WOM generating same result? While many studies have focused on one direct of WOM which indicates positive (or negative) informative reviews or comments generate positive (or negative) results and more (or less) profits, this study investigates not only directional properties of WOM but also how people change their opinion towards product or service positive to negative, negative to positive through the online WOM. An experiment was conducted quantitatively by using a sample of 168 users who have experience within the online movie review site, 'Naver Movie'. Users were required to complete a survey regarding reviews and comments taken from the real movie page. The data reflected user's perceptions of online WOM information that determined users' adoption level. Analysis results provide empirical support for the proposed theoretical perspective. When user can't agree with the opinion of online WOM information, in other words, when cognitive dissonance between online WOM information and users' preference occurs, perceived self-efficacy significantly decreases customers' perception of usefulness. And this perception of usefulness plays an important role in determining users' intention to adopt online WOM information. Most of researches have been concentrated on characteristics of online WOM itself such as quality or vividness of information, credibility of source and direction of online WOM, etc. for describing effect of online WOM, but our results suggest that users' personal character (e.g., self-efficacy) plays decisive role for acceptance of online WOM information. Higher self-efficacy means lower possibility to accept the information that represents counter opinion because of cognitive dissonance, whereas the people that have lower self-efficacy are willing to accept the online WOM information as true and refer to purchase decision. This study suggests a model for understanding role of direction of online WOM information. Also, our result implicates the importance of online review supervision and personalized information service by confirming switching opinion negative to positive is more difficult than positive to negative through the online WOM information. This implication would help marketers to manage online reviews of their products or services.

• Journal of Internet Computing and Services
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• v.15 no.1
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• pp.29-43
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• 2014

The development of NGS technologies, such as scientific workflows, has reduced the time required for decoding DNA sequences. Although the automated technologies change the genome sequence analysis environment, limited computing resources still pose problems for the analysis. Most scientific workflow systems are pre-built platforms and are highly complex because a lot of the functions are implemented into one system platform. It is also difficult to apply components of pre-built systems to a new system in the cloud environment. Cloud computing technologies can be applied to the systems to reduce analysis time and enable simultaneous analysis of massive DNA sequence data. Web service techniques are also introduced for improving the interoperability between DNA sequence analysis systems. The workflow-based middleware, which supports Web services, DBMS, and cloud computing, is proposed in this paper for expecting to reduceanalysis time and aiding lightweight virtual instances. It uses DBMS for managing the pipeline status and supporting the creation of lightweight virtual instances in the cloud environment. Also, the RESTful Web services with simple URI and XML contents are applied for improving the interoperability. The performance test of the system needs to be conducted by comparing results other developed DNA analysis services at the stabilization stage.

• Journal of Distribution Science
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• v.12 no.6
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• pp.5-13
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• 2014

Purpose - The purposes of this editorial review are twofold: firstly, to introduce the four flagship international journals of the Korea Distribution Science Association(KODISA): the Journal of Distribution Science(JDS), the Journal of Industrial Distribution & Business(JIDB), the East Asian Journal of Business Management(EAJBM), and the Journal of Asian Finance, Economics and Business(JAFEB), and secondly, to identify the direction of the KODISA journals and the roles and responsibilities of the editors of the KODISA journals. Research design, data, and methodology - To achieve the goals, firstly, this review paper addresses the current progress of the four KODISA journals: JDS, JIDB, EAJBM, and JAFEB. Secondly, this paper defines the aims and missions of the four KODISA journals. JDS publishes the articles of examining past, current, and emerging trends and concerns in the area of distribution science and economics, logistics and SCM, transportation, distribution channel management, distribution innovation and information technology, merchandising and procurement, distribution and marketing, consumer behavior, and manufacturing, wholesaling, and retailing. JDS publishes both quantitative and qualitative research as well as scholarly commentaries, case studies, book reviews and other types of reports relating to all aspects of distribution. JIDB publishes the articles of examining past, current, and emerging trends and concerns in the areas of industry and corporate behavior, industry policy making, industrial distribution and business, e-commerce, and service industry. EAJBM publishes empirical and theoretical research papers as well as scholarly commentaries, case studies, book reviews, and other types of reports relating to all aspects of East Asian business and economy. JAFEB publishes original research analysis and inquiry into the contemporary issues of finance, economics and business management in Asia, including Central Asia, East Asia, South Asia, Southeast Asia, and Middle East. The mission of JAFEB is to bring together the latest theoretical and empirical finance, economics and business management research in Asian markets. The audiences of the KODISA journals include higher education institutions, scholars, industry researchers and practitioners, scientists, economists, and policy makers throughout the world. The main mission of the KODISA journals is to provide an intellectual platform for international scholars, promote interdisciplinary studies in social sciences and economics, and become leading journals in the social science and economics category in the world. Thirdly, this paper addresses the current status of indexing in major databases of the KODISA journals, namely: Cabell's Directories, EBSCO, SCOPUS (Elsevier), and Social Sciences Citation Index^® (SSCI, Thomson Reuters). Fourthly, this paper identifies the roles and responsibilities of the editors of the KODISA journals as the following: (1) Make sure that the journal be published in a timely manner and in international standards both in print and online versions. (2) Maintain the online homepage of the journal is always accessible to, and (3) Make sure that every article should go through a peer review process that meets international standards. Findings and conclusion - To accomplish the goals and missions of the KODISA journals, the editors of the KODISA journals must work together to publish high scholarly journals that meet international standards of journal publications.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.977-980
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• 2015

Beacons have been noted in the core of the recent things Internet. It is also the technology is spreading most rapidly among the things Internet-related communication technologies. Beacon is a data communications technology that provides information that is customized to know the user's location. Using the BLE technology, to grasp the position of such people and goods. In addition to the non-contact method, since it is possible to communicate within the maximum 70m, it has attracted the interest than the NFC. Beacon, guidance for the current coupon, you can use as an advertising platform, such as the provision of product information, it has also been used in the indoor positioning service. Therefore, in this paper, we introduce about whether Case Study beacon is utilized how in the Internet of Things, were analyzed. Beacon exit the smart phone, the date to be used in conjunction with a wearable device, such as Google glasses and smart watch was not far away. Future it is expected or beacons are used everywhere to be expanded.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.37 no.1
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• pp.68-75
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• 2019

This study aims to look at the application methods of landscape architecture in response to the 4th Industrial Revolution. The results of the analysis of trends in the 4th Industrial Revolution and the subsequent search for application methods to the field of landscape architecture are as follows. First, the 4th Industrial Revolution means innovative change based on digital technology and seeks to create value based on intelligent information technology, and continuous growth is being made through innovation. This requires expertise to collect large amounts of information and creatively rework it, and a strategy to flexibly cope with changes in the times. Second, the status of technological use in response to the 4th Industrial Revolution in the field of landscape architecture is generalizing the establishment of precise analysis results such as survey technology and global mapping using drones, three-dimensional design simulation, and VR. In the field of traditional landscape architecture, efforts are made to obtain accurate fact-finding data on landscape site components. Third, the application methods in the field of landscape science according to the 4th Industrial Revolution in the future are required to supply precision technology and supply programs in the technology sector, and to provide a shared platform. In addition, a systemically standardized process will need to be established for this. In addition, educational efforts should be continued to professional manpower training and provide economic support for the development of technologies.

• Journal of Korea Entertainment Industry Association
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• v.14 no.3
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• pp.149-162
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• 2020

This paper applied components of experience-based communication in terms of experience theory of Burnd H. Schmitt and context-based communication in the messenger platform environment through the scenario-based survey method, in order to study the influence of individual experiences, shared experiences, ubiquitous connectivity, and contextual usefulness on the perceived value and use intention of chatbot. Through this, the study is to provide companies in various service industries with practical approaches to further promote the use of chatbot. The implications of this study are as follows. First, as most chatbots still do not exceed the human planning level of designing them, it is necessary to consider how to design individual experience elements functionally according to the customer's intention to speak when developing the chatbot. Second, the chatbot should be designed not only from the perspective of completing specific tasks at any real time in anywhere, but also from the overall perspective of enhancing the quality of interaction, including the situation to which the customer belongs. Third, since the chatbot is likely to be anthropomorphized by users, it is important to be cautious about determining the chatbot's 'persona' and 'tone and manner' when developing the chatbot. Customer satisfaction is the most important criterion for the success of chatbot development. In other words, the quality of planning and data rather than the quality of artificial intelligence algorithms determines the utilization of chatbot. This is why companies are trying to make interactions with chatbot as close as possible to human interactions.

• Journal of Digital Convergence
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• v.20 no.2
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• pp.241-250
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• 2022

Due to the COVID-19 pandemic, with increased 'untact' services and with unstable household economy, the bike insurance fraud is expected to surge. Moreover, the fraud methodology gets complicated. However, the fraud detection model for bike insurance is absent. we deal with the issue of skewed class distribution and reflect the criterion of fraud detection expert. We utilize a balanced random-forest algorithm to develop an efficient bike insurance fraud detection model. As a result, while the predictive performance of balanced random-forest model is superior than it of non-balanced model. There is no significant difference between the variables used by the experts and the confirmatory models. The important variables to detect frauds are turned out to be age and gender of driver, correspondence between insured and driver, the amount of self-repairing claim, and the amount of bodily injury liability.