• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.63-82
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• 2016

Individuals gather information online to resolve problems in their daily lives and make various decisions about the purchase of products or services. With the revolutionary development of information technology, Web 2.0 has allowed more people to easily generate and use online reviews such that the volume of information is rapidly increasing, and the usefulness and significance of analyzing the unstructured data have also increased. This paper presents an analysis on the lexical features of expert product reviews to determine their influence on consumers' purchasing decisions. The focus was on how unstructured data can be organized and used in diverse contexts through text mining. In addition, diverse lexical features of expert reviews of contents provided by a third-party review site were extracted and defined. Expert reviews are defined as evaluations by people who have expert knowledge about specific products or services in newspapers or magazines; this type of review is also called a critic review. Consumers who purchased products before the widespread use of the Internet were able to access expert reviews through newspapers or magazines; thus, they were not able to access many of them. Recently, however, major media also now provide online services so that people can more easily and affordably access expert reviews compared to the past. The reason why diverse reviews from experts in several fields are important is that there is an information asymmetry where some information is not shared among consumers and sellers. The information asymmetry can be resolved with information provided by third parties with expertise to consumers. Then, consumers can read expert reviews and make purchasing decisions by considering the abundant information on products or services. Therefore, expert reviews play an important role in consumers' purchasing decisions and the performance of companies across diverse industries. If the influence of qualitative data such as reviews or assessment after the purchase of products can be separately identified from the quantitative data resources, such as the actual quality of products or price, it is possible to identify which aspects of product reviews hamper or promote product sales. Previous studies have focused on the characteristics of the experts themselves, such as the expertise and credibility of sources regarding expert reviews; however, these studies did not suggest the influence of the linguistic features of experts' product reviews on consumers' overall evaluation. However, this study focused on experts' recommendations and evaluations to reveal the lexical features of expert reviews and whether such features influence consumers' overall evaluations and purchasing decisions. Real expert product reviews were analyzed based on the suggested methodology, and five lexical features of expert reviews were ultimately determined. Specifically, the "review depth" (i.e., degree of detail of the expert's product analysis), and "lack of assurance" (i.e., degree of confidence that the expert has in the evaluation) have statistically significant effects on consumers' product evaluations. In contrast, the "positive polarity" (i.e., the degree of positivity of an expert's evaluations) has an insignificant effect, while the "negative polarity" (i.e., the degree of negativity of an expert's evaluations) has a significant negative effect on consumers' product evaluations. Finally, the "social orientation" (i.e., the degree of how many social expressions experts include in their reviews) does not have a significant effect on consumers' product evaluations. In summary, the lexical properties of the product reviews were defined according to each relevant factor. Then, the influence of each linguistic factor of expert reviews on the consumers' final evaluations was tested. In addition, a test was performed on whether each linguistic factor influencing consumers' product evaluations differs depending on the lexical features. The results of these analyses should provide guidelines on how individuals process massive volumes of unstructured data depending on lexical features in various contexts and how companies can use this mechanism from their perspective. This paper provides several theoretical and practical contributions, such as the proposal of a new methodology and its application to real data.

• Journal of Korean Classical Literature and Education
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• no.39
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• pp.137-180
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• 2018

This article examines the constitutional characteristics of the works in the "Shinbi Apartment" (Mysterious Apartment) series produced by Tooniverse, a domestic animation channel, and considers the meaning of the contents of the ghoststory (鬼神談). The "Shinbi Apartment" series is a horror animation for children. It was produced for the first time in Korea and recorded high ratings. Additionally, it is different from Japanese horror animations that were dubbed and broadcast in Korea in terms of composition and narrative direction, and it succeeds in the form and direction of the traditional Korean ghost story. "Shinbi Apartment - The Secret of Ghost Ball" enriches narrative stories by embracing the structure of the "female ghost story" in traditional ghost stories while following the form of ghosts that suddenly pop up in the daily routines of contemporary ghost stories. The ghost's shape, which has a bizarre and unpredictable aspect, embodies the ghost as the object of fear that modern horror stories intend. However, it does not stop there, but puts the attention on the hero who focuses on the emerging ghost and listens and communicates with it, placing the emphasis of the story on communication, understanding, forgiveness, and reconciliation. The structure and contents of the unique story of "The Secret of Ghost Ball" contribute to the transformation of the ghost into a subject of friendliness and entertainment, not merely as one of shock, fear, and anxiety. Additionally, as the concept of "child" is being created, the custom of modernity, which deals with the story of ghosts in the dimension of teaching and edification, is also manifested in "The Secret of Ghost Ball." In other words, through the figure of the devil, it is to continue the lesson of the story by revealing the adventure, the courage necessary for the "child," and the boundaries for substance and appearance. The "Shinbi Apartment" series has also contributed to the success of ghosts as commercial contents. The structure of the story and its characters have been actively used as educational tools and toys for children. It can be said that ghost culture contributed to this popularization by establishing a base for enjoying ghosts for amusement and entertainment.

• Journal of Korea Entertainment Industry Association
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• v.14 no.5
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• pp.87-102
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• 2020

The purpose of this study was to develop regional dance contents in order to receive attention from the region and re-illuminate the peacock fan, the intangible cultural property of Seocheon, Chungnam, which has been preserved in history and has been preserved in the face of rapid urbanization and modernization. The representative four series are composed of one-person dance, two-person dance, military dance, and creative dance. The titles of each piece are basic dance , male and female love dance , military dance , and finally Korean creative dance . The commonality of the four series is the traditional dance using peacock fan, and each dance showed unique emotion and atmosphere through different themes and music, costumes, and stages. It was found that the development of regional dance contents re-created reflecting the characteristics of regional cultural heritage should create an environment that can be steadily revitalized through modernization. Through this study, it was found that the intangible cultural properties, which are our traditional cultural resources, have unlimited potential to contribute to enhancing regional and national competitiveness along with the growth potential of regional differentiation. Through such research, if existing cultural resources are preserved for globalization and produced as contents that can be easily accessed by the public, various contents besides regional dance using regional unique culture can be developed and utilized.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.