• Asia Pacific Journal of Corpus Research
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• v.3 no.2
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• pp.17-33
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• 2022

While the term is nothing new, 'cybersecurity' still seems to be defined quite loosely and subjectively depending on context. This is problematic especially to legal writers for prosecuting cybercrimes that do not fit a particular clause/act. In fact, what is more difficult is the non-existent single 'cybersecurity law' in Malaysia, rather than the current implementation of 10-related cyber security acts. In this paper, the 10 acts are compiled into a corpus to analyse the language used in these acts via a corpus linguistics approach. A list of frequent words is firstly investigated to see whether the so-called related laws do talk about cybersecurity followed by close inspection of the concordance lines and habitually associated phrases (clusters) to explore use of these words in context. The 'compare 2 wordlist' feature is used to identify similarities or differences between the 10 Malaysian cybersecurity related laws against a corpus of cyber laws from other ASEAN countries. Findings revealed that ASEAN cyber laws refer mostly to three cybersecurity dominant themes identified in the literature: technological solutions, events, and strategies, processes, and methods, whereas Malaysian cybersecurity-related laws revolved around themes like human engagement, and referent objects (of security). Although these so-called cyber related policies and laws in Malaysia are highlighted in the National Cyber Security Agency (NACSA), their practical applications to combat cybercrimes remain uncertain.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.129-142
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• 2016

Customer product reviews have become one of the important factors for purchase decision makings. Customers believe that reviews written by others who have already had an experience with the product offer more reliable information than that provided by sellers. However, there are too many products and reviews, the advantage of e-commerce can be overwhelmed by increasing search costs. Reading all of the reviews to find out the pros and cons of a certain product can be exhausting. To help users find the most useful information about products without much difficulty, e-commerce companies try to provide various ways for customers to write and rate product reviews. To assist potential customers, online stores have devised various ways to provide useful customer reviews. Different methods have been developed to classify and recommend useful reviews to customers, primarily using feedback provided by customers about the helpfulness of reviews. Most shopping websites provide customer reviews and offer the following information: the average preference of a product, the number of customers who have participated in preference voting, and preference distribution. Most information on the helpfulness of product reviews is collected through a voting system. Amazon.com asks customers whether a review on a certain product is helpful, and it places the most helpful favorable and the most helpful critical review at the top of the list of product reviews. Some companies also predict the usefulness of a review based on certain attributes including length, author(s), and the words used, publishing only reviews that are likely to be useful. Text mining approaches have been used for classifying useful reviews in advance. To apply a text mining approach based on all reviews for a product, we need to build a term-document matrix. We have to extract all words from reviews and build a matrix with the number of occurrences of a term in a review. Since there are many reviews, the size of term-document matrix is so large. It caused difficulties to apply text mining algorithms with the large term-document matrix. Thus, researchers need to delete some terms in terms of sparsity since sparse words have little effects on classifications or predictions. The purpose of this study is to suggest a better way of building term-document matrix by deleting useless terms for review classification. In this study, we propose neutrality index to select words to be deleted. Many words still appear in both classifications - useful and not useful - and these words have little or negative effects on classification performances. Thus, we defined these words as neutral terms and deleted neutral terms which are appeared in both classifications similarly. After deleting sparse words, we selected words to be deleted in terms of neutrality. We tested our approach with Amazon.com's review data from five different product categories: Cellphones & Accessories, Movies & TV program, Automotive, CDs & Vinyl, Clothing, Shoes & Jewelry. We used reviews which got greater than four votes by users and 60% of the ratio of useful votes among total votes is the threshold to classify useful and not-useful reviews. We randomly selected 1,500 useful reviews and 1,500 not-useful reviews for each product category. And then we applied Information Gain and Support Vector Machine algorithms to classify the reviews and compared the classification performances in terms of precision, recall, and F-measure. Though the performances vary according to product categories and data sets, deleting terms with sparsity and neutrality showed the best performances in terms of F-measure for the two classification algorithms. However, deleting terms with sparsity only showed the best performances in terms of Recall for Information Gain and using all terms showed the best performances in terms of precision for SVM. Thus, it needs to be careful for selecting term deleting methods and classification algorithms based on data sets.

• International Journal of Contents
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• v.10 no.2
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• pp.37-41
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• 2014

This study defined the pre-elderly as middle age people from 50 to 59. Because it is difficult to produce a design to satisfy the pre-elderly without deeply understanding them, their financial and physical characteristics and persona-based scenario method was studied. An experimental study about persona based scenario method was conducted, and as a result, the types of personas found were as follows: 1) Users enjoy the same games online and offline. 2) Users enjoy playing alone on the computer. 3) Users prefer games that end quickly with win or loss. Writing the situation scenario for each type, the pre-elderly's problems and needs occurring while they play web board games were obtained. The obtained user requests were as follows: users would like the level of difficulty to be simpler in the game of baduk; users wanted unlimited credit and refrainment from using English words in go-Stop; and there were simple comments about game screen design.

• The Journal of the Korea Contents Association
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• v.8 no.11
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• pp.10-17
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• 2008

The sign recognition and translation offer information and support decision making for foreigners or city tourist. Collecting sign images and building words in signs are essential to train machine recognizers and to evaluate systems. In this paper, we analyze the characteristics of sign images. The collected sign images are about 1000 captured from difference conditions and locations. We also build a dictionary of words in 100,000 sign names.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.95-107
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• 2020

This study analyzes the effect of corporate social responsibility (CSR) activity on investors' heterogeneous beliefs. The hypothesis of this study is based on the conflicting effects of CSR activities on firm value and earning's quality. Investors' heterogeneous beliefs used in the empirical analysis of this study are trading volume, and CSR activity is measured by the KEJI Index (Korea Economic Justice Institute Index). This study performs an empirical analysis using regression analysis including control variables. CSR activities are found to have a positive relationship with trading volume. This is consistent regardless of the low and high accounting information (earning's quality). It can be interpreted that Korea's CSR activity acts as an incentive to increase investors' heterogeneous beliefs about target companies. In other words, it implies that the investor judges CSR activities negatively when evaluating firm value. This study could have a policy implication in that it analyzes how CSR activities affect investors' decision-making. In other words, this study analyzed CSR activities from the perspective of shareholders. Therefore, this study is expected to provide useful information for policymaking by regulatory agencies. In particular, its contribution is to presents data that CSR activities can be a negative factor in evaluating firm values.

• Journal of the Korea Convergence Society
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• v.12 no.5
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• pp.121-126
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• 2021

Based on network agenda-setting theory, this study attempted to analyze media reports about suicide from 2000 to 2020 in order to find solutions for suicide problem in the Korean society. Results showed that top 10 key words in media were suicide, death leap, death, attempt, supposition, discovery, men, pessimism. Those key words were appeared similarly and contunually in the media. In addition, both newspapers and broadcastings had similar reports trend, so it is plausible to consider inter-media agenda setting relations between newspapers and broadcasings.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.7
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• pp.345-350
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• 2016

This research suggests the keyword filtering about disaster and the method of detecting area in real-time event detecting system by analyzing contents of twitter. The diffusion of smart-mobile has lead to a fast spread of SNS and nowadays, various researches based on studying SNS are being processed. Among SNS, the twitter has a characteristic of fast diffusion since it is written in 140 words of short paragraph. Therefore, the tweets that are written by twitter users are able to perform a role of sensor. By using these features the research has been constructed which detects the events that have been occurred. However, people became reluctant to open their information of location because it is reported that private information leakage are increasing. Also, problems associated with accuracy are occurred in process of analyzing the tweet contents that do not follow the spelling rule. Therefore, additional designing keyword filtering and the method of area detection on detecting real-time event process were required in order to develop the accuracy. This research suggests the method of keyword filtering about disaster and two methods of detecting area. One is the method of removing area noise which removes the noise that occurred in the local name words. And the other one is the method of determinating the area which confirms local name words by using landmarks. By applying the method of keyword filtering about disaster and two methods of detecting area, the accuracy has improved. It has improved 49% to 78% by using the method of removing area noise and the other accuracy has improved 49% to 89% by using the method of determinating the area.

• Journal of the Korea Convergence Society
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• v.10 no.6
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• pp.59-64
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• 2019

This study used the Google Trends site to analyze selection information that users expect from prominent Toothbrushes and Toothpastes through related search keywords that users wanted to obtain. From 2006 to 2018(sep), searches for Toothbrushes and Toothpastes were arranged in the order of popularity of related searched words. The total number of searches words exposed was each 25, total 325 collected. The analysis was conducted using two methods, first, by search function. second, by a word network using a Big Data program. The study has shown that toothbrushes there are high expectations for brands, toothpaste there are high expectations in the function. In order to increase the motivation for oral health education, it is recommended to use and provide knowledge about the brand of toothbrushes and Toothpastes by the function.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.4
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• pp.251-256
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• 1988

This work describes a speech analysis of Korean number ('1'-'10') which are spoken by several speakers using Fast Walsh Transform(FWHT) method. FWHT includes only addition and subtraction operations, therefore faster and needs less memory than FFT(Fast Fourier Transfifrm) or LPC(Linear Predictive Coding) analysis method. We have investigated that FWHT method can find speaker independent feature(which represents same cue about some word independent of different speakers) The results of this experiment, the 70% of same words(korean number '2')which spoken by several speakers have had slmilar patterns.

• YAKHAK HOEJI
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• v.56 no.5
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• pp.333-345
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• 2012

A product labelling is one of key tools in ensuring that a patient uses drugs safely and effectively in self-care without professional support. This study aimed to explore the readability and comprehensibility of the information contained on two package inserts of medicines. Two package inserts were tested with first year college students. Fifty-one potential consumers underlined words they could not understand and answered 10 scenario questions. Any differences among groups with different characteristics were statistically tested. Secondly, the readability of two package inserts was assessed with comparison to the level of the 6th grade Korean textbooks. As results, more than 80% of participants properly replied to straightforward questions concerning indication, dosage, duplication, use in pregnancy and contraindication, and 73% about formulation. Less than half answered correctly in multiple choice questions about pediatric use (41%) and side effects (35%). Little discrepancy was observed in the comprehensibility between participants' characteristics. Drug inserts contained about 20% more professional-level words than 6th grade textbooks. In conclusion, Korean consumers may face challenges to understand drug information due to professional terminology and outdated expressions in the current package inserts. To secure safe and effective use of over-the-counter agents, greater efforts should be made to develop more consumer friendly labels. In the other hand, educational supports are required to prepare consumers in a proper level of knowledge for the safe use of drugs.