• The Journal of Economics, Marketing and Management
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• v.11 no.5
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• pp.45-55
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• 2023

Purpose: As one of the continuous studies on the offline distribution industry, the purpose of this study is to find ways for offline stores to respond to the growth of online shopping by identifying research trends on department stores. Research design, data and methodology: To this end, this study conducted word frequency analysis, word co-occurrence frequency analysis, BERTopic, LDA, and dynamic topic modeling using Python 3.7 on a total of 551 English abstracts searched with the keyword 'department store' in scienceON as of October 10, 2022. Results: The results of word frequency analysis and co-occurrence frequency analysis revealed that research related to department stores frequently focuses on factors such as customers, consumers, products, satisfaction, services, and quality. BERTopic and LDA analyses identified five topics, including 'store image,' with 'shopping information' showing relatively high interest, while 'sales systems' were observed to have relatively lower interest. Conclusions: Based on the results of this study, it was concluded that research related to department stores has so far been conducted in a limited scope, and it is insufficient to provide clues for department stores to secure competitiveness against online platforms. Therefore, it is suggested that additional research be conducted on topics such as the true role of department stores in the retail industry, consumer reinterpretation, customer value and lifetime value, department stores as future retail spaces, ethical management, and transparent ESG management.

• Journal of Korean Library and Information Science Society
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• v.42 no.4
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• pp.353-374
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• 2011

Analyzing research paper published from 2005 to 2010, this study aims for analysing the research paradigm on multi-culture and understanding the structural characteristics of the multicultural knowledge via scientometric. Co-word network constructed by keywords in documents and their co-occurrence relationships is a kind of mapping knowledge structure. A total of 4,521 and 1,373 papers published between 2005 and 2010 were retrieved from the KRF Registered Journals and Proposed Journals. This paper employs k-core analysis method in the field of mapping knowledge structure to analyze keyword co-occurrence network of multicultural research in Korea. And Netminer 3 is employed to visualize the networks in this paper.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.1
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• pp.110-114
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• 2010

We describe a new method for text categorization using TextRank algorithm. Text categorization is a problem that over one pre-defined categories are assigned to a text document. TextRank algorithm is a graph-based ranking algorithm. If we consider that each word is a vertex, and co-occurrence of two adjacent words is a edge, we can get a graph from a document. After that, we find important words using TextRank algorithm from the graph and make feature which are pairs of words which are each important word and a word adjacent to the important word. We use classifiers: SVM, Na$\ddot{i}$ve Bayesian classifier, Maximum Entropy Model, and k-NN classifier. We use non-cross-posted version of 20 Newsgroups data set. In consequence, we had an improved performance in whole classifiers, and the result tells that is a possibility of TextRank algorithm in text categorization.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.22 no.2
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• pp.235-248
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• 2011

In this study, co-word occurrence analysis was performed on 288 articles rerieved from the Web of Science DB with the topic of web archiving. Results showed that research on image archiving information technology and system were most frequently carried out especially in medical area. Within library and information science and records management & archives areas, web archiving/digital preservation project subject and web archiving tools and methodology subject were studied mostly. It is expected that research related to web archiving software and tools will be increased in near future.

• The Journal of Economics, Marketing and Management
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• v.10 no.6
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• pp.27-37
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• 2022

Purpose: The purpose of this study is to derive various ways to realize customer satisfaction for the development of the service industry by exploring research trends related to customer satisfaction, which is presented as an important goal in the service industry. Research design, data and methodology: To this end, 1,456 papers with English abstracts using scienceON were used for analysis. Using Python 3.7, word frequency and co-occurrence analysis were confirmed, and topics related to research trends were classified through BERTopic and LDA. Results: As a result of word frequency and co-occurrence frequency analysis, words such as quality, intention, and loyalty appeared frequently. As a result of BERTopic and LDA, 11 topics such as 'catering service' and 'brand justice' were derived. As a result of trend analysis, it was confirmed that 'brand justice' and 'internet shopping' are emerging as relatively important research topics, but CRM is less interested. Conclusions: The results of this study showed that the 7P marketing strategy is working to some extent. Therefore, it is proposed to conduct research related to acquisition of good customers through service price, customer lifetime value application, and customer segmentation that are expected to be needed for the development of the service industry.

• The Journal of Economics, Marketing and Management
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• v.11 no.4
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• pp.53-63
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• 2023

Purpose: The purpose of this study is to examine the research trends in the papers published by Korean researchers related to traditional markets, to check what topics have been studied, and to make various suggestions for research directions and effective ways to revitalize traditional markets. Research design, data and methodology: To this end, this study conducted word frequency analysis, co-occurrence frequency analysis, BERTopic, LDA, dynamic topic modeling and OLS regression analysis using Python 3.7 on the English abstracts of a total of 502 papers extracted through ScienceON. Results: As a result of word frequency analysis and co-occurrence frequency analysis, it was found that studies related to traditional markets have been conducted not only on factors related to customers, but also on traditional market merchants and government policies, and the degree of service, quality, and satisfaction perceived by customers using traditional markets. Through BERTopic and LDA, three topics such as 'Traditional market safety management' were identified, and among them, it was found that 'Traditional market safety management' is relatively less attention by researchers. Conclusions: The results of this study suggest that future research on the revitalization of traditional markets should be conducted from a specific consulting perspective along with the establishment of various data, a causal model study from various perspectives such as the characteristics of merchants as well as consumers, and an integrated and convergent approach to policy formulation by the government and local governments.

• Asia Pacific Journal of Corpus Research
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• v.2 no.1
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• pp.13-22
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• 2021

The present study employed an analytical framework that is characterised by a synthesis of quantitative and qualitative analyses with a specially designed computer software SpeechActConc to examine speech acts in business communication. The naturally occurring data from the audio recordings and the prosodic transcriptions of the business sub-corpora of the HKCSE (prosodic) are manually annotated with a speech act taxonomy for finding out the frequency of fillers, the co-occurring patterns of fillers with other speech acts, and the linguistic realisations of fillers. The discoursal function of fillers to sustain the discourse or to hold the floor has diverse linguistic realisations, ranging from a sound (e.g. 'uhuh') and a word (e.g. 'well') to sounds (e.g. 'um er') and words, namely phrase ('sort of') and clause (e.g. 'you know'). Some are even combinations of sound(s) and word(s) (e.g. 'and um', 'yes er um', 'sort of erm'). Among the top five frequent linguistic realisations of fillers, 'er' and 'um' are the most common ones found in all the six genres with relatively higher percentages of occurrence. The remaining more frequent realisations consist of clause ('you know'), word ('yeah') and sound ('erm'). These common forms are syntactically simpler than the less frequent realisations found in the genres. The co-occurring patterns of fillers and other speech acts are diverse. The more common co-occurring speech acts with fillers include informing and answering. The findings show that fillers are not only frequently used by speakers in spontaneous conversation but also mostly represented in sounds or non-linguistic realisations.

• Journal of KIISE:Software and Applications
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• v.27 no.7
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• pp.769-783
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• 2000

In this paper, in order to disambiguate Korean noun word sense, we define a local context and explain how to extract it from a raw corpus. Following the intuition that two different nouns are likely to have similar meanings if they occur in the same local context, we use, as a clue, the word that occurs in the same local context where the target noun occurs. This method increases the usability of extracted knowledge and makes it possible to disambiguate the sense of infrequent words. And we can overcome the data sparseness problem by extending the verbs in a local context. The sense of a target noun is decided by the maximum similarity to the clues learned previously. The similarity between two words is computed by their concept distance in the sense hierarchy borrowed from WordNet. By reducing the multiplicity of clues gradually in the process of computing maximum similarity, we can speed up for next time calculation. When a target noun has more than two local contexts, we assign a weight according to the type of each local context to implement the differences according to the strength of semantic restriction of local contexts. As another knowledge source, we get a co-occurrence information from dictionary definitions and example sentences about the target noun. This is used to support local contexts and helps to select the most appropriate sense of the target noun. Through experiments using the proposed method, we discovered that the applicability of local contexts is very high and the co-occurrence information can supplement the local context for the precision. In spite of the high multiplicity of the target nouns used in our experiments, we can achieve higher performance (89.8%) than the supervised methods which use a sense-tagged corpus.

• The Journal of Economics, Marketing and Management
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• v.11 no.3
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• pp.47-66
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• 2023

Purpose: The purpose of this study is to identify research trends related to ESG by domestic and overseas researchers so far, and to present research directions and clues for the possibility of applying ESG to Korean companies in the future and ESG practice through comparison of derived topics. Research design, data and methodology: In this study, as of October 20, 2022, after searching for the keyword 'ESG' in 'scienceON', 341 domestic papers with English abstracts and 1,173 overseas papers were extracted. For analysis, word frequency analysis, word co-occurrence frequency analysis, BERTopic, LDA, and OLS regression analysis were performed to confirm trends for each topic using Python 3.7. Results: As a result of word frequency analysis, It was found that words such as management, company, performance, and value were commonly used in both domestic and overseas papers. In domestic papers, words such as activity and responsibility, and in overseas papers, words such as sustainability, impact, and development were included in the top 20 words. As a result of analyzing the co-occurrence frequency of words, it was confirmed that domestic papers were related mainly to words such as company, management, and activity, and overseas papers were related to words such as investment, sustainability, and performance. As a result of topic modeling, 3 topics such as named ESG from the corporate perspective were derived for domestic papers, and a total of 7 topics such as named sustainable investment for overseas papers were derived. As a result of the annual trend analysis, each topic did not show a relatively increasing or decreasing tendency, confirming that all topics were neutral. Conclusions: The results of this study confirmed that although it is desirable that domestic papers have recently started research on consumers, the subject diversity is lower than that of overseas papers. Therefore, it is suggested that future research needs to approach various topics such as forecasting future risks related to ESG and corporate evaluation methods.

• Journal of the Korean Society for information Management
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• v.24 no.4
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• pp.285-303
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• 2007

This study aims to explore a new technique making complementary linkage between controlled vocabularies and uncontrolled vocabularies for analyzing a research domain. Co-word analysis can be largely divided into two based on the types of vocabulary used: controlled and uncontrolled. In the case of using controlled vocabulary, data sparseness and indexer effect are inherent drawbacks. On the other case, word selection by the author's perspective and word ambiguity. To complement each other, we suggest a descriptor profiling that represents descriptors(controlled vocabulary) as the co-occurrence with words from the text(uncontrolled vocabulary). Applying the profiling to the domain of information science implies that this method can complement each other by reducing the inherent shortcoming of the controlled and uncontrolled vocabulary.