• International journal of advanced smart convergence
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• v.12 no.4
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• pp.353-360
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• 2023

This paper explores notable shifts in the restaurant startup market following the lifting of social distancing measures. Key trends identified include an escalated interest in startups, a heightened focus on the quality and diversity of food, a relative decline in the importance of delivery services, and a growing interest in specific industry sectors. The study's data collection spanned three years, from April 2021 to May 2023, encompassing the period before and after social distancing. Data were sourced from a range of online platforms, including blogs, news sites, cafes, web documents, and intellectual forums, provided by Naver, Daum, and Google. From this collected data, the top 50 words were identified through a refinement process. The analysis was structured around the social distancing application period, comparing data from April 2021 to April 2022 with data from May 2022 to May 2023. These observed trend changes provide founders with valuable insights to seize new market opportunities and formulate effective startup strategies. In summary, We offer crucial insights for founders, enabling them to comprehend the evolving dynamics in food service startups and to adapt their strategies to the current market environment.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.133-146
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• 2013

While the use of internet is routine nowadays, users receive and share information through a variety of media. Through the use of internet, information delivery media is diversifying from traditional media of one-way communication, such as newspaper, TV, and radio, into media of two-way communication. In contrast of traditional media, blogs enable individuals to directly upload and share news, which can be considered to have a differential speed of information diffusion than news media that convey information unilaterally. Therefore this Study focused on the difference between online news and social media blogs. Moreover, there are variations in the speed of information diffusion because that information closely related to one person boosts communications between individuals. We believe that users' standard of evaluation would change based on the types of information. As well, the speed of information diffusion would change based on the level of proximity. Therefore, the purpose of this study is to examine the differences in information diffusion based on the types of media. And then information is segmentalized and an examination is done to see how information diffusion differentiates based on the types of information. This study used the Bass diffusion model, which has been frequently used because this model has higher explanatory power than other models by explaining diffusion of market through innovation effect and imitation effect. Also this model has been applied a lot in other information diffusion related studies. The Bass diffusion model includes an innovation effect and an imitation effect. Innovation effect measures the early-stage impact, while the imitation effect measures the impact of word of mouth at the later stage. According to Mahajan et al. (2000), Innovation effect is emphasized by usefulness and ease-of-use, as well Imitation effect is emphasized by subjective norm and word-of-mouth. Also, according to Lee et al. (2011), Innovation effect is emphasized by mass communication. According to Moore and Benbasat (1996), Innovation effect is emphasized by relative advantage. Because Imitation effect is adopted by within-group influences and Innovation effects is adopted by product's or service's innovation. Therefore, ours study compared online news and social media blogs to examine the differences between media. We also choose different types of information including entertainment related information "Psy Gentelman", Current affair news "Earthquake in Sichuan, China", and product related information "Galaxy S4" in order to examine the variations on information diffusion. We considered that users' information proximity alters based on the types of information. Hence, we chose the three types of information mentioned above, which have different level of proximity from users' standpoint, in order to examine the flow of information diffusion. The first conclusion of this study is that different media has similar effect on information diffusion, even the types of media of information provider are different. Information diffusion has only been distinguished by a disparity between proximity of information. Second, information diffusions differ based on types of information. From the standpoint of users, product and entertainment related information has high imitation effect because of word of mouth. On the other hand, imitation effect dominates innovation effect on Current affair news. From the results of this study, the flow changes of information diffusion is examined and be applied to practical use. This study has some limitations, and those limitations would be able to provide opportunities and suggestions for future research. Presenting the difference of Information diffusion according to media and proximity has difficulties for generalization of theory due to small sample size. Therefore, if further studies adopt to a request for an increase of sample size and media diversity, difference of the information diffusion according to media type and information proximity could be understood more detailed.

• The Journal of Society for e-Business Studies
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• v.13 no.3
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• pp.21-49
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• 2008

The area of the internet shopping mall heavily relies on new emerging information technologies, and it essentially requires delicate marketing model to support consumer behavior. RSS, which is one of the representative Web 2.0 technologies, is the system that distributes digital contents without any Web browser. RSS is expected not only to be very useful in online marketing but also to become actively applied on various areas such as online newspapers and blogs. AISAS model was proposed to complement the AIDMA model that did not cover the new changing customer behaviors of online commerce environment such as search and share. In this research, we propose a marketing model which utilizes RSS based on the AISAS model to support internet shopping malls. With our marketing model, internet shopping malls are expected to provide required services to the customers at every AISAS step. Moreover, it can provide integrated services by connecting all service components of each step. We utilized RSS in our model to implement those services because RSS has many advantages on supporting search and share of product information.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.9
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• pp.1898-1904
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• 2009

Recently, real documents such as newspapers as well as blogs include newly coined words such as "Wikipedia". However, most previous information processing technologies cannot deal with these newly coined words because they construct their dictionaries based on materials acquired during system development. In this paper, we propose a model to automatically recognize Korean unknown words excluded from the previously constructed dictionary. The proposed model consists of an unknown noun recognition phase based on full text analysis, an unknown verb recognition phase based on web document frequency, and an unknown noun recognition phase based on web document frequency. The proposed model can recognize accurately the unknown words occurred once and again in a document by the full text analysis. Also, the proposed model can recognize broadly the unknown words occurred once in the document by using web documents. Besides, the proposed model fan recognize both a Korean unknown verb, which syllables can be changed from its base form by inflection, and a Korean unknown noun, which syllables are not changed in any eojeol. Experimental results shows that the proposed model improves precision 1.01% and recall 8.50% as compared with a previous model.

• Journal of Digital Convergence
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• v.12 no.1
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• pp.51-60
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• 2014

Modern society is rapidly changing by the Internet, and it is getting influential on the field of education. Learners can learn what they want to learn actively and freely at their desired level at anywhere in their free time by using the internet. The purpose of this study, therefore, is to find out the methods for improving writing ability through e-learning. The results of the study are as follows: First, learners can attend a lecture to improve their writing ability and can get learning materials from on-line course sites, internet websites, communities and blogs. Second, e-learning is learner-centered education, so it stimulates learners learning motivation and interest. Third, learners have an opportunity to express their ideas freely, and they can gain cultural comprehension while they communicate with people in the world by e-mail and chatting.

• The Journal of the Korea Contents Association
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• v.20 no.3
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• pp.515-526
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• 2020

Digital healthcare is a combined area of medical field and IT and various information on digital healthcare is provided in social media. This study aims to find the research trend of digital healthcare by collecting and analyzing data related to digital healthcare through the social media. The data were collected from Naver and Daum's news and blogs from January 2008 to June 2019. Major keywords with high frequency were extracted and visualized with wordcloud and network analysis was used to analyze the relationship between major keywords. Research combining medical field and IT from 2008 to 2001, various convergence research based on medical field and IT from 2012 to 2015, convergence research that applied the 4th industrial revolution technologies such as big data, blockchain and AI were actively conducted from 2016 to June 2019.

• The Research Journal of the Costume Culture
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• v.28 no.2
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• pp.265-284
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• 2020

This study aimed to analyze the performance of Disney-collaborated fashion lines based on online consumer reviews. To do so, the researchers employed text mining and network analysis to identify key words in the reviews of these products. Blogs, internet cafes, and web documents provided by Naver, Daum, and YoutTube were selected as subjects for the analysis. The analysis period was limited to one year after for the 2019. Data collection and analysis were conducted using Python 3.7, Textom, and NodeXL. The research terms in question were as follows: 'Disney fashion collaboration' and 'Frozen fashion collaboration'. Preliminary survey results indicated that 'Elsa's dress' was the most frequently mentioned term and that the domestic fashion brand Eland Retail was the most active in selling Disney branded clothing through its own brand. The writers of reviews for Disney-collaborated fashion products were primarily mothers with daughters. Their decision to purchase these products was based upon the following factors; price, size, stability of decoration, shipping, laundry, and retailer. The motives for purchasing the product were the positive response of the consumer's child and the satisfaction of the parents due to the child's response. The problems to be solved included insufficient quantity of supply, delay in delivery, expensive price considering the number of times children's clothes are worn, poor glitter decoration, faded color, contamination from laundry, and undesirable smells immediately after the purchase.

• Journal of Digital Convergence
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• v.14 no.10
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• pp.241-252
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• 2016

The purpose of this study is to explain the word-of-mouth communication that evolve differently from traditional marketing communications using existing mass media in an environment of the flooding of new products. In particular, people use digital devices as internet users and various communication is activated in blogs and communities. It is expanding that companies use market maven as a facilitator of communication. The role of Market maven due to the spread of the Internet seems to be more meaningful for marketing activities. Market maven is a look at how it should study moderate effect on word of mouth of new products. Empirical results show that perceived curiosity and perceived innovativeness of new product has a positive impact on the word of mouth of new product, and was confirmed in a moderate effect of market maven.

• Journal of the Korean Society for Marine Environment & Energy
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• v.20 no.2
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• pp.117-125
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• 2017

SNS Big-data Analysis means to find potential value from big data which has produced by the social media. In this paper, SNS Big-data has been analysed to find Korean concerns by using 24 key words from the marine and fisheries sector. Among 24 key words, seafood, shipping and Dokdo Island are the most mentioned ones. Some key words such as ocean policies and marine security that have less concerns have bess mentioned less. Also, key words that are led by government are mostly mentioned by news media, but key words that are led by private sector and have intimate relationship with people's lives are mostly mentioned by Blogs and Twitters. Therefore, reflecting close national concerns by SNS Big-data Analysis and especially resolving negative factors are the most significant part of the policy establishment. Also, differentiated promotion methods need to be prepared because the frequency of key words mentioned from each type of media are different.

• Fashion & Textile Research Journal
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• v.20 no.5
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• pp.533-547
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• 2018

The objective of this study is to examine the perception of golfwear and related trends based on major keywords and associated words related to golfwear utilizing big data. For this study, the data was collected from blogs, Jisikin and Tips, news articles, and web $caf{\acute{e}}$ from two of the most commonly used search engines (Naver & Daum) containing the keywords, 'Golfwear' and 'Golf clothes'. For data collection, frequency and matrix data were extracted through Textom, from January 1, 2016 to December 31, 2017. From the matrix created by Textom, Degree centrality, Closeness centrality, Betweenness centrality, and Eigenvector centrality were calculated and analyzed by utilizing Netminer 4.0. As a result of analysis, it was found that the keyword 'brand' showed the highest rank in web visibility followed by 'woman', 'size', 'man', 'fashion', 'sports', 'price', 'store', 'discount', 'equipment' in the top 10 frequency rankings. For centrality calculations, only the top 30 keywords were included because the density was extremely high due to high frequency of the co-occurring keywords. The results of centrality calculations showed that the keywords on top of the rankings were similar to the frequency of the raw data. When the frequency was adjusted by subtracting 100 and 500 words, it showed different results as the low-ranking keywords such as J. Lindberg in the frequency analysis ranked high along with changes in the rankings of all centrality calculations. Such findings of this study will provide basis for marketing strategies and ways to increase awareness and web visibility for Golfwear brands.