• The Journal of Information Systems
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• v.30 no.4
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• pp.1-20
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• 2021

Purpose Nowadays, Autonomous Sensory Meridian Response (ASMR) is rapidly growing in popularity and increasingly appearing in marketing. Not even in TV commercial advertisement, ASMR also fast growing in one-person media communication, many brands and social media influencers used ASMR for their marketing contents. The purpose of this study is to measure consumers' perceptions about the products in ASMR marketing content and compare the differences in communication effect of ASMR content creator between product review and how-to in the same Macro tier influencer - the YouTuber that has 10,000-100,000 subscribers. Design/methodology/approach The research methods selected ASMRtist that do product review content and how-to content, Text comments data was collected from 200 videos of tech-device review videos and beauty-fashion videos. A total of 52,833 text comments were analyzed by applying the LDA topic modeling algorithm and social network analysis. Findings Through the result, we can know that ASMR is good at taking attention of viewers with ASMR triggers. In the Tech device reviews field, ASMR viewers also focus on the product like product's performance and purchase. However, there are many topics related to reaction of ASMR sound, trigger, relaxation. In the Beauty-fashion field, viewers' topics mainly focus on the reaction of the ASMR trigger, response to ASMRtist and other topics are talking about makeup - fashion, product, purchase. From LDA result, many ASMR viewers comment that they feel more comfortable when watching the marketing content that uses ASMR. This result has shown that ASMR marketing contents have a good performance in terms of user watching experience, so applying ASMR can take more consumer intention. And the result of social network analysis showed that product review ASMRtist have a higher communication effectiveness than how-to ASMRtist in the same tier. As an influencer marketing strategy, this study provides information to establish an efficient advertising strategy by using influencers that create ASMR content.

• Journal of Information Technology Services
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• v.19 no.4
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• pp.1-11
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• 2020

Through text mining, sentiment analysis, and semiotics analysis, this study aims to reinterpret the meaning of user emotional words and related words to derive strategic elements of brand and design. After selecting a local car manufacturer whose user opinion on the brand is a clear topic, web-crawl the car comments of the manufacturer directly created by the users online. Then, analyze the extracted morphology and its associated words and convert them to fit the marketing mix theory. Through this process, propose a methodology that allows consumers to supplement and improve brand elements with negative sensibilities, and to inherit elements with positive sensibilities and manage brands reasonably. In particular, the Map presented in this study are considered to be fully utilized as information for overall brand management.

• Journal of Communications and Networks
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• v.17 no.3
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• pp.265-266
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• 2015

In a recent paper [1], the authors investigated the maximum stable throughput region of a network composed of a rechargeable primary user and a secondary user plugged to a reliable power supply. The authors studied the cases of an infinite and a finite energy queue at the primary transmitter. However, the results of the finite case are incorrect. We show that under the proposed energy queue model (a decoupled M/D/1 queueing system with Bernoulli arrivals and the consumption of one energy packet per time slot), the energy queue capacity does not affect the stability region of the network.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.3
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• pp.1-10
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• 2012

Recently, Social Network services(SNS) is gaining popularity as Facebook and Twitter. Popularity of SNS leads to active service and social data is to be increased. Thus, social search is remarkable that provide more meaningful information to users. but previous studies using social network structure, network distance is calculated using only familiarity. It is familiar as distance on network, has been demonstrated through several experiments. If taking advantage of social context data that users are using SNS to produce, then familiarity will be helpful to evaluate further. In this paper, reflect user's attention through comments and tags, Facebook context is determined using familiarity between friends in SNS. Facebook context is advantageous finding a friend who has a similar propensity users in context of profiles and interests. As a result, we provide a blog post that interest with a close friend. We also assist in the retrieval facilities using Near Field Communication(NFC) technology. By the experiment, we show the proposed soicial search method is more effective than only tag.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.101-109
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• 2023

This paper discusses the use of sentiment analysis and text summarization techniques to extract valuable information from the large volume of user-generated content such as reviews, comments, and feedback on online platforms and social media. The paper highlights the effectiveness of sentiment analysis in identifying positive and negative reviews and the importance of summarizing such text to facilitate comprehension and convey essential findings to readers. The proposed work focuses on summarizing all positive and negative reviews to enhance product quality, and the performance of the generated summaries is measured using ROUGE scores. The results show promising outcomes for the developed methods in summarizing user-generated content.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.238-246
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• 2021

The rapid rise of the Internet and social media has resulted in a large number of text-based reviews being placed on sites such as social media. In the age of social media, utilizing machine learning technologies to analyze the emotional context of comments aids in the understanding of QoS for any product or service. The classification and analysis of user reviews aids in the improvement of QoS. (Quality of Services). Machine Learning algorithms have evolved into a powerful tool for analyzing user sentiment. Unlike traditional categorization models, which are based on a set of rules. In sentiment categorization, Bidirectional Long Short-Term Memory (BiLSTM) has shown significant results, and Convolution Neural Network (CNN) has shown promising results. Using convolutions and pooling layers, CNN can successfully extract local information. BiLSTM uses dual LSTM orientations to increase the amount of background knowledge available to deep learning models. The suggested hybrid model combines the benefits of these two deep learning-based algorithms. The data source for analysis and classification was user reviews of Indian Railway Services on Twitter. The suggested hybrid model uses the Keras Embedding technique as an input source. The suggested model takes in data and generates lower-dimensional characteristics that result in a categorization result. The suggested hybrid model's performance was compared using Keras and Word2Vec, and the proposed model showed a significant improvement in response with an accuracy of 95.19 percent.

• Journal of Distribution Science
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• v.13 no.8
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• pp.73-80
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• 2015

Purpose - This study's objective is to analyze the content of the communications between users and producers based on the construal level theory. User generated content refers to content created in an online-based service where users and producers communicate interactively with each other. In a user generated content platform, the messages sent and received between the many players, the users and producers who use the content, may be analyzed at the psychological level based on construal level theory. Research design, data, and methodology - This study gathered user and producer participation through a snow-bowling sampling method. The data analyzed includes 125 video clips and 2,912 comments. The period of the data collection was from September 2014 to December 2014. The collected data was analyzed using a t-test and two-way ANOVA. Results - This study obtained the following research results. First, users who were a short social distance from producers responded to user participatory activities stated in concrete language rather than abstract language. In contrast, users who were at a longer social distance from producers tended to respond to the content requesting user participation through abstract language. Second, if users and producers were at a short social distance from each other, user preference increased more when a producer response to user participation was expressed concretely rather than when it was expressed abstractly. In contrast, if the users were at a longer social distance, users' preferences increased more when producer response was expressed abstractly rather than when it was expressed concretely. Conclusion - This study found that the effect of suitability, in which the social distance and the content were in congruence at the construal level, could be observed. Therefore, based on this, academic and practical implications were drawn. The three main insights of the study are as follows. First, firms can use psychological factors to analyze the message content of users in their distribution platforms. This study reveals managerial implications for marketing managers who want to take make use of this analysis of user and producer communications. This study indicates that the main factors include the concrete and abstract scores and social distance between users and producers. Second, we also provide the strategic guidelines to maximizing user preferences and other outcomes. The main dependent variable in this study is the user preference shift; the variable increases through the congruence effect; and the construal level is determined by the social distance between the users and producers and the type of producer response. The outcomes here from users can be utilized to develop several systemic strategies. One process to use the outcomes could be: (1) firms could measure the users and producers social distance; (2) calculate the concreteness or abstractness of the messages; and, (3) predict the user preference outcomes by the congruence between user and producer social distance and the abstractness or concreteness of the message content.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.3
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• pp.1795-1805
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• 2015

This paper analyzed the recommendation stories in the online journalism on the user's news choice by college students in two ways. One way is recommendation stories, and the other one is their arrangement and the index of use. From the results of the analysis, 7 out of 11 types of recommendation stories had positive effects on selecting news stories, while the 4 other types had little effect. Most of the recommendation stories that had little effect on the user's news selection were 'comments' or 'things' related to tweets' on SNS. The arrangements of new stories and the searched keywords had some effects on the user's news choice but had no effect on the index of use. In addition, the hours of using news stories and the types of recommendation stories were mostly correlated with each other. Consequently, formal factors, such as the arrangement of news stories and the recommendation stories of online journalism, had positive effects on the user's news selection, as well as headlines and keywords of news stories.

• Journal of the Korean Society for Library and Information Science
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• v.23
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• pp.127-163
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• 1992

The proper evaluation of reference services requires qualitative approach as well as quantitative one. The quality of a reference service can be evaluated by how promptly and accurately a librarian responds to the user's questions and also by how much the user is satisfied with the librarian's overall performance in providing the answer. In this study, the reference service of an university library was evaluated by the following procedure : 1. Identification of a group of the most frequently referred Korean government publications through two pre-tests of user surveys. 2. Preparation of 130 questions of bibliographic and factual type from the above publications. 3. Selection of 30 questions which can be answered from the collection of the evaluated library. 4. Mimic requests of reference service by 5 proxies trained on the unobtrusive test method with 30 questions asked at various times of the day and on various days of the week during a period of 5 months. 5. Drawing up of response sheets (by proxies) with descriptive comments on library staffs' question administration, response, attitude, etc. 6. Preparation and coding of data tabulation sheets and final analysis. The conclusions of this study are as follows : 1. The user serveys showed that needs for the library service for government publications were great. The $80\%$ of the government publications users were visiting more than two organizations for access to information and the $37\%$ were getting information directly from the publishers. 2. The librarians of the evaluated library could give correct answers to $53\%$ of 30 (bibliographic and factual) guestions. 3. The correctness of answer was independent of the length of the time spent the librarians. The librarians' grasp of the questions and direction of approach determined the success or failure of the service. 4. The librarians relied too much on the reference library catalog which doesn't include many of the government publications of their own collection. 5. The $79\%$ of the failure of the service were due to the librarians' lack of knowledge as to the information source for government publications and the unsystematic method of approach to it.

• Journal of the Korea Society of Computer and Information
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• v.26 no.8
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• pp.221-227
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• 2021

Since there are almost no scales for measuring the size of We-Chat applets, and most of the existing We-Chat applets are grafted through the original APP application, At present, the application scope of We-chat applets which is mainly in /shopping/life/food application. Thus, the purpose of this research is to focus on the iPhone app store, collect data on the top five of APP-STORE through users' comments and The high-frequency words will be obtained for statistics, and the variables of this study will be set up. Last, develop relevant Empirical research on the size and measurement scale of the We-Chat applet. Therefore, how to use We-Chat applets to improve user experience, we can create their own user private domain traffic for We-Chat applets and achieve long-term market competitiveness.