• Journal of Information Technology Services
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• v.11 no.3
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• pp.103-127
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• 2012

With the advent of SNS (Social Network Services), the product reviews by friends in SNS are intensively utilized for online marketing. However, there is a lack of empirical evidence on the actual marketing effect of SNS reviews, although we need to identify who can be the target of SNS marketing in terms of customer attributes, preferences, or experiences. In this study, we investigate the moderating role of customer attributes in identifying the effect of SNS reviews on customer purchasing decision. As the moderating variables, we adopt 'information search experience' and 'perception of information overload'. Research results evidence that, in order to understand the effect of SNS reviews in a comprehensive manner, we need to examine it in the context of various related factors such as 'information search experience' and 'perception of information overload'. The results show that the persuading effect of SNS reviews for product purchasing is stronger for the customers with the lower information search experiences as well as the lower perception on the information overload on the web. This result delivers managerial implications on who can be the target customers of SNS marketing.

• The Journal of the Korea Contents Association
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• v.19 no.8
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• pp.58-68
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• 2019

Recently SNS product reviews are excessively increasing. However, many SNS reviews are under feeble regulation than how big and powerful that their awarenesses are. This problem leads to consumers' discontentment on product reviews on online. This study aims to analyze how SNS product reviews characteristics: informativeness, entertainment, reliability and familiarity attribute on consumers' purchase intent and brand attitude. However, at this time, consumers' high discontents (stored-knowledge) expect to have negative affect on product reviews thus I put this as a regulation effect. This study is consisted of 240 examinee who check SNS product reviews before buying products.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.268-272
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• 2023

With the development of SNS, companies and individuals are actively marketing through social media to develop their own products. It is also important to post posts promoting on simple SNS or to show a lot of exposure using algorithms, but customers upload reviews or proof shots of the product on their own, naturally increasing the exposure of the product and increasing the purchasing power of potential customers. As the number of products that users want to purchase through SNS is increasing, they want to access and purchase not only tangible products such as goods and food, but also intangible services through SNS. In this paper, we would like to study exhibitions that have both tangible and intangible characteristics. SNS accounts that mainly introduce these products by searching for reviews have been created while spending leisure time such as exhibitions and fairs, reducing the hassle of searching for personal interests on search engines, and providing prices and reviews from the exhibition's schedule, lowering entry barriers and increasing purchasing power. Using this point, many exhibitions not only display works, but also open various experience centers, and create a photo zone or a unique exhibition hall atmosphere to attract many customers. In this study, we study the impact of SNS on the leisure culture of exhibition. The marketing direction in the situation where SNS marketing is becoming the mainstream is presented, and the change in the form of exhibition is described and presented as an academic approach.

• Knowledge Management Research
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• v.15 no.4
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• pp.171-187
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• 2014

The social network services (SNS) like Facebook, have gained an enormous amount of popularity. However, side-effects of Facebook usage are occasionally reported such as sense of alienation and cyber-bullying. Among these potential factors threatening to the success of SNS, this research focused on alienation and intends to investigate possible factors that affect SNS alienation and how it affects on SNS attachment and proactive use of SNS. Through extensive literature reviews regarding online and offline alienation, SNS characteristics, and SNS usage, we generated the research model and hypotheses. We surveyed 142 Facebook users and empirically proved that among SNS characteristics, complexity increases SNS alienation, and interactivity and social presence positively affect SNS attachment. Offline alienation, one of the personal attributes, increases both SNS alienation and SNS attachment at the same time while the number of SNS friends have no significant effects. In addition, SNS alienation decreases proactive use of Facebook while SNS attachment increases it. Theoretical and practical implications are discussed based on research findings, and we also suggest future research directions to minimize negative consequences due to SNS users' sense of alienation.

• Journal of Satellite, Information and Communications
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• v.10 no.1
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• pp.33-43
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• 2015

This study, by using SNS, is to find ways to improve the recognition of the audience on creative musical for performance planning and marketing after looking into how the choice attributes of creative musical has the different impact on satisfaction. As a result, the audiences who use SNS show that the composition of content(1st ranking), main actors(2nd ranking), reviews on musical(3rd raking), and production(4th ranking) have the impact on their satisfaction but the stage composition, staff service, satisfaction on theater, and admission fee haven't. For those who don't use SNS, however, the composition of content(1st ranking), reviews on musical(2nd ranking), production(3rd raking), and main actors(4th ranking) affect the satisfaction while the staff service, stage composition, admission fee, satisfaction on theater hardly make any effect on it.

• Journal of the Korea Convergence Society
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• v.11 no.8
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• pp.165-171
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• 2020

Most of the stock price prediction research using text mining uses news and SNS data. However, there is a weakness that it is difficult to get honest and vivid information about companies from them. This paper deals with the problem of the prediction for the direction of stock price by doing text mining the online company reviews of internal staff indicating employee satisfaction. The comparative analysis of the prediction models for the direction of stock price showed the prediction model, which adds internal employee reviews, has better performance than those that did not. This paper presents the convergence study using natural language processing in financial engineering. In the field of stock price prediction, This paper pursued a new methodology that used employee satisfaction. In practice, it is expected to provide useful information in the field of forecasting stock price direction.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.1-6
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• 2023

Text mining (TM) is most widely used to process the various unstructured text documents and process the data present in the various domains. The other name for text mining is text classification. This domain is most popular in many domains such as movie reviews, product reviews on various E-commerce websites, sentiment analysis, topic modeling and cyber bullying on social media messages. Cyber-bullying is the type of abusing someone with the insulting language. Personal abusing, sexual harassment, other types of abusing come under cyber-bullying. Several existing systems are developed to detect the bullying words based on their situation in the social networking sites (SNS). SNS becomes platform for bully someone. In this paper, An Enhanced text mining approach is developed by using Ensemble Algorithm (ETMA) to solve several problems in traditional algorithms and improve the accuracy, processing time and quality of the result. ETMA is the algorithm used to analyze the bullying text within the social networking sites (SNS) such as facebook, twitter etc. The ETMA is applied on synthetic dataset collected from various data a source which consists of 5k messages belongs to bullying and non-bullying. The performance is analyzed by showing Precision, Recall, F1-Score and Accuracy.

• The KIPS Transactions:PartC
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• v.18C no.4
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• pp.217-226
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• 2011

As a diverse range of smartphones has been recently developed and diffused, the users of SNS (Social Network Service) also have been sharply increased. The SNS saves a variety of information such as exchanged pictures and videos, voice mails or location sharing, chat history, etc. as well as simple user data, so that the acquisition of data that are useful in the aspect of digital forensic is achievable. This thesis reviews the types of SNS that are available for the iPhone, a recent example of highly used smartphones, and types of data by each client. Also, efficient data analysis method for digital forensic investigations is suggested by analyzing the relationships within the collected data by each client.

• Management & Information Systems Review
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• v.30 no.3
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• pp.85-105
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• 2011

The primary purpose of this study is to examine the effects of privacy concern on user's satisfaction and continuance intention in SNS. Based on relevant literature reviews, this study posits five characteristics, that is, privacy concern, perceived usefulness, perceived enjoyment, satisfaction, and continuance intention as key factors. And then we structured a research model and hypotheses about relationship between these variables. A total 298 usable survey responses of SNS users have been employed in the analysis. The major findings from the data analyses are as follows. Firstly, privacy concern had a significant influence upon perceived usefulness and enjoyment, however, privacy concern had not a significant influence upon satisfaction Secondly, perceived usefulness and enjoyment had a positive influence upon satisfaction. Lastly, user's perceived usefulness, perceived enjoyment, and satisfaction had significantly related to continuance intention in SNS. From this study, we expect to suggest practical and managerial implications to SNS providers.

• Journal of the Korea Society of Computer and Information
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• v.25 no.10
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• pp.87-94
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• 2020

Social reviews such as SNS feeds and blog articles have been widely used to extract keywords reflecting opinions and complaints from users' perspective, and often include proper nouns or new words reflecting recent trends. In general, these words are not included in a dictionary, so conventional morphological analyzers may not detect and extract those words from the reviews properly. In addition, due to their high processing time, it is inadequate to provide analysis results in a timely manner. This paper presents a method for efficient keyword extraction from social reviews based on the notion of cohesion scoring. Cohesion scores can be calculated based on word frequencies, so keyword extraction can be performed without a dictionary when using it. On the other hand, their accuracy can be degraded when input data with poor spacing is given. Regarding this, an algorithm is presented which improves the existing cohesion scoring mechanism using the structure of a word tree. Our experiment results show that it took only 0.008 seconds to extract keywords from 1,000 reviews in the proposed method while resulting in 15.5% error ratio which is better than the existing morphological analyzers.