Journal of the Korea Society of Computer and Information
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v.18
no.9
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pp.139-152
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2013
Although a series of studies shows the fact that a company's reputation could affect its sales rate and stock price, due to the increased use of SNS, the research related to the online measurement method for the corporate reputation has been relatively insufficient. This study explores a design for a method to quantify the corporate reputation value by reconstructing the discussions in literature review. Concretely, this study divides the corporate reputation value into the corporate identity information and the corporate awareness information, which includes the following five sub-categories: (1) the quality of product and service; (2) the employment environment; (3) the corporate vision; (4) the social responsibility; and (5) the business achievement. Additionally, for the corporate identity assessment, this study considers the following six factors: (1) Agreeableness (Goodness), (2)Capability (Ability), (3)Enterprise (Rise), (4)Chic (Class), (5) Ruthlessness (Authority), and (6)Informality. Based on these categories and factors, this study develops a technique quantifying the corporate reputation value by selecting 'word items' for the reputation search, and after conducting a frequency analysis in a survey. Also, to verify the result, this study exemplifies the reputation of three SI companies in Korea which could be utilized by using the commercialized reputation service. This study firstly attempts the corporate reputation measurement by classifying the identity and the awareness (corporate image and communication) upon a company in detail and enables its real applicabilities by proposing a formula to measure the reputation scores which can be utilized by verified word items from a frequency analysis.
With the emergence of SNS, TV, newspapers and radio, which are one-way communication media, have become less important. Therefore social networking enables social networking beyond the constraints of time and space, and communication and emotional communication required for social relations have emerged as a factor in the importance of social media. Social media, which is based on rapid connectivity and scalability, is an medium of expression that is advantageous for companies and consumers to communicate more easily than traditional advertising media. Advertising can form a consensus that consumers and companies can create an atmosphere of friendly conversation because of the social media that has the efficiency of communication. This study compares two ads. One is the advertisement of 'Bear and Hare', an animation of John Lewis department store in the UK, where a new form of advertising marketing strategy is fused with emotional storytelling and social media. The second is an advertisement of LG, 'I love you LG' to be. Social media should be remembered as a warm and loving company in the heart of customers through open communication with customers, rather than companies that pursue merit profits by using social media ads as a medium of emotional transmission to consumers. It is a study on useful advertising strategy that can pursue the sales of the company at the same time.
The information that consumers share in the SNS (Social Networking Service) has a great influence on the purchase of consumers. Therefore, it is necessary to pay attention to new research methodology and advertising strategy using Social Big Data. In this context, the purpose of this study is to quantitatively analyze customer value through Social Big Data. In this study, we analyzed the value structure of consumers for the three smartphone brands through text mining and positive/negative image analysis. Analysis result, it was possible to distinguish the emotional aspects (sensitivity) and rational aspects (rationality) for customer value per brand. In the case of the Galaxy S7 and iPhone 6S, emotional aspects were important before the launch, but the rational aspects was important after release date. On the other hand, in the case of the LG G5, emotional aspects were important before and after launch. We can propose two core advertising strategies based on analyzed consumer value. When developing advertising strategy in the case of the Galaxy S7, there is a need to emphasize the rational aspects of product attributes and differentiated functions. In the case of the LG G5, it is necessary to consider the emotional aspects of happiness, excitement, pleasure, and fun that are felt by using products in advertising strategy. As a result, this study will provide a good standard for actual advertising strategy through consumer value analysis. Advertising strategies are primarily driven by intuition or experience. Therefore, it is important to develop advertising strategies by analyzing consumer value through social big data analysis.
Due to the development of digital appliance, role of TV causes both-way by introducing IPTV, and SNS service causes big change of watching environment and residence environment. There are good conditions on the role of integrated control because it is arranged in the living room which secures movement most effectively and because family members can easily use, and the degree of use is high. Therefore, we infer user's needs by analyzing user scenario and current role of TV in home network environment. Primarily, we collect surveys of development scenario and technology which companies suggest TV applied by home network service, and secondly, we comparatively study scenario which the companies mentioned above suggest through observing user scenario, and study the role of IPTV in the future through actual scenario-based experiment by ethnography. After analyzing user scenario through case study and experiment, there are integrated device studies mainly in company study because it can be made up inside home, security and entertainment. On the other hand, there are patterns of user behavior by scenario experiment mainly in auto-tainment, security, and it showed that it is insufficient for interaction between TV and home media peripheral. Through this paper, we analyze context of home user, and based on this, we could suggest effective use of service development. Also after analyzing user form, we could know it also should be considered of ratio between activity inside home and activity outside home.
Following the recent advancement in the use of social networks, a vast amount of different online reviews is created. These variable online reviews which provide feedback data of contents' are being used as sources of valuable information to both contents' users and providers. With the increasing importance of online reviews, studies on opinion mining which analyzes online reviews to extract opinions or evaluations, attitudes and emotions of the writer have been on the increase. However, previous sentiment analysis techniques of opinion-mining focus only on the classification of reviews into positive or negative classes but does not include detailed information analysis of the user's satisfaction or sentiment grounds. Also, previous designs of the sentiment analysis technique only applied to one content domain that is, either product or movie, and could not be applied to other contents from a different domain. This paper suggests a sentiment analysis technique that can analyze detailed satisfaction of online reviews and extract detailed information of the satisfaction level. The proposed technique can analyze not only one domain of contents but also a variety of contents that are not from the same domain. In addition, we design a system based on Hadoop to process vast amounts of data quickly and efficiently. Through our proposed system, both users and contents' providers will be able to receive feedback information more clearly and in detail. Consequently, potential users who will use the content can make effective decisions and contents' providers can quickly apply the users' responses when developing marketing strategy as opposed to the old methods of using surveys. Moreover, the system is expected to be used practically in various fields that require user comments.
This paper examines the rising value of social networked journalism and analyzes the case of a social news site based on the theory of networked journalism. Social networked journalism allows the public to be involved in every aspect of journalism production through crowd-sourcing and interactivity. The networking effect with the public is driving journalism to transform into a more open, more networked and more responsive venue. "wikitree" is a social networking news service on which anybody can write news and disseminate it via Facebook and Twitter. It is operated as an open sourced program which incorporates "Google Translate" to automatically convert all its content, enabling any global citizen with an Internet access to contribute news production and share either their own creative contents or generated contents from other sources. Since its inception, "wikitree global" site has been expanding its coverage rapidly with access points arising from 160 countries. Analyzing its international coverage by country and by news category as well as by the unique visit numbers via SNS, the results of the case study imply that networking with the global public can enhance news traffic to the social news site as well as to specific news items. The results also suggest that the utilization of Twitter and Facebook in social networked journalism can break the boundary between local and global public by extending news-gathering ability while growing audience's interest in the site, and engender a feasible business model for a local online journalism.
The Journal of Korean Institute of Communications and Information Sciences
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v.38B
no.5
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pp.385-393
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2013
In the past decade, a paradigm shift from machine-centered to human-centered and from technology-driven to user-driven has been witnessed. Consequently, Social search is getting more social and Social Network Service (SNS) is a popular Web service to connect and/or find friends, and the tendency of users interests often affects his/her who have similar interests. If we can track users' preferences in certain boundaries in terms of Web search and/or knowledge sharing, we can find more relevant information for users. In this paper, we propose a novel Topic Sensitive_Social Relationship Rank (TS_SRR) algorithm. We propose enhanced Web searching idea by finding similar and credible users in a Social Network incorporating social information in Web search. The Social Relation Rank between users are Social Relation Value, that is, for a different topics, a different subset of the above attributes is used to measure the Social Relation Rank. We observe that a user has a certain common interest with his/her credible friends in a Social Network, then focus on the problem of identifying users who have similar interests and high credibility, and sharing their search experiences. Thus, the proposed algorithm can make social search improve one step forward.
The social media data and the broadcasting data related to onion as well as agri-food consumer panel data were collected and investigated if the amount of money spent to purchase onion in year 2014 when onion price plunged latest were correlated with the frequencies of onion-related keywords in the social media data and the broadcasting programs because onion price in year 2018 is expected to plunge due to overproduction and there has been needs to analyze impacts of social media and broadcasting program on onion purchase in the previous similar events, and identify potential factors that can promote onion consumption in advance. What we identified from our study include a) broadcasting news programs mentioning words "onion," were correlated with onion purchase with 3 - 6 weeks in advance; b) broadcasting entertainment programs mentioning words "onion and health," were correlated with onion purchase with 11 weeks in advance; c) blog mentioning words "onion and efficacy," were correlated with onion purchase with 5 weeks in advance. Our study provided a case on how social media and broadcasting programs could be analyzed for their effects on consumer purchase behavior using big data collection and analysis in the field of agriculture. We propose to use the findings from the study may be applied to promote onion consumption.
The Journal of Korea Institute of Information, Electronics, and Communication Technology
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v.14
no.3
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pp.193-200
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2021
Recently, posts and opinions on tourist attractions are actively shared on social media. These social big data provide meaningful information to identify objective images of tourist destinations recognized by consumers. Therefore, an in-depth understanding of the tourist image is possible by analyzing these big data on tourism. The study is to analyze destination images in Gangwon-do using big data from social media. It is wanted to understand destination images in Gangwon-do using semantic network analysis and then provided suggestions on how to enhance image to secure differentiated competitiveness as a destination for tourists. According to the frequency analysis results, as tourism in Gangwon-do, Sokcho, Gangneung, and Yangyang were mentioned at a high level in that order, and the purpose of travel was restaurant tour, gourmet food, family trip, vacation, and experience. In particular, it was found that they preferred day trips, weekends, and experiences. Four suggestions were made based on the results. First, it is necessary to develop various types of hotels, accommodation facilities and experience-oriented tour packages. Second, it is necessary to develop a day-to-day travel package that utilizes proximity to the Seoul metropolitan area. Third, it is necessary to promote traditional restaurants and local food. Finally, it is necessary to develop tourist package suitable for healing and family travel. Through this research, the destination image of Gangwon-do was identified and a tourism marketing strategy was presented to improve competitiveness. It also provided a theoretical basis for the use of the big data of tourism consumers in the field of tourism business.
As more people share their opinions in online communities, such as Internet portals and social networking services, more opinions are manipulated for the benefit of particular individuals and groups. In particular, when manipulations occur for political purposes, they influence election results as well as government policies and the quality of life. This type of manipulation has targeted the general public, and their analysis and detection has also focused on such manipulation. However, to more efficiently spread propaganda, recent manipulations have targeted common interest groups(e.g., a group of those interested in real estate) and propagated information whose content and style are customized to those groups. This work characterizes such manipulations on common interest groups and proposes method to detect manipulations. To this end, we collected and analyzed opinions posted on 10 common interest groups before and after an election. As a result, we found that manipulations on common interest groups indeed occurred and were gradually increasing toward the election date. We also proposed a detection system that examines individual opinions, their authors, and their collaborators. Using the collected opinions, we demonstrated that the proposed system can accurately classify more than 90% of manipulated opinions and that many of these opinions were posted by multiple collaborators. We believe that regular audits of opinions using the proposed system can quickly isolate manipulations and decrease their impact. Moreover, the proposed features can be used to identify manipulations in domains other than politics.
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