• Annual Conference of KIPS
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• 2014.11a
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• pp.928-931
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• 2014

The detection of human behavior from social media revolutionized health, business, criminal and political prediction. Significance of it, in incentive transformation of public opinion had already proven for developed countries in improving democratic process of elections. In $3^{rd}$ World countries, voters poll votes for personal interests being unaware of party manifesto or national interest. These issues can be addressed by social media, resulting as ongoing process of improvement for presently adopted electoral procedures. On the optimistic side, people of such countries applied social media to garner support and campaign for political parties in General Elections. Political leaders, parties, and people empowered themselves with social media, in disseminating party's agenda and advocacy of party's ideology on social media without much campaigning cost. To study effectiveness of social media inferred from individual's political behavior, large scale analysis, sentiment detection & tweet classification was done in order to classify, predict and forecast election results. The experimental results depicts that social media content can be used as an effective indicator for capturing political behaviors of different parties positive, negative and neutral behavior of the party followers as well as party campaign impact can be predicted from the analysis.

• Convergence Security Journal
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• v.15 no.6_2
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• pp.37-44
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• 2015

There appears a variety forms of crime type and age in accordance with the change of social structure. In this paper it is described for combining the Anomie theory of Emile Durkheim. Anomie refers to the absence of dual standards or norms. In other words, while weakening the existing norms prevailing when the new rules has not been established. That situation would cause social chaos. Rules on the dissemination and utilization of SNS due to the development of information and communication technology undermine the social norms while online regulations are being a weak state not established. In the confusion of these norms it has been shown to increase in juvenile delinquency. Social media has characteristics such as openness, accessibility, relationships, and content diversity. The social media itself is not subject to the general mechanisms of consumption and production due to growing as a kind of organism. It has characteristic to make the most content by utilizing the users to voluntarily share information. Social media using as communication, contact and information in the youth, thus the possibility of crime is high. Social media is also direct and indirect influence on youth crime but no apparent systemic regulation of this situation.

• Asia pacific journal of information systems
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• v.25 no.4
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• pp.719-745
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• 2015

Social networking services provide individuals with an easy approach for exchanging messages with others based on interpersonal relationships. However, why individuals spread marketer-generated content (MGC) in their online social circles remains unclear. Therefore, we develop a theoretical model to examine how social capital, intrinsic motivations, personal perceptions, past behavior, and personal traits influence MGC sharing behavior of social media users in micro-blogging context. Data collected from 319 social networking users support the proposed model. The results from partial least squares analyses show that enjoyment, perceived control, and outcome expectations are significant indicators of individual's MGC sharing intention in the social broadcasting environment. Results also suggest that social capital, users' intention, and past behavior positively influence the MGC sharing behavior of users. Moreover, individual prevention pride exhibits a significant interaction effect on the relationships between users' MGC sharing and its antecedents. Implications for research and practice are discussed.

• International Journal of Knowledge Content Development & Technology
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• v.4 no.2
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• pp.25-47
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• 2014

The goal of the present study is to explore IM interruption by relating it to media choices and purposes of IM use in the workplace. Two major media choice concepts were: media richness and social influence; while four purposes of IM use were: organization work, knowledge work, socializing, and boundary spanning activities. Data (N = 283) were collected via a combination of convenience and snowball sampling of "computer-using workers" in Taiwan, based on the Standard Occupational Classification system published by the Taiwan government. Results indicated that media choice works better than purpose of IM use to explain IM interruption. Among them, social influence was the best predictor to IM interruption in the workplace. In addition, instant feedback and personalization provided by IM, and IM usage for the purposes of knowledge work and socializing, also relate to IM interruption in the workplace.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.89-105
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• 2014

After emergence of Internet, social media with highly interactive Web 2.0 applications has provided very user friendly means for consumers and companies to communicate with each other. Users have routinely published contents involving their opinions and interests in social media such as blogs, forums, chatting rooms, and discussion boards, and the contents are released real-time in the Internet. For that reason, many researchers and marketers regard social media contents as the source of information for business analytics to develop business insights, and many studies have reported results on mining business intelligence from Social media content. In particular, opinion mining and sentiment analysis, as a technique to extract, classify, understand, and assess the opinions implicit in text contents, are frequently applied into social media content analysis because it emphasizes determining sentiment polarity and extracting authors' opinions. A number of frameworks, methods, techniques and tools have been presented by these researchers. However, we have found some weaknesses from their methods which are often technically complicated and are not sufficiently user-friendly for helping business decisions and planning. In this study, we attempted to formulate a more comprehensive and practical approach to conduct opinion mining with visual deliverables. First, we described the entire cycle of practical opinion mining using Social media content from the initial data gathering stage to the final presentation session. Our proposed approach to opinion mining consists of four phases: collecting, qualifying, analyzing, and visualizing. In the first phase, analysts have to choose target social media. Each target media requires different ways for analysts to gain access. There are open-API, searching tools, DB2DB interface, purchasing contents, and so son. Second phase is pre-processing to generate useful materials for meaningful analysis. If we do not remove garbage data, results of social media analysis will not provide meaningful and useful business insights. To clean social media data, natural language processing techniques should be applied. The next step is the opinion mining phase where the cleansed social media content set is to be analyzed. The qualified data set includes not only user-generated contents but also content identification information such as creation date, author name, user id, content id, hit counts, review or reply, favorite, etc. Depending on the purpose of the analysis, researchers or data analysts can select a suitable mining tool. Topic extraction and buzz analysis are usually related to market trends analysis, while sentiment analysis is utilized to conduct reputation analysis. There are also various applications, such as stock prediction, product recommendation, sales forecasting, and so on. The last phase is visualization and presentation of analysis results. The major focus and purpose of this phase are to explain results of analysis and help users to comprehend its meaning. Therefore, to the extent possible, deliverables from this phase should be made simple, clear and easy to understand, rather than complex and flashy. To illustrate our approach, we conducted a case study on a leading Korean instant noodle company. We targeted the leading company, NS Food, with 66.5% of market share; the firm has kept No. 1 position in the Korean "Ramen" business for several decades. We collected a total of 11,869 pieces of contents including blogs, forum contents and news articles. After collecting social media content data, we generated instant noodle business specific language resources for data manipulation and analysis using natural language processing. In addition, we tried to classify contents in more detail categories such as marketing features, environment, reputation, etc. In those phase, we used free ware software programs such as TM, KoNLP, ggplot2 and plyr packages in R project. As the result, we presented several useful visualization outputs like domain specific lexicons, volume and sentiment graphs, topic word cloud, heat maps, valence tree map, and other visualized images to provide vivid, full-colored examples using open library software packages of the R project. Business actors can quickly detect areas by a swift glance that are weak, strong, positive, negative, quiet or loud. Heat map is able to explain movement of sentiment or volume in categories and time matrix which shows density of color on time periods. Valence tree map, one of the most comprehensive and holistic visualization models, should be very helpful for analysts and decision makers to quickly understand the "big picture" business situation with a hierarchical structure since tree-map can present buzz volume and sentiment with a visualized result in a certain period. This case study offers real-world business insights from market sensing which would demonstrate to practical-minded business users how they can use these types of results for timely decision making in response to on-going changes in the market. We believe our approach can provide practical and reliable guide to opinion mining with visualized results that are immediately useful, not just in food industry but in other industries as well.

• The Journal of the Korea Contents Association
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• v.16 no.10
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• pp.421-434
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• 2016

This research paper aims to inform and suggest methods in which Korea Media content could successfully enter the African broadcasting market. It also seeks to suggest preparatory steps and propose various policies that Korean government could provide, to aid the export process. In order to maximize the Korean media content exposure in the Kenyan market, increased financial support for subtitles and dubbing as well as launching a Korean culture center is suggested. In addition, to encourage more diverse channels to show the Korean content, joint content production between Korea and Kenya should be considered. Moreover, in analyzing the social, cultural, ethnic and local characteristics of the Kenyan people, the paper seeks to identify the most efficient method in which Korean wave could be more widespread in Kenya. Since virtually no prior research papers exist on Kenyan's social and cultural characteristics and their thought process on the Korean media content, this paper seeks to provide valuable insight and policy implications for Korean media policy makers.

• International Journal of Contents
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• v.16 no.1
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• pp.10-24
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• 2020

As many brands use social media influencers (SMIs) on Instagram to advertise, not disclosing advertised content affects how consumers perceive these influencers. The purpose of this study was to investigate two objectives: 1) recent advertising disclosure types on Instagram and 2) the factors that affect consumer responses towards Instagram influencers posting advertised content. Using an experimental 2x2 between-subjects design (N=200), the findings show that "sponsored" and "paid partnership with" are two recent types of ad disclosures. However, both factors are insignificantly different from each other. Also, ad disclosure condition enhances the trustworthiness of the influencer than no disclosure. Ad skepticism, source credibility, and the level of persuasion strongly relate to how consumers perceive Instagram influencers advertising for brands. These factors enable consumers to assess if the influencer is a reliable source of information when faced with advertisement. Ultimately, using disclosure gives full information to consumers about the persuasive intent, as well as increases positive consumer responses towards the influencer who discloses, thereby, enhancing the ethical use of the influencer advertising strategy and long-term consumer relationship.

• Asia Marketing Journal
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• v.22 no.3
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• pp.71-85
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• 2020

Social media has emerged as a major hub of engagement between brands and consumers in recent years, and allows user-generated content to serve as a powerful means of encouraging communication between the sides. However, it is challenging to negotiate user-generated content owing to its lack of structure and the enormous amount generated. This study focuses on the hashtag, a metadata tag that reflects customers' brand perception through social media platforms. Online users share their knowledge and impressions using a wide variety of hashtags. We examine hashtags that co-occur with particular branded hashtags on the social media platform, Instagram, to derive insights about brand perception. We apply text mining technology and network analysis to identify the perceptions of brand images among consumers on the site, where this helps distinguish among the diverse personalities of the brands. This study contributes to highlighting the value of hashtags in constructing brand personality in the context of online marketing.

• Journal of Information Science Theory and Practice
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• v.8 no.4
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• pp.6-19
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• 2020

The objective of this research is to analyze which functions make up web-based as well as mobile social media services and messengers. Services are clustered by their functionality. A total of 640 individual functions were identified, while investigating altogether 44 selected services in their web and mobile versions. Applying content analysis, functions were assigned to the services. The services were ranked by the number of implemented functions, and the functions were ranked by their occurrence in the services. Cluster analysis was applied to classify the services according to their functionality. Facebook and VKontakte were found to be the ones with the most functions; the most frequently implemented functions are support, profile, and account-related. Cluster analysis revealed six classes for mobile and seven classes for web applications. There is a noteworthy difference regarding the functionality scope between web and mobile applications of the same services. An example for this is Mendeley with 38 functions in the mobile and 91 functions in the web version. This is the first empirical attempt at clustering social media services based on their functionality.

• Asia pacific journal of information systems
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• v.34 no.1
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• pp.91-113
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• 2024

In the wake of the COVID-19 pandemic, unsubstantiated information concerning vaccines and the coronavirus has proliferated on various social media platforms. Consequently, we have considered viable actions to mitigate the impact of such unverified content, enabling individuals to use social media platforms more effectively and minimize any ensuing confusion. Recent measures in this area have included YouTube's practice of labeling vaccine or corona videos as authoritative when emanating from reputable organizations and Twitter's practice of flagging vaccine-related content as potentially misleading or taken out of context. This study seeks to explore how such contrasting labeling practices influence users' believability and engagement differentially, while also examining the moderating impact of regulatory focus. The results indicate that authoritative labeling positively influenced users' believability and engagement, whereas misleading labeling adversely affected users' believability and engagement. Additionally, our findings revealed that authoritative labeling has a stronger impact on promotion-focused individuals, while misleading labeling has a more pronounced effect on prevention-focused individuals. Our findings offer insights into how social media platforms can design and present information to their users, taking into account their regulatory focus.