• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.1032-1042
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• 2017

Many empirical studies indicate that SNS use has increased substantially over the last few years. People use SNSs for social purposes, mostly related to the maintenance of existing offline contacts. Such usage may have led to compulsive use of SNSs resulting in addictive behavior. This paper aims to explore factors affecting SNS addiction. Specifically, the study examined the role of personality traits in the Facebook usage among college students. Compared to the rest of world, daily log on the site has grown very quickly in South Korea. And college students constitute a vast majority of Facebook users in South Korea. Results from a survey of 235 college students revealed that extraversion and neuroticism positively predicted Facebook usage. Students who were high in extraversion were more likely to update their profiles, share photo and images with others and give feedback on other's posts. Similarly, those who were high in neuroticism were more likely to share photo and images with others and update their profiles. These findings support previous research. Furthermore, in terms of the effect of personality on SNS addiction, this study found that consciousness was negatively associated with Facebook addiction, while extraversion and neuroticism were positively associated with Facebook addiction. Based on these findings implications and directions for futures studies are discussed.

• Journal of Internet Computing and Services
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• v.15 no.2
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• pp.73-85
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• 2014

This study analyzed the profile of a Facebook account to examine how personal information is revealed and what kinds of factors influence personal information revelation. Categories of user's profile on Facebook were analyzed and two dimensions were developed; the degree that how much personal information is revealed and the network limits that personal information is accessed. Main variables to determine personal information revelation are Facebook privacy concern and uses for social relationships along with gender, the duration of Facebook use, and average time of use. Data were collected from college students. Factor analysis produced two factors of Facebook privacy concern, Facebook privacy concern with users and Facebook privacy concern with the Facebook system. Regression analyses were performed to identify significant determinants of the degree of information revelation and the network limits of personal information. The results found out that the degree of personal information revelation is explained by gender, the duration of use, and use for social relationships while the network limit is explained by the duration of use and Facebook privacy concern with users. Worthy of notice is that use for social relationships and Facebook privacy concern with the Facebook system offset each other. The implications of the results are discussed. Additionally and finally the categories of profiles are graphically re-grouped to show how personal information revelation is associated with social relationship generation and maintenance.

• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.87-93
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• 2020

The popularity of social media has led to a variety of communicative behaviors among users. This study targeted Facebook as a representative social medial platform because it has the most subscribers in order to investigate factors that influence Facebook usage. In particular, because a person's behavior is based on how they are perceived by others, self-conscious behavior was examined in the study. Facebook usage and news consumption were examined to ascertain the effects of self-consciousness. An online survey was conducted to examine how private SC and public SC (SCs), affects Facebook usage (profiles and writing posts) and news consumption (clicking "like" and sharing news). 616 participants completed the survey, and results indicated that public SC was positively related to the degree of profile updating and post writing. On the other hand, private SC was positively related to the degree of news sharing. These results suggest that psychological elements significantly predict a user's behavior on Facebook.

• 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.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.57-71
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• 2013

Over a billion people in the world generate new news minute by minute. People forecasts some news but most news are from unexpected events such as natural disasters, accidents, crimes. People spend much time to watch a huge amount of news delivered from many media because they want to understand what is happening now, to predict what might happen in the near future, and to share and discuss on the news. People make better daily decisions through watching and obtaining useful information from news they saw. However, it is difficult that people choose news suitable to them and obtain useful information from the news because there are so many news media such as portal sites, broadcasters, and most news articles consist of gossipy news and breaking news. User interest changes over time and many people have no interest in outdated news. From this fact, applying users' recent interest to personalized news service is also required in news service. It means that personalized news service should dynamically manage user profiles. In this paper, a content-based news recommendation system is proposed to provide the personalized news service. For a personalized service, user's personal information is requisitely required. Social network service is used to extract user information for personalization service. The proposed system constructs dynamic user profile based on recent user information of Facebook, which is one of social network services. User information contains personal information, recent articles, and Facebook Page information. Facebook Pages are used for businesses, organizations and brands to share their contents and connect with people. Facebook users can add Facebook Page to specify their interest in the Page. The proposed system uses this Page information to create user profile, and to match user preferences to news topics. However, some Pages are not directly matched to news topic because Page deals with individual objects and do not provide topic information suitable to news. Freebase, which is a large collaborative database of well-known people, places, things, is used to match Page to news topic by using hierarchy information of its objects. By using recent Page information and articles of Facebook users, the proposed systems can own dynamic user profile. The generated user profile is used to measure user preferences on news. To generate news profile, news category predefined by news media is used and keywords of news articles are extracted after analysis of news contents including title, category, and scripts. TF-IDF technique, which reflects how important a word is to a document in a corpus, is used to identify keywords of each news article. For user profile and news profile, same format is used to efficiently measure similarity between user preferences and news. The proposed system calculates all similarity values between user profiles and news profiles. Existing methods of similarity calculation in vector space model do not cover synonym, hypernym and hyponym because they only handle given words in vector space model. The proposed system applies WordNet to similarity calculation to overcome the limitation. Top-N news articles, which have high similarity value for a target user, are recommended to the user. To evaluate the proposed news recommendation system, user profiles are generated using Facebook account with participants consent, and we implement a Web crawler to extract news information from PBS, which is non-profit public broadcasting television network in the United States, and construct news profiles. We compare the performance of the proposed method with that of benchmark algorithms. One is a traditional method based on TF-IDF. Another is 6Sub-Vectors method that divides the points to get keywords into six parts. Experimental results demonstrate that the proposed system provide useful news to users by applying user's social network information and WordNet functions, in terms of prediction error of recommended news.

• The Journal of Bigdata
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• v.1 no.1
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• pp.61-66
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• 2016

With big data analysis, companies use the customized marketing strategy based on customer's information. However, because of the concerns about privacy issue and identity theft, people start erasing their personal information or changing the privacy settings on social network site. Facebook, the most used social networking site, has the feature called 'Likes' which can be used as a tool to predict user's demographic profiles, such as sex and age range. To make accurate analysis model for the study, 'Likes' data has been processed by using Gaussian RBF and nFactors for dimensionality reduction. With random Forest and 5-fold cross-validation, the result shows that sex has 75% and age has 97.85% accuracy rate. From this study, we expect to provide an useful guideline for companies and marketers who are suffering to collect customers' data.

• Journal of Contemporary Eastern Asia
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• v.18 no.1
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• pp.49-69
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• 2019

Over the last couple of years, digital diplomacy has become a fascinating area of research among Mass Communication, Peace and Conflict Studies, and International Affairs scholars. Social media and new technology open up new avenues for governments, individuals, and organizations to engage with foreign audiences. However, developing countries' governments are still lacking in the realization of the potential of social media. This study aims to analyze the usage of social media (Facebook & Twitter) by the two biggest countries in South Asia (Pakistan and India). I selected 10 government officials' social media accounts including prime ministers', national press offices', military public relations offices', public diplomacy divisions', and ministries of foreign offices' profiles. The study relies on quantitative content analysis and a comparative research approach. The total number of analyzed Twitter tweets (n=1,015) and Facebook posts (n=1,005) include 10 accounts, five from each country. In light of Kent and Taylor's (1998) dialogic communication framework, the results indicate that no digital engagement and dialogue occurs between government departments and the public through social networking sites. Government departments do not engage with local or foreign audiences through digital media. When comparing both countries, results reveal that India has more institutionalized and organized digital diplomacy. In terms of departmental use of social media, the digital diplomacy division and foreign office of India is more active than other government departments in that nation. Meanwhile, Pakistan's military public relations office and press office is more active than its other government departments. In conclusion, both countries realize the potential of social media in digital diplomacy, but still lack engagement with foreign audiences.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.5
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• pp.141-148
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• 2011

Recently, various social network services have been grown. Among them, personal relationships based social network services such as Facebook and Twitter make a remarkable growth of industry. In such services, users' profiles are very important for establishing the relationship between two users. However some information in a user's profile causes the leakage of the user's privacy, and thus we have to deal with the information in the profile. Especially, we have to treat contact information, such as the phone number and the e-mail address, very carefully since an adversary can use the information to violate the user's privacy in real life. In this paper, we propose two profile management systems that can enhance the privacy of users in social network services. We compare our systems with existing profile management techniques in well-known social network services such as Facebook and Twitter, and show that our systems provide enhanced privacy.

• Knowledge Management Research
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• v.16 no.4
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• pp.89-108
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• 2015

Social networking communities (SNCs) are media designed to facilitate social interaction using highly accessible and scalable publishing techniques. SNCs can constitute individuals' their own profiles in the online environment and share texts, images and photos in a variety ways. In other words, one of the other motivators is knowledge sharing. Various sites, such as Facebook, Orkut, MySpace, and Hi5 are categorized as SNCs. SNCs have become increasingly popular in recent years among youths, especially students, who use them to build social networks. This study examines whether this usage of SNCs inculcates a sense of community among their members. Several studies have examined the role of a sense of community through increased usage in the context of virtual communities. Although this result may be true of virtual communities, this paper contends that the opposite relationship prevails in the case of SNCs because members interact to build networks and are not obliged to interact. The results reveal that maintaining long-term interactions in the SNCs is helpful in building a sense of community in SNCs. Although short-term usage may not boost the development of a sense of community in SNCs, it does matter if the premise is for a long-term commitment to SNCs. Implications for theory and practice are discussed.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.2
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• pp.395-410
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• 2015

This research defines the degree of the threat caused by the leakage of personal information in a quantitative way. The proposed definition classifies the individual items in a personal data, then assigns a risk value to each item. The proposed method considers the increase of the risk by the composition of the multiple items. We also deals with various attack scenarios, where the attackers seek different types of personal information. The concept of entropy applies to associate the degree of the personal information exposed with the total risk value. In our experiment, we measured the risk value of the Facebook users with their public profiles. The result of the experiment demonstrates that they are most vulnerable against stalker attacks among four possible attacks with the personal information.