Abstract

In recent years, Social Network Service, which is defined as a web-based service that allows an individual to construct a public or a semi-public profile within a bounded system, articulates a list of other users with whom they share connections, and traverses their list of connections. For example, Facebook and Twitter are the representative sites of Social Network Service, and these sites are the big issue in the world. A lot of people use Social Network Services to connect and maintain social relationship. Recently the users of Social Network Services have increased dramatically. Accordingly, many organizations become interested in Social Network Services as means of marketing, media, communication with their customers, and so on, because social network services can offer a variety of benefits to organizations such as companies and associations. In other words, organizations can use Social Network Services to respond rapidly to various user's behaviors because Social Network Services can make it possible to communicate between the users more easily and faster. And marketing cost of the Social Network Service is lower than that of existing tools such as broadcasts, news papers, and direct mails. In addition, Social network Services are growing in market place. So, the organizations such as companies and associations can acquire potential customers for the future. However, organizations uniformly communicate with users through Social Network Service without consideration of the characteristics of the networks although networks have different effects on information deliveries. For example, members' cohesion in an offline communication is higher than that in an online communication because the members of the offline communication are very close. that is, the network of the offline communication has a strong tie. Accordingly, information delivery is fast in the network of the offline communication. In this study, we compose two networks which have different characteristic of communication in Twitter. First network is constructed with data based on an offline communication such as friend, family, senior and junior in school. Second network is constructed with randomly selected data from users who want to associate with friends in online. Each network size is 250 people who divide with three groups. The first group is an ego which means a person in the center of the network. The second group is the ego's followers. The last group is composed of the ego's follower's followers. We compare the networks through social network analysis and follower's reaction analysis. We investigate density and centrality to analyze the characteristic of each network. And we analyze the follower's reactions such as replies and retweets to find differences of information delivery in each network. Our experiment results indicate that density and centrality of the offline communicationbased network are higher than those of the online-based network. Also the number of replies are larger than that of retweets in the offline communication-based network. On the other hand, the number of retweets are larger than that of replies in the online based network. We identified that the effect of information delivery in the offline communication-based network was different from those in the online communication-based network through experiments. So, you configure the appropriate network types considering the characteristics of the network if you want to use social network as an effective marketing tool.

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