A Study on Online Self-disclosure Using Data Mining Techniques

• Main Authors: Ya-Fang Cheng, 鄭雅方
• Other Authors: Mu-Jung Huang
• Format: Others
• Language: zh-TW
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/61955507428982974358

碩士 === 國立彰化師範大學 === 資訊管理學系所 === 98 === In the era of Internet, many Internet services show up and are challenged by new ones. However, with newer, more comprehensive network services, the old services are facing the fate of being replaced. For example, the social network site “Facebook” provides many interactive services and has grown so rapidly that it influences the existence of other sites. However, when the user switching to different network services, what are in their mind? For novelty, or better quality? Do new services are really better fit to user needs? This study chooses self- disclosure, the most common network acts, as a research field. Invite individual who posted personal messages on the Internet to implement the survey and build our user database based on 1812 returned questionnaire. Through data mining approach by association rules and decision tree, we identify the differences of user s’ motivation to change the self- disclosure platform and retrieval the reasons why people continue to use old platform. Then, add the Internet satisfaction of motivation and personality differences to try to find the rules. The results confirm that most users who use Facebook still use the original platform because of switching costs. Whether the Internet services meet the user needs, the personality will influence users to switch to the new platform or use the old platform.