| Summary: | 碩士 === 中國文化大學 === 資訊管理研究所 === 97 === Web 2.0, especially Blog, grows rapidly in recent years. According to a survey conducted by InsightXplorer in November 2008 regarding to the usage of Blogs in Taiwan, found that 32% of respondents have their own Blogs. Most of them used Blog Service Delivery Platforms (Blog Service Providers, BSPs) to build and maintain their blogs. Among them "Wretch" (42.9 %) is the most favored one.
The classification of Blogs on BSPs usually is done through the blog authors’ (bloggers’) self-classifications. However, the writings of bloggers are diversified and the self-classifications are not rigorous, which resulting in the classification of blogs usually are lacking of precision.
Mostly of studies of network-related classification in the past used the hyperlinks, degrees of aggregation, such as backtracking, or the frequencies of words used as the methods of classification. However, most results can only be used to show liking strengths among sites, and can’t be used as effective classification methods.
In this study, a more realistic compromise is used. We first pick a certain amount of sample blogs from manually classification of BSP as training data, and then pick keywords according to categories they belonged to classified them and do word frequency analysis. And finally test and verify the results. The result shows the proposed classification method is indeed effective.
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