Extracting Spam Blogs With Co-Citation Clusters
Source: Association for Computing Machinery
This paper reports the estimated number of spam blogs in order to assess their current state in the blogosphere. To extract spam blogs, they developed a traversal method among co-citation clusters of blogs from a spam seed. Spam seeds were collected in terms of high out-degree and spam keyword. According to the experiment, a mixed seed set composed of high out-degree and spam keyword seeds is more effective than individual seed sets in terms of FMeasure. In conclusion, mixed seeds from different methods are effective in improving the F-Measure results of spam extraction with co-citation clusters.
| Format: | Size: | 234.60 | |
| Date: | Apr 2008 |



