Fast Spammer Detection Using Structural Rank
This addresses spam detection in online comments to prevent bias in product or service quality measurements, though it appears incremental as it builds on existing structural rank techniques.
The paper tackles the problem of detecting spammers in rapidly growing online comment sections by proposing an efficient method using structural rank of author-specific term-document matrices, which was found to be effective and significantly faster than similar methods.
Comments for a product or a news article are rapidly growing and became a medium of measuring quality products or services. Consequently, spammers have been emerged in this area to bias them toward their favor. In this paper, we propose an efficient spammer detection method using structural rank of author specific term-document matrices. The use of structural rank was found effective and far faster than similar methods.