Combining Anchor Text Categorization and Graph Analysis for Paid Link Detection

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Abstract

In order to artificially boost the rank of commercial pages in search engine results, search engine optimizers pay for links to these pages on other websites. Identifying paid links is important for a web search engine to produce highly relevant results. In this paper we introduce a novel method of identifying such links. We start with training a classifier of anchor text topics and analyzing web pages for diversity of their outgoing commercial links. Then we use this information and analyze link graph of the Russian Web to find pages that sell links and sites that buy links and to identify the paid links. Testing on manually marked samples showed high efficiency of the algorithm.