DSpin: Detecting Automatically Spun Content on the Web

Web spam is an abusive search engine optimization technique that artificially boosts the search result rank of pages promoted in the spam content. A popular form of Web spam today relies upon automated spinning to avoid duplicate detection. Spinning replaces words or phrases in an input article to create new versions with vaguely similar meaning but sufficiently different appearance to avoid plagiarism detectors. With just a few clicks, spammers can use automated tools to spin a selected article thousands of times and then use posting services via proxies to spam the spun content on hundreds of target sites. The goal of this paper is to develop effective techniques to detect automatically spun content on the Web. Our approach is directly tied to the underlying mechanism used by automated spinning tools: we use a technique based upon immutables, words or phrases that spinning tools do not modify when generating spun content. We implement this immutable method in a tool called DSpin, which identifies automatically spun Web articles. We then apply DSpin to two data sets of crawled articles to study the extent to which spammers use automated spinning to create and post content, as well as their spamming behavior.