I thought this was pretty impressive:

We study techniques for identifying an anonymous author via linguistic stylometry, i.e., comparing the writing style against a corpus of texts of known authorship. We experimentally demonstrate the effectiveness of our techniques with as many as 100,000 candidate authors.

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In experiments where we match a sample of just 3 blog posts against the rest of the posts from that blog (mixed in with 100,000 other blogs), the nearest-neighbor/RLSC combination is able to identify the correct blog in about 20% of cases; in about 35% of cases, the correct blog is one of the top 20 guesses. Via confidence estimation, we can increase precision from 20% to over 80% with a recall of 50%, which means that we identify 50% of the blogs overall compared to what we would have if we always made a guess.

The efficacy of the attack varies based on the number of labeled and anonymous posts available. Even with just a single post in the anonymous sample, we can identify the correct author about 7.5% of the time (without any confidence estimation). When the number of available posts in the sample increases to 10, we are able to achieve a 25% accuracy. Authors with relatively large amounts of content online (about 40 blog posts) fare worse: they are identified in over 30% of cases (with only 3 posts in the anonymous sample).

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Further, we confirmed that our techniques work in a cross-context setting: in experiments where we match an anonymous blog against a set of 100,000 blogs, one of which is a different blog by the same author, the nearest neighbor classifier can correctly identify the blog by the same author in about 12% of cases. Finally, we also manually verified that in crosscontext matching we find pairs of blogs that are hard for humans to match based on topic or writing style; we describe three such pairs in Appendix A.

The strength of the deanonymization attack we have presented is only likely to improve over time as better techniques are developed. Our results thus call into question the viability of anonymous online speech. Even if the adversary is unable to identify the author using our methods in a fully automated fashion, he might be able to identify a few tens of candidates for manual inspection as we detail in Section III.