Layout 1 ISDS Annual Conference Proceedings 2012. This is an Open Access article distributed under the terms of the Creative Commons Attribution- Noncommercial 3.0 Unported License (http://creativecommons.org/licenses/by-nc/3.0/), permitting all non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. ISDS 2012 Conference Abstracts Towards Linking Anonymous Authorship in Casual Sexual Encounter Ads Jason A. Fries*1, Alberto M. Segre1 and Philip M. Polgreen2 1Computer Science, The University of Iowa, Iowa City, IA, USA; 2The University of Iowa - Department of Internal Medicine, Iowa CIty, IA, USA Objective This paper constructs an authorship-linked collection or corpus of anonymous, sex-seeking ads found on the classifieds website Craigslist. This corpus is then used to validate an authorship attribu- tion approach based on identifying near duplicate text in ad clusters, providing insight into how often anonymous individuals post sex- seeking ads and where they meet for encounters. Introduction The increasing use of the Internet to arrange sexual encounters presents challenges to public health agencies formulating STD inter- ventions, particularly in the context of anonymous encounters. These encounters complicate or break traditional interventions. In previous work [1], we examined a corpus of anonymous personal ads seeking sexual encounters from the classifieds website Craigslist and pre- sented a way of linking multiple ads posted across time to a single au- thor. The key observation of our approach is that some ads are simply reposts of older ads, often updated with only minor textual changes. Under the presumption that these ads, when not spam, originate from the same author, we can use efficient near-duplicate detection tech- niques to cluster ads within some threshold similarity. Linking ads in this way allows us to preserve the anonymity of authors while still ex- tracting useful information on the frequency with which authors post ads, as well as the geographic regions in which they seek encounters. While this process detects many clusters, the lack of a true corpus of authorship-linked ads makes it difficult to validate and tune the parameters of our system. Fortunately, many ad authors provide an obfuscated telephone number in ad text (e.g., 867-5309 becomes 8sixseven5three oh nine) to bypass Craigslist filters, which prohibit including phone numbers in personal ads. By matching phone num- bers of this type across all ads, we can create a corpus of ad clusters known to be written by a single author. This authorship corpus can then be used to evaluate and tune our existing near-duplicate detec- tion system, and in the future identify features for more robust au- thorship attribution techniques. Methods From 7-1-2009 until 7-1-2011, RSS feeds were collected daily for 8 personal ad categories from 414 sites across the United States, for a total of 67 million ads. To create an anonymous, author-linked cor- pus, we used a regular expression to identify obfuscated phone num- bers in ad text. We measure the ability of near-duplicate detection to link clusters in two ways: 1) detecting all ads in a cluster; and 2) cor- rectly detecting a subset of ads within a single cluster. Ads incorrectly assigned to more than 1 cluster are considered false positives. All re- sults are reported in terms of precision, recall, and F-scores (common information retrieval metrics) across cluster size, expressed as num- ber of ads. Results 652,014 ads contained phone numbers, producing a total of 46,079 authorship-linked ad clusters. For detecting all ads within a cluster, precision ranged from 0.05 to 0.0 and recall from 0.02 to 0.0 for all cluster sizes. For detecting partial clusters, see Figure 1. Conclusions We find that near-duplicate detection alone is insufficient to de- tect all ads within a cluster. However, we do find that the process can, with high precision and low recall, detect a subset of ads associated with a single author. This follows the intuition that an author’s total set of ads is itself comprised of multiple self-similar subsets. While a near-duplicate detection approach can correctly identify subsets of ads linked to a single author, this process alone cannot attribute mul- tiple clusters to a single author. Future work will explore leveraging additional linguistic features to improve author attribution. (Top) Evaluations for partial cluster detection using the near-duplicate iden- tification approach to linking anonymous authorship in Craigslist ads and (bottom) the distribution of ad cluster sizes. Keywords Surveillance; Public Health; STDs; Authorship Attribution; Computer Science References [1] JA Fries, AM Segre, PM Polgreen .Using Online Classified Ads to Identify the Geographic Footprints of Anonymous, Casual Sex-seek- ing Individuals. ASE/IEEE International Conference on Social Com- puting 2012. *Jason A. Fries E-mail: jason-fries@uiowa.edu Online Journal of Public Health Informatics * ISSN 1947-2579 * http://ojphi.org * 5(1):e164, 2013