Using Contexts and Constraints for Improved Geotagging of Human Trafficking Webpages

Extracting geographical tags from webpages is a well-motivated application in many domains. In illicit domains with unusual language models, like human trafficking, extracting geotags with both high precision and recall is a challenging problem. In this paper, we describe a geotag extraction framework in which context, constraints and the openly available Geonames knowledge base work in tandem in an Integer Linear Programming (ILP) model to achieve good performance. In preliminary empirical investigations, the framework improves precision by 28.57% and F-measure by 36.9% on a difficult human trafficking geotagging task compared to a machine learning-based baseline. The method is already being integrated into an existing knowledge base construction system widely used by US law enforcement agencies to combat human trafficking.Comment: 6 pages, GeoRich 2017 workshop at ACM SIGMOD conferenc

Positing the problem : enhancing classification of extremist web content through textual analysis

Webpages with terrorist and extremist content are key factors in the recruitment and radicalization of disaffected young adults who may then engage in terrorist activities at home or fight alongside terrorist groups abroad. This paper reports on advances in techniques for classifying data collected by the Terrorism and Extremism Network Extractor (TENE) web-crawler, a custom-written program that browses the World Wide Web, collecting vast amounts of data, retrieving the pages it visits, analyzing them, and recursively following the links out of those pages. The textual content is subjected to enhanced classification through software analysis, using the Posit textual analysis toolset, generating a detailed frequency analysis of the syntax, including multi-word units and associated part-of-speech components. Results are then deployed in a knowledge extraction process using knowledge extraction algorithms, e.g., from the WEKA system. Indications are that the use of the data enrichment through application of Posit analysis affords a greater degree of match between automatic and manual classification than previously attained. Furthermore, the incorporation and deployment of these technologies promises to provide public safety officials with techniques that can help to detect terrorist webpages, gauge the intensity of their content, discriminate between webpages that do or do not require a concerted response, and take appropriate action where warranted