A repository of privacy incidents is essential for understanding the attributes of products and policies that lead to privacy incidents. We describe our vision for a novel privacy incidents database and our progress toward building a prototype. Key challenges in gathering such a database include bootstrapping and sustainability. We propose a semi-automated framework that can recognize privacy incidents and related information from various online sources such as news, blogs, and social media. The crux of our framework is an incident classi er that identi es whether a piece of text in natural language is related to a privacy incident or not. We curate a dataset consisting of 1324 news articles of which 543 articles are about one or more privacy incidents. We train the incident classi er on this dataset, considering a variety of feature engineering, feature selection, and classi cation techniques. We nd that our incident classi er yields an F 1 measure of 93.1%, which is about 12% higher than the keyword search-based baselines we adopt. CCS CONCEPTS • Security and privacy → Human and societal aspects of security and privacy; • Information systems → Data analytics;

Previous approaches to narrative generation have required a new planner implementation for each set of constraints deemed relevant to the narrative domain, each consisting of thousands of lines of code and supporting one primary mode of interaction: fully specifying a domain and problem, and receiving a plan as output. We present a lightweight, flexible narrative planner written with Answer Set Programming, designed specifically to support constraint-based narrative generation, show how it generalizes previous approaches, and show how it can be easily extended with notions of thematic plot schema such as “betrayal.” Finally, we demonstrate how the ASP model can be explored through interactive question answering, where answers take the form of generated narratives. In the long term, we intend this work to support understanding of complex rule systems through interactive exploration.

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