In this article, we examine the discourse goals that are accomplished by the use of eight forms of figurative language: hyperbole, idiom, indirect request, irony, understatement, metaphor, rhetorical question, and simile. Subjects were asked to provide reasons why they would use a particular figure of speech. Based on their responses, a discourse goal taxonomy that includes each of the eight figures was developed. The goal taxonomy indicates that each figure of speech is used to accomplish a unique constellation of communicative goals. The degree of goal overlap between the eight forms was also calculated, and the results provide support for theoretical claims about the relatedness of certain figures. Taken together, the goal taxonomy and overlap scores broaden our understanding of functional and theoretical differences between the various kinds of figurative language.

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In this study a model of question answering (called QUEST) is tested in the context of short stories. College students first read a story and then judged the quality of answers to questions about episodes in the story. The model could account for the goodness-of-answer judgments and decision latencies of 5 categories of questions: why, how, when, enablement, and consequence. QUEST specifies the information sources that are activated during question answering; the content of each information source is structured according to a theory of knowledge representation. QUEST specifies the convergence processes that dramatically narrow down the set of possible answers (activated from the information sources) to a small set of good answers to a question.

The Internet of Things (IoT) introduces an unprecedented diversity and ubiquity to networked computing. It also introduces new attack surfaces that are a boon to attackers. The recent Mirai botnet showed the potential and power of a collection of compromised IoT devices. A new botnet, known as Hajime, targets many of the same devices as Mirai, but differs considerably in its design and operation. Hajime uses a public peer-to-peer system as its command and control infrastructure, and regularly introduces new exploits, thereby increasing its resilience. We show that Hajime's distributed design makes it a valuable tool for better understanding IoT botnets. For instance, Hajime cleanly separates its bots into different peer groups depending on their underlying hardware architecture. Through detailed measurement-active scanning of Hajime's peer-to-peer infrastructure and passive, longitudinal collection of root DNS backscatter traffic-we show that Hajime can be used as a lens into how IoT botnets operate, what kinds of devices they compromise, and what countries are more (or less) susceptible. Our results show that there are more compromised IoT devices than previously reported; that these devices use an assortment of CPU architectures, the popularity of which varies widely by country; that churn is high among IoT devices; and that new exploits can quickly and drastically increase the size and power of IoT botnets. Our code and data are available to assist future efforts to measure and mitigate the growing threat of IoT botnets.

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