Tropes in advertising: a web-based empirical study

This study examines the role of one type of rhetorical figure, tropes, which are creative devices that entail the arrangement of words in paradoxical relationships. Specifically, its focus lies in investigating whether the influence simple and complex tropes have on persuasion, as reported in previous research by Toncar and Munch (2003), are generalisable beyond the sample they used. In the extant literature, it is argued that by fully understanding the effects of certain types of tropes, advertisers may better apply their persuasive messages. The study finds that, when using subjective measures as initiated by Toncar and Munch (2003), tropes have no influence on persuasion. While it is noted that further research is needed to increase the generalisability of this study, this result holds true when both simple and complex trope types are used. <br /

Consumer traits: an investigation of influences

This study uses a hierarchical approach to build a model of the relationships between Consumer Need for Uniqueness (CNFU), Consumer Novelty Seeking (CNS), and a behavioural outcome, media consumption and information exposure. The study finds that those consumers who have a need for uniqueness are high in consumer novelty seeking tendencies. Subsequently, these consumers are found to have higher information exposure by consuming more media.<br /

Phobos: A front-end approach to extensible compilers (long version)

This paper describes a practical approach for implementing certain types of domain-specific languages with extensible compilers. Given a compiler with one or more front-end languages, we introduce the idea of a "generic" front-end that allows the syntactic and semantic specification of domain-specific languages. Phobos, our generic front-end, offers modular language specification, allowing the programmer to define new syntax and semantics incrementally

Reading Wikipedia to Answer Open-Domain Questions

This paper proposes to tackle open- domain question answering using Wikipedia as the unique knowledge source: the answer to any factoid question is a text span in a Wikipedia article. This task of machine reading at scale combines the challenges of document retrieval (finding the relevant articles) with that of machine comprehension of text (identifying the answer spans from those articles). Our approach combines a search component based on bigram hashing and TF-IDF matching with a multi-layer recurrent neural network model trained to detect answers in Wikipedia paragraphs. Our experiments on multiple existing QA datasets indicate that (1) both modules are highly competitive with respect to existing counterparts and (2) multitask learning using distant supervision on their combination is an effective complete system on this challenging task.Comment: ACL2017, 10 page

What Words Do We Use to Lie?: Word Choice in Deceptive Messages

Text messaging is the most widely used form of computer- mediated communication (CMC). Previous findings have shown that linguistic factors can reliably indicate messages as deceptive. For example, users take longer and use more words to craft deceptive messages than they do truthful messages. Existing research has also examined how factors, such as student status and gender, affect rates of deception and word choice in deceptive messages. However, this research has been limited by small sample sizes and has returned contradicting findings. This paper aims to address these issues by using a dataset of text messages collected from a large and varied set of participants using an Android messaging application. The results of this paper show significant differences in word choice and frequency of deceptive messages between male and female participants, as well as between students and non-students

The effect of public funding on research output: the New Zealand Marsden Fund

The Marsden Fund is the premiere funding mechanism for blue skies research in New Zealand. In 2014, $56 million was awarded to 101 research projects chosen from among 1222 applications from researchers at universities, Crown Research Institutes and independent research organizations. This funding mechanism is similar to those in other countries, such as the European Research Council. This research measures the effect of funding receipt from the New Zealand Marsden Fund using a unique dataset of funded and unfunded proposals that includes the evaluation scores assigned to all proposals. This allows us to control statistically for potential bias driven by the Fund’s efforts to fund projects that are expected to be successful, and also to measure the efficacy of the selection process itself. We find that Marsden Funding does increase the scientific output of the funded researchers, but that there is no evidence that the final selection process is able to meaningfully predict the likely success of different proposals