Surprising turns of the persuasive path – exploitation of conceptual blending in Polish medical advertising

The essence of advertising lies very often in unusual and surprising juxtapositions of apparently incongruous elements, which nevertheless successfully combine in pro-ducing a coherent and understandable message. A vital role is performed by a skillful-ly engineered context, which allows for simultaneous activation of certain otherwise inconspicuous senses and the construction of novel and attractive connections. Such theoretical proposals as Lemke’s traversals (2001; 2005), Fauconnier and Turner’s Conceptual Blending Theory (1998; 2002) and Kecskes’s Dynamic Model of Mean-ing (2008) seem to describe many vital aspects of the phenomenon in question. It is in advertising that we often come across the linking of elements by transgressing naturally existing borders between domains which are unrelated, and we are invited to map onto one another different mental spaces on the basis of their salient analogy or identity, and indulge in creative riddle-like exploration of contextual elements in order to reconstruct the intended message. These techniques’ true power lies in their abil-ity to blur the distinction between ‘the real’ and ‘the imagined’ to such an extent that certain irrational but attractive connections, implanted in the minds of the audience, contribute to subsequent decisions in the real world. The present study attempts to uncover the ways in which certain unrelated elements are skillfully brought together in a context which allows for such a juxtaposition in selected Polish TV advertise-ments for various medicine and health-related products. The method employed is an in-depth content analysis of the material, followed by an attempt to integrate the iden-tifi ed mechanisms with the models of meaning-making mentioned above. The results will hopefully help in better understanding of the ways in which particular compo-nents of the context may interact with the message expressed verbally or pictorially in the construction of multilevel meanings in advertising communication

Knowledge-rich Image Gist Understanding Beyond Literal Meaning

We investigate the problem of understanding the message (gist) conveyed by images and their captions as found, for instance, on websites or news articles. To this end, we propose a methodology to capture the meaning of image-caption pairs on the basis of large amounts of machine-readable knowledge that has previously been shown to be highly effective for text understanding. Our method identifies the connotation of objects beyond their denotation: where most approaches to image understanding focus on the denotation of objects, i.e., their literal meaning, our work addresses the identification of connotations, i.e., iconic meanings of objects, to understand the message of images. We view image understanding as the task of representing an image-caption pair on the basis of a wide-coverage vocabulary of concepts such as the one provided by Wikipedia, and cast gist detection as a concept-ranking problem with image-caption pairs as queries. To enable a thorough investigation of the problem of gist understanding, we produce a gold standard of over 300 image-caption pairs and over 8,000 gist annotations covering a wide variety of topics at different levels of abstraction. We use this dataset to experimentally benchmark the contribution of signals from heterogeneous sources, namely image and text. The best result with a Mean Average Precision (MAP) of 0.69 indicate that by combining both dimensions we are able to better understand the meaning of our image-caption pairs than when using language or vision information alone. We test the robustness of our gist detection approach when receiving automatically generated input, i.e., using automatically generated image tags or generated captions, and prove the feasibility of an end-to-end automated process

Promoting Active Learning in Computer Science Using Microlabs

Computer science education continues to grow in importance as the technology industry becomes increasingly prevalent on a global scale. In order to remain competitive, computer science education must continue to increase both the quality and quantity of graduates. In efforts to achieve such ends, the Wags system has been designed and developed to be used in conjunction with the Microlab Learning Cycle, an educational process founded in constructivist learning theory. Through continual testing and refinement, the Microlab Learning Cycle and accompanying system have been able to produce measurable improvements in student understanding and retention of important computer science concepts, while providing an active-learning classroom environment that students enjoy and find valuable

A Graph-to-Text Approach to Knowledge-Grounded Response Generation in Human-Robot Interaction

Knowledge graphs are often used to represent structured information in a flexible and efficient manner, but their use in situated dialogue remains under-explored. This paper presents a novel conversational model for human--robot interaction that rests upon a graph-based representation of the dialogue state. The knowledge graph representing the dialogue state is continuously updated with new observations from the robot sensors, including linguistic, situated and multimodal inputs, and is further enriched by other modules, in particular for spatial understanding. The neural conversational model employed to respond to user utterances relies on a simple but effective graph-to-text mechanism that traverses the dialogue state graph and converts the traversals into a natural language form. This conversion of the state graph into text is performed using a set of parameterized functions, and the values for those parameters are optimized based on a small set of Wizard-of-Oz interactions. After this conversion, the text representation of the dialogue state graph is included as part of the prompt of a large language model used to decode the agent response. The proposed approach is empirically evaluated through a user study with a humanoid robot that acts as conversation partner to evaluate the impact of the graph-to-text mechanism on the response generation. After moving a robot along a tour of an indoor environment, participants interacted with the robot using spoken dialogue and evaluated how well the robot was able to answer questions about what the robot observed during the tour. User scores show a statistically significant improvement in the perceived factuality of the robot responses when the graph-to-text approach is employed, compared to a baseline using inputs structured as semantic triples.Comment: Submitted to Dialogue & Discourse 202

Literature in the Arid Zone

This chapter surveys and assesses from an ecocentric perspective some representative literary portrayals of the Australian deserts. Generally, it contrasts works that portray the desert as an alien, hostile, and undifferentiated void with works that recognise and value the biological particularities of specific desert places. It explores the literature of three dominant cultural orientations to the deserts: pastoralism, mining, and traversal. It concludes with a consideration of several multi-voiced and/or multi-genred bioregionally informed works that suggest fruitful directions for more ecocentric literary approaches

The challenges of participatory research with 'tech-savvy' youth

This paper focuses on participatory research and how it can be understood and employed when researching children and youth. The aim of this paper is to provide a theoretically and empirically grounded discussion of participatory research methodologies with respect to investigating the dynamic and evolving phenomenon of young people growing up in networked societies. Initially, we review the nature of participatory research and how other researchers have endeavoured to involve young people (children and youth) in their research projects. Our review of these approaches aims to elucidate what we see as recurring and emerging issues with respect to the methodological design of involving young people as co-researchers. In the light of these issues and in keeping with our aim, we offer a case study of our own research project that seeks to understand the ways in which high school students use new media and network ICT systems (Internet, mobile phone applications, social networking sites) to construct identities, form social relations, and engage in creative practices as part of their everyday lives. The article concludes by offering an assessment of our tripartite model of participatory research that may benefit other researchers who share a similar interest in youth and new media