Linguistic Representation of Power in Edward Bond’s Lear: A Lexico-Pragmatic Approach to Critical Discourse Analysis

This paper investigates the linguistic representation of power in Edward Bond’s Lear (1978). More specifically, the paper tries to explore the extent to which power is linguistically represented manipulatively and/or persuasively by means of specific lexical and pragmatic devices in the discourse of the selected play. The main objective of the paper is to explore how power relations, irrespective of their type, influence the cognitive world of the discourse participants, which in turn attempts a change in their conversational behavior to the extent that allows the acceptance of a specific argument in a particular way. The paper adopts a lexico-pragmatic perspective to Critical Discourse Analysis (CDA), instanced by Fairclough’s (1989) lexical model for the analysis of discourse, and the concepts of politeness and face (Thomas, 1995; Yule, 1996a). The main research question of the paper is: to what extent do different power relations, encoded lexically and/or pragmatically, affect the conversational behavior of the play’s characters, persuasively and/or manipulatively? Some lexical and pragmatic strategies have been highlighted and then linguistically analyzed to expose their effectiveness in deciphering persuasive and manipulative power relations in the selected play. Among these strategies are: euphemism, myth-making, positive self-presentation and negative other-presentation, and politeness strategies. The paper concludes that power has linguistically been encoded in the discourse of the selected play, both persuasively and manipulatively, to affect a cognitive shift in behavior reflected in the conversational interaction among characters.

Perceptions on Authenticity in Chat Bots

In 1950, Alan Turing proposed his concept of universal machines, emphasizing their abilities to learn, think, and behave in a human-like manner. Today, the existence of intelligent agents imitating human characteristics is more relevant than ever. They have expanded to numerous aspects of daily life. Yet, while they are often seen as work simplifiers, their interactions usually lack social competence. In particular, they miss what one may call authenticity. In the study presented in this paper, we explore how characteristics of social intelligence may enhance future agent implementations. Interviews and an open question survey with experts from different fields have led to a shared understanding of what it would take to make intelligent virtual agents, in particular messaging agents (i.e., chat bots), more authentic. Results suggest that showcasing a transparent purpose, learning from experience, anthropomorphizing, human-like conversational behavior, and coherence, are guiding characteristics for agent authenticity and should consequently allow for and support a better coexistence of artificial intelligence technology with its respective users.

Combining heterogeneous inputs for the development of adaptive and multimodal interaction systems

In this paper we present a novel framework for the integration of visual sensor networks and speech-based interfaces. Our proposal follows the standard reference architecture in fusion systems (JDL), and combines different techniques related to Artificial Intelligence, Natural Language Processing and User Modeling to provide an enhanced interaction with their users. Firstly, the framework integrates a Cooperative Surveillance Multi-Agent System (CS-MAS), which includes several types of autonomous agents working in a coalition to track and make inferences on the positions of the targets. Secondly, enhanced conversational agents facilitate human-computer interaction by means of speech interaction. Thirdly, a statistical methodology allows modeling the user conversational behavior, which is learned from an initial corpus and improved with the knowledge acquired from the successive interactions. A technique is proposed to facilitate the multimodal fusion of these information sources and consider the result for the decision of the next system action.

Talking theory of mind talk: young school-aged children's everyday conversation and understanding of mind and emotion

ABSTRACTLinks between young children's everyday use of mindful conversational skills and their success on laboratory tests of theory of mind understanding (ToM) were evaluated. Using published scales, teachers rated the conversational behavior and shyness of 129 children aged 60 to 101 months (M = 78·8 months) who were in their first years of primary school. The children also took batteries of first- and second-order false-belief tests along with tests of emotion understanding and general language ability. Correlational and regression analyses showed that performance on false-belief tests of ToM significantly predicted children's competence at reading others' minds in their everyday conversational interactions. Furthermore, these links transcended individual differences in language ability, shy personality, emotion understanding, and age. These findings augment and extend a growing body of evidence linking performance on laboratory ToM tests to socially competent real-world behavior.