Repairs and old-age categorisations: interactional and categorisation analysis

This paper examines the use of self-repairs in ascribing old-age categorisations to self and others in casual interactions among friends. Membership categorisation analysis and conversation analysis are employed to analyse self-recorded, everyday conversations of a group of older Greek Cypriot women with a long interactional history. The interactional organisation of old-age labels, and specifically instances of self-repair of age categorisations, reveal that members orient to old-age categories as hierarchically positioned and inference-rich. Members make relevant a very intricate set of expectations of who can be categorised by whom, with what specific age category term and at which context, partly because other-categorisations can also implicate one’s self-categorisation as old. Sequential and categorisation analyses provide a powerful analytical toolkit for the investigation of participants’ local system of self- and other-ascription of explicit -but also implicit- age identities. It is shown that the combination of membership categorisation analysis and conversation analysis can be extended beyond the analysis of turn-generating categories and can be instrumental in analysing flexible, context-shaped and agentively managed category identifications that also have currency beyond the local interactional occasion

Repairs and old-age categorisations: interactional and categorisation analysis

This paper examines the use of self-repairs in ascribing old-age categorisations to self and others in casual interactions among friends. Membership categorisation analysis and conversation analysis are employed to analyse self-recorded, everyday conversations of a group of older Greek Cypriot women with a long interactional history. The interactional organisation of old-age labels, and specifically instances of self-repair of age categorisations, reveal that members orient to old-age categories as hierarchically positioned and inference-rich. Members make relevant a very intricate set of expectations of who can be categorised by whom, with what specific age category term and at which context, partly because other-categorisations can also implicate one’s self-categorisation as old. Sequential and categorisation analyses provide a powerful analytical toolkit for the investigation of participants’ local system of self- and other-ascription of explicit -but also implicit- age identities. It is shown that the combination of membership categorisation analysis and conversation analysis can be extended beyond the analysis of turn-generating categories and can be instrumental in analysing flexible, context-shaped and agentively managed category identifications that also have currency beyond the local interactional occasion

Hierarchical word clustering - automatic thesaurus generation

In this paper, we propose a hierarchical, lexical clustering neural network algorithm that automatically generates a thesaurus (synonym abstraction) using purely stochastic information derived from unstructured text corpora and requiring no prior word classifications. The lexical hierarchy overcomes the Vocabulary Problem by accommodating paraphrasing through using synonym clusters and overcomes Information Overload by focusing search within cohesive clusters. We describe existing word categorisation methodologies, identifying their respective strengths and weaknesses and evaluate our proposed approach against an existing neural approach using a benchmark statistical approach and a human generated thesaurus for comparison. We also evaluate our word context vector generation methodology against two similar approaches to investigate the effect of word vector dimensionality and the effect of the number of words in the context window on the quality of word clusters produced. We demonstrate the effectiveness of our approach and its superiority to existing techniques. (C) 2002 Elsevier Science B.V. All rights reserved

A frame signature matrix for analysing and comparing interaction design behaviour

Protocol studies are an established method to investigate design behaviour. In the context of a project to investigate novice interaction design (ID) behaviour across protocols and cultures, we found that existing design behaviour analysis frameworks did not provide reliable results. This paper describes the development of a new approach to analyse and compare ID behaviour using verbal protocols. We augment Schön’s basic design and reflection cycle with construction of a frame signature matrix and analogical categorisation coding. We demonstrate this approach by comparing two protocols of novice interaction designers in Botswana. The initial findings indicate that this approach increases consistency and accuracy of coding, and that there are different degrees of reframing for the design problem and solutions

Similarity and categorisation: getting dissociations in perspective

Dissociations between similarity and categorization have constituted critical counter-evidence to the view that categorization is similarity-based. However, there have been difficulties in replicating such dissociations. This paper reports three experiments. The first provides evidence of a double dissociation between similarity and categorization. The second and third show that by asking participants to make their judgments from particular perspectives, this dissociation disappears or is much reduced. It is argued that these data support a perspectival view of concepts, in which categorization is similarity-based, but where the dimensions used to make similarity and categorization judgments are partially fixed by perspective

Metaphor as categorisation: a connectionist implementation

A key issue for models of metaphor comprehension is to explain how in some metaphorical comparison , only some features of B are transferred to A. The features of B that are transferred to A depend both on A and on B. This is the central thrust of Black's well known interaction theory of metaphor comprehension (1979). However, this theory is somewhat abstract, and it is not obvious how it may be implemented in terms of mental representations and processes. In this paper we describe a simple computational model of on-line metaphor comprehension which combines Black's interaction theory with the idea that metaphor comprehension is a type of categorisation process (Glucksberg & Keysar, 1990, 1993). The model is based on a distributed connectionist network depicting semantic memory (McClelland & Rumelhart, 1986). The network learns feature-based information about various concepts. A metaphor is comprehended by applying a representation of the first term A to the network storing knowledge of the second term B, in an attempt to categorise it as an exemplar of B. The output of this network is a representation of A transformed by the knowledge of B. We explain how this process embodies an interaction of knowledge between the two terms of the metaphor, how it accords with the contemporary theory of metaphor stating that comprehension for literal and metaphorical comparisons is carried out by identical mechanisms (Gibbs, 1994), and how it accounts for both existing empirical evidence (Glucksberg, McGlone, & Manfredi, 1997) and generates new predictions. In this model, the distinction between literal and metaphorical language is one of degree, not of kind

Do Social Bots Dream of Electric Sheep? A Categorisation of Social Media Bot Accounts

So-called 'social bots' have garnered a lot of attention lately. Previous research showed that they attempted to influence political events such as the Brexit referendum and the US presidential elections. It remains, however, somewhat unclear what exactly can be understood by the term 'social bot'. This paper addresses the need to better understand the intentions of bots on social media and to develop a shared understanding of how 'social' bots differ from other types of bots. We thus describe a systematic review of publications that researched bot accounts on social media. Based on the results of this literature review, we propose a scheme for categorising bot accounts on social media sites. Our scheme groups bot accounts by two dimensions - Imitation of human behaviour and Intent.Comment: Accepted for publication in the Proceedings of the Australasian Conference on Information Systems, 201

The listening talker: A review of human and algorithmic context-induced modifications of speech

International audienceSpeech output technology is finding widespread application, including in scenarios where intelligibility might be compromised - at least for some listeners - by adverse conditions. Unlike most current algorithms, talkers continually adapt their speech patterns as a response to the immediate context of spoken communication, where the type of interlocutor and the environment are the dominant situational factors influencing speech production. Observations of talker behaviour can motivate the design of more robust speech output algorithms. Starting with a listener-oriented categorisation of possible goals for speech modification, this review article summarises the extensive set of behavioural findings related to human speech modification, identifies which factors appear to be beneficial, and goes on to examine previous computational attempts to improve intelligibility in noise. The review concludes by tabulating 46 speech modifications, many of which have yet to be perceptually or algorithmically evaluated. Consequently, the review provides a roadmap for future work in improving the robustness of speech output

Dissimilarity is used as evidence of category membership in multidimensional perceptual categorization: a test of the similarity-dissimilarity generalized context model

In exemplar models of categorization, the similarity between an exemplar and category members constitutes evidence that the exemplar belongs to the category. We test the possibility that the dissimilarity to members of competing categories also contributes to this evidence. Data were collected from two 2-dimensional perceptual categorization experiments, one with lines varying in orientation and length and the other with coloured patches varying in saturation and brightness. Model fits of the similarity-dissimilarity generalized context model were used to compare a model where only similarity was used with a model where both similarity and dissimilarity were used. For the majority of participants the similarity-dissimilarity model provided both a significantly better fit and better generalization, suggesting that people do also use dissimilarity as evidence

A literature review of analytical techniques for materials characterisation of painted textiles - Part 1: categorising painted textiles, sampling and the use of optical tools

Many types of painted textile are represented in museum collections. Their flexibility, draping qualities, and heterogeneous, layered nature make painted textiles complex objects to conserve. What do we know about their materials and making? There has been limited research into painted textiles and particularly their analysis. Whilst much valuable information can be gleaned from paintings analysis, there are many distinct differences in materials behaviour between stretched paintings and painted textiles that need to be identified and addressed. This paper, together with Part 2, aims to raise the awareness of textile conservators, in particular, of potential analytical techniques to identify and characterise the materials, thus enhancing understanding and conservation of painted textiles. Part 1 focuses firstly, on the categorisation of different groups of painted textile providing a context for their study and secondly, it reviews sampling and optical techniques that can be used by conservators, highlighting some of the challenges they present