Information and Experience in Metaphor: A Perspective From Computer Analysis

Novel linguistic metaphor can be seen as the assignment of attributes to a topic through a vehicle belonging to another domain. The experience evoked by the vehicle is a significant aspect of the meaning of the metaphor, especially for abstract metaphor, which involves more than mere physical similarity. In this article I indicate, through description of a specific model, some possibilities as well as limitations of computer processing directed toward both informative and experiential/affective aspects of metaphor. A background to the discussion is given by other computational treatments of metaphor analysis, as well as by some questions about metaphor originating in other disciplines. The approach on which the present metaphor analysis model is based is consistent with a theory of language comprehension that includes both the intent of the originator and the effect on the recipient of the metaphor. The model addresses the dual problem of (a) determining potentially salient properties of the vehicle concept, and (b) defining extensible symbolic representations of such properties, including affective and other connotations. The nature of the linguistic analysis underlying the model suggests how metaphoric expression of experiential components in abstract metaphor is dependent on the nominalization of actions and attributes. The inverse process of undoing such nominalizations in computer analysis of metaphor constitutes a translation of a metaphor to a more literal expression within the metaphor-nonmetaphor dichotomy

ssMousetrack: Analysing computerized tracking data via Bayesian state-space models in {R}

Recent technological advances have provided new settings to enhance individual-based data collection and computerized-tracking data have became common in many behavioral and social research. By adopting instantaneous tracking devices such as computer-mouse, wii, and joysticks, such data provide new insights for analysing the dynamic unfolding of response process. ssMousetrack is a R package for modeling and analysing computerized-tracking data by means of a Bayesian state-space approach. The package provides a set of functions to prepare data, fit the model, and assess results via simple diagnostic checks. This paper describes the package and illustrates how it can be used to model and analyse computerized-tracking data. A case study is also included to show the use of the package in empirical case studies

Co-thought and Co-speech Gestures Are Generated by the Same Action Generation Process

We thank Lucy Foulkes, Rachel Furness, Valentina Lee, and Zeshu Shao for their help with data collection; Paraskevi Argyriou for her help with reliability checks of gesture coding; and Agnieszka Konopka and Josje Praamstra for their help with proofreading this article.Peer reviewedPostprin

A rapid prototyping/artificial intelligence approach to space station-era information management and access

Applications of rapid prototyping and Artificial Intelligence techniques to problems associated with Space Station-era information management systems are described. In particular, the work is centered on issues related to: (1) intelligent man-machine interfaces applied to scientific data user support, and (2) the requirement that intelligent information management systems (IIMS) be able to efficiently process metadata updates concerning types of data handled. The advanced IIMS represents functional capabilities driven almost entirely by the needs of potential users. Space Station-era scientific data projected to be generated is likely to be significantly greater than data currently processed and analyzed. Information about scientific data must be presented clearly, concisely, and with support features to allow users at all levels of expertise efficient and cost-effective data access. Additionally, mechanisms for allowing more efficient IIMS metadata update processes must be addressed. The work reported covers the following IIMS design aspects: IIMS data and metadata modeling, including the automatic updating of IIMS-contained metadata, IIMS user-system interface considerations, including significant problems associated with remote access, user profiles, and on-line tutorial capabilities, and development of an IIMS query and browse facility, including the capability to deal with spatial information. A working prototype has been developed and is being enhanced

Toddlers Benefit from Labeling on an Executive Function Search Task

Although labeling improves executive function (EF) performance in children older than 3 (e.g., Kirkham, Cruess, & Diamond, 2003), the results from studies with younger children have been equivocal (e.g., Sophian & Wellman, 1983). In the present study, we assessed performance in a computerized multistep multilocation search task with older 2-year-old children. The correct search location was either: (a) not marked by a familiar picture nor given a distinct label, (b) marked by a familiar picture but not given a distinct label (c) marked by a familiar picture and labeled by the experimenter, or (d) marked by a familiar picture and labeled by the participant. The results revealed that accuracy improved across conditions such that children made fewest errors when they generated the label for the hiding location. These findings support the hierarchical competing systems model (Marcovitch & Zelazo, 2006, 2009) that postulates that improved performance can be explained by more powerful representations that guide search behavior