![]() ![]() The question, "What is Cognitive Science?" is often asked but seldom answered to anyone's satisfaction. ![]() The results of the two studies suggest that FDT can deliver semantic representations that correlate with those that emerge from aggregations of features norms, and can cluster fairly homogeneous categories and subcategories of related concepts. This chapter presents the Flickr Distributional Tagspace (FDT), a distributional semantic space built on Flickr tag co-occurrences, and evaluates it follows: 1) through a comparison between the semantic representations that it produces, and those that are obtained from speaker generated features norms collected in experimental setting, as well as with WordNet-based metrics of semantic similarity between words 2) through a categorization task and a consequent cluster analysis. by relying on the idea that concepts that appear in similar contexts have similar meanings (e.g. ![]() ![]() This is achieved by means of distributional semantics, i.e. Mining the emergent semantic patterns of these complex open- ended large-scale bodies of uncoordinated annotations provided by humans is the goal of this chapter. Such annotations could provide genuine insights on salient aspects emerging from the personal experiences that have been captured in the picture, which range beyond the purely visual features, or the language-based associations. An additional content analysis, also reported here, shows that the type of semantic information encoded in the related tags (i.e., the contexts on which the contingency matrices of this distributional method are built) differs, in relation to the modality of the metaphor: while situation-related and entity-related features are typically associated with concepts aligned in visual metaphors, introspections, and taxonomic features are typically associated with concepts aligned in linguistic metaphors.įlickr users tag their personal pictures with a variety of keywords. These findings suggest that the relational similarity between two metaphor terms (captured and modeled through FDT) is crucial for visual metaphors but not for linguistic metaphors. The present study, conducted through FDT, found that visual and linguistic metaphors behave differently, in that the similarity between two aligned concepts in a visual metaphor appears to be significantly higher than the similarity between two concepts aligned in a linguistic metaphor (which, in turn, does not differ substantially from the similarity between two randomly paired concepts). A comprehensive theory, which argues in favor of the conceptual nature of metaphor, cannot afford to be biased toward the analysis and modeling of one specific modality of expression, thus neglecting potential modality-specific differences. A long established view in metaphor theory claims that metaphors pertain to the conceptual dimension of meaning, but while different models aim at explaining how language constructs and represents metaphorical conceptual structures, we still know very little about how other modalities (for example, images) achieve metaphor construction and expression. As explained in the article, this distributional model, Flickr Distributional Tagspace (FDT), captures primarily relational similarity between concept pairs, that is, between tags that appear in similar tagsets (and therefore in similar pictures). This study aims at modeling the semantic similarity between metaphor terms by means of a distributional method based on a Big Data stream: Flickr tags. ![]()
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