Evolution of Concept “Black” in the US Media Discourse

Media discourse is an effective tool for projecting and shaping the public perception of a certain idea or image. The article focuses on the linguistic and semantic representation of the concept “Black” in the American media discourse with a particular attention to how the concept representation has evolved from the 1990s to 2010s. The study employed corpus methodology (keyness, frequency, concordances) to analyze news articles from “The New York Times” and “The Los Angeles Times”, which were arranged into three corpora according to the publication date (1990s, 2000s, 2010s). The corpus analysis established a number of changes in the concept “Black” representation manifested primarily through the high relevance keywords and high frequency collocations. Dominant semantic components were identified in the concept representation in each corpus, as well as notable shifts in core and peripheral aspects within these semantic components. The analysis showed that although the semantic components ‘racial / ethnic inequality’ and ‘economic issues’ remain at the core of the concept in each corpus, they are expressed through connections with other semantic components which may vary throughout three decades, such as ‘culture’ in the 1990s, ‘education’ and ‘politics’ in the 2000s and ‘police brutality and profiling’ and ‘appearance’ in the 2010s.

Computational Social Science for Nonprofit Studies: Developing a Toolbox and Knowledge Base for the Field

How can computational social science (CSS) methods be applied in nonprofit and philanthropic studies? This paper summarizes and explains a range of relevant CSS methods from a research design perspective and highlights key applications in our field. We define CSS as a set of computationally intensive empirical methods for data management, concept representation, data analysis, and visualization. What makes the computational methods “social” is that the purpose of using these methods is to serve quantitative, qualitative, and mixed-methods social science research, such that theorization can have a solid ground. We illustrate the promise of CSS in our field by using it to construct the largest and most comprehensive database of scholarly references in our field, the Knowledge Infrastructure of Nonprofit and Philanthropic Studies (KINPS). Furthermore, we show that through the application of CSS in constructing and analyzing KINPS, we can better understand and facilitate the intellectual growth of our field. We conclude the article with cautions for using CSS and suggestions for future studies implementing CSS and KINPS.

A Distributed Network for Multimodal Experiential Representation of Concepts

The architecture of the cortical system underlying concept representation is a topic of intense debate. Much evidence supports the claim that concept retrieval selectively engages sensory, motor, and other neural systems involved in the acquisition of the retrieved concept, yet there is also strong evidence for involvement of high-level, supramodal cortical regions. A fundamental question about the organization of this system is whether modality-specific information originating from sensory and motor areas is integrated across multiple ″convergence zones″ or in a single centralized ″hub″. We used representational similarity analysis (RSA) of fMRI data to map brain regions where the similarity structure of neural patterns elicited by large sets of concepts matched the similarity structure predicted by a high-dimensional model of concept representation based on sensory, motor, affective, and other modal aspects of experience. Across two studies involving different sets of concepts, different participants, and different tasks, searchlight RSA revealed a distributed, bihemispheric network engaged in multimodal experiential representation, composed of high-level association cortex in anterior, lateral, and ventral temporal lobe; inferior parietal lobule; posterior cingulate gyrus and precuneus; and medial, dorsal, ventrolateral, and orbital prefrontal cortex. These regions closely resemble networks previously implicated in general semantic and ″default mode″ processing and are known to be high-level hubs for convergence of multimodal processing streams. Supplemented by an exploratory cluster analysis, these results indicate that the concept representation system consists of multiple, hierarchically organized convergence zones supporting multimodal integration of experiential information.

Decoding the Information Structure Underlying the Neural Representation of Concepts

The nature of the neural code underlying conceptual knowledge remains a major unsolved problem in cognitive neuroscience. Three main types of information have been proposed as candidates for the neural representations of lexical concepts: taxonomic (i.e., information about category membership and inter-category relations), distributional (i.e., information about patterns of word co-occurrence in natural language use), and experiential (i.e., information about sensory-motor, affective, and other features of phenomenal experience engaged during concept acquisition). In two experiments, we investigated the extent to which these three types of information are encoded in the neural activation patterns associated with hundreds of English nouns from a wide variety of conceptual categories. Participants made familiarity judgments on the meaning of written nouns while undergoing functional MRI. A high-resolution, whole-brain activation map was generated for each noun in each participant′s native space. These word-specific activation maps were used to evaluate different representational spaces corresponding to the three types of information described above. In both studies, we found a striking advantage for experience-based models in most brain areas previously associated with concept representation. Partial correlation analyses revealed that only experiential information successfully predicted concept similarity structure when inter-model correlations were taken into account. This pattern of results was found independently for object concepts and event concepts. Our findings indicate that the neural representation of conceptual knowledge primarily encodes information about features of experience, and that - to the extent that it is represented in the brain - taxonomic and distributional information may rely on such an experience-based code.

КОНЦЕПТ «ЛИТЕРАТУРА» В ПЕРЕПИСКЕ И. С. ТУРГЕНЕВА И Ф. М. ДОСТОЕВСКОГО

The article examines the concept of literature as a unit of the linguistic image of the world of two great writers, which is associated with each of the authors’ comprehension and figurative interpretation of the literary process and journalistic activity in the 19th century. Using the letters of Turgenev and Dostoevsky during their conspicuous interaction (1860—1867) the author researches the linguistic methods of concept representation, its semantic volume, identifies a set of semantic features, explores the use of various evaluative vocabulary as a means of explication of this concept, establishes stimulus words in the correspondence. Turgenev perceives the sphere of literature as something true, superior and even miraculous, Dostoevsky proposes both a positive and a negative assessment of the events occurring in the literary process. The analysis of the two writers’ correspondence made it possible to disclose the attitude of correspondents to various literary spheres, to reveal the specific features of the concept of literature in the conceptual sphere of Turgenev and Dostoevsky. Accordingly, it was determined that the language units of the concept of literature as perceived by the Russian intelligentsia contain emotive components, and that the epistolary texts contain elements of intimization and frequent use of authors’ specific language techniques, comparisons and metaphorical images. The notions of literature and the literary process are conceptualized in writers’ letters as an animate acting force, an environment that is capable of action. The figurative language means used by writers in the correspondence endow the concepts with a specific image and sensual meaning. The concept of literature reveals the features of their work, the literary process and journalistic activities, which were an essential part of themselves and their lives for both Turgenev and Dostoevsky.

Computational social science for nonprofit studies: Developing a toolbox and database for the field

How can computational social science (CSS) methods be applied in nonprofit and philanthropic studies? This paper summarizes and explains a range of relevant CSS methods, and highlights key applications in our field. Based on a typical design of empirical social science research, we define CSS as a set of computationally intensive empirical methods for data organization, concept representation, data analysis, and visualization. What makes the computational methods “social” is that the purpose of using these methods is to serve empirical social science research, such that theorization can have a solid ground. We illustrate the promise of CSS in our field by using it to construct the largest and most comprehensive database of scholarly references in our field so far, the Knowledge Infrastructure of Nonprofit and Philanthropic Studies (KINPS). Furthermore, we show that through the application of CSS in the analyses of the KINPS, our field’s knowledge and knowledge producing activities can be advanced, which is a core requisite for the development of our field as a discipline. We conclude the article with cautions for using CSS and suggestions for future research directions implementing CSS and the KINPS.