Knowledge Modelling and Learning through Cognitive Networks

One of the most promising developments in modelling knowledge is cognitive network science, which aims to investigate cognitive phenomena driven by the networked, associative organization of knowledge. For example, investigating the structure of semantic memory via semantic networks has illuminated how memory recall patterns influence phenomena such as creativity, memory search, learning, and more generally, knowledge acquisition, exploration, and exploitation. In parallel, neural network models for artificial intelligence (AI) are also becoming more widespread as inferential models for understanding which features drive language-related phenomena such as meaning reconstruction, stance detection, and emotional profiling. Whereas cognitive networks map explicitly which entities engage in associative relationships, neural networks perform an implicit mapping of correlations in cognitive data as weights, obtained after training over labelled data and whose interpretation is not immediately evident to the experimenter. This book aims to bring together quantitative, innovative research that focuses on modelling knowledge through cognitive and neural networks to gain insight into mechanisms driving cognitive processes related to knowledge structuring, exploration, and learning. The book comprises a variety of publication types, including reviews and theoretical papers, empirical research, computational modelling, and big data analysis. All papers here share a commonality: they demonstrate how the application of network science and AI can extend and broaden cognitive science in ways that traditional approaches cannot

Imagining Workers: The Working-Class Presence in Late Nineteenth-Century American Literature. (Volumes I and II).

This dissertation examines how late nineteenth-century American realist and naturalist narratives defuse the working-class drive for class self-determination and political power. The texts examined are Rebecca Harding Davis\u27s Life in the Iron Mills (1861), Elizabeth Stuart Phelps\u27s The Silent Partner (1871), Henry James\u27s The Princess Casamassima (1886), William Dean Howells\u27s A Hazard of New Fortunes (1890) and Theodore Dreiser\u27s Sister Carrie (1900). Each work is examined in the context of a specific proletarian insurgency that was taking place at roughly the same time, and sometimes the same place, in which the author was writing. Each text bears the impress of specific attempts by proletarians to represent themselves through activism and mass action. These proletarian attempts at self-representation become historically knowable to the extent that they at once resist and abet literary representation. Thus, while each literary text attempts to denature the emergent working-class presence in the body politic, that presence persists, often as a kind of absent or negative image of itself. Working-class presence inspires disruptions in the usual realist time-order narration, for instance, and it deeply affects plot, setting, characterization and metaphor use. Further, because realism and naturalism define themselves in the literary marketplace through rendering empirically precise, objective pictures of society, these texts cannot simply erase workers from the narrative. Working-class presence certainly poses a threat to the class privileges of the middle-class authors and readers of nineteenth-century fiction, but it also provides an opportunity for those writers and readers to carve their niche in the emerging power structure of consumer capitalism. Thus instead of eliding working-class presence, realist and naturalist narratives at once depict it and imaginatively manage the threats it poses to the status quo. Realist and naturalist writings are at once drawn to and repulsed by the scenes of proletarian insurrection that marked the late nineteenth century. The resultant writing-under-erasure of workers and worker power deeply determines American literature

Spatial and Temporal Sentiment Analysis of Twitter data

The public have used Twitter world wide for expressing opinions. This study focuses on spatio-temporal variation of georeferenced Tweets’ sentiment polarity, with a view to understanding how opinions evolve on Twitter over space and time and across communities of users. More specifically, the question this study tested is whether sentiment polarity on Twitter exhibits specific time-location patterns. The aim of the study is to investigate the spatial and temporal distribution of georeferenced Twitter sentiment polarity within the area of 1 km buffer around the Curtin Bentley campus boundary in Perth, Western Australia. Tweets posted in campus were assigned into six spatial zones and four time zones. A sentiment analysis was then conducted for each zone using the sentiment analyser tool in the Starlight Visual Information System software. The Feature Manipulation Engine was employed to convert non-spatial files into spatial and temporal feature class. The spatial and temporal distribution of Twitter sentiment polarity patterns over space and time was mapped using Geographic Information Systems (GIS). Some interesting results were identified. For example, the highest percentage of positive Tweets occurred in the social science area, while science and engineering and dormitory areas had the highest percentage of negative postings. The number of negative Tweets increases in the library and science and engineering areas as the end of the semester approaches, reaching a peak around an exam period, while the percentage of negative Tweets drops at the end of the semester in the entertainment and sport and dormitory area. This study will provide some insights into understanding students and staff ’s sentiment variation on Twitter, which could be useful for university teaching and learning management

Seeking the Self in Pigment and Pixels: Postmodernism, Art, and the Subject

In this study, I examine how works of art become vehicles for the postmodern inquiry into the nature of subjectivity. My thesis narrows the focus to those characters who attempt to ground themselves in works of art, especially representational paintings. I argue that, to cope with what they see as the chaos of a decentered postmodern world, these figures try to anchor their confused identities in what they wrongfully interpret as stable and mimetic artworks. Nostalgic for an imagined past when representation was transparent and corresponded to reality, they believe that traditional figurative art offers the promise of cohesive meaning otherwise lacking under postmodernism. Their views of art, therefore, underwrite a desire and nostalgia for absolutes that are non-existent. In their failure to ground themselves in images, we see the fundamental instability of both the subject and of art. The wayward individuals that I examine yearn for art objects to come to life in order to confirm their own selfhood. What they seek, then, is to transform art-objects into art-subjects; this Pygmalionesque project is grounded in the futile hope that the art-object can reciprocate their desires. We find literary examples of this trend in the characters I analyze in my first two chapters: notably the narrator(s) of John Banville’s Frames Trilogy and the gay spies of the fictionalized Cambridge Five. In my final chapter, I look to the clones and androids of popular culture and explore the real life example of Japanese love-doll owners. In each of these instances, artworks are strategically positioned as sites of ontological anchorage, but this foundation can never be secure under postmodernism. Despite their fervent hopes, these characters have misplaced their trust in a form of representation that is no more stable than any other aspect of the postmodern condition. I argue that Freddie, Victor, Tommy, and Tavo, among others, are particularly good examples of the vexed relationship between the image and the self

Recent Advances in Social Data and Artificial Intelligence 2019

The importance and usefulness of subjects and topics involving social data and artificial intelligence are becoming widely recognized. This book contains invited review, expository, and original research articles dealing with, and presenting state-of-the-art accounts pf, the recent advances in the subjects of social data and artificial intelligence, and potentially their links to Cyberspace