Always One Bit More, Computing and the Experience of Ambiguity

Fun is often understood to be non-conceptual and indeed without rigour, without relation to formal processes of thought, yielding an intense and joyous informality, a release from procedure. Yet, as this book argues, fun may also be found, alongside other kinds of pleasure, in the generation, iteration and imagination of operations and procedures. This chapter aims to develop a means of drawing out an understanding of fun in relation to concepts of experience in the culture of mathematics and in the machinic fun of certain computer games. Mathematical concepts of experience, as something to be effaced, in terms of the grind of churning out calculations, understood as an acme of human knowledge bordering on the mystical or something both prosaic, peculiar and thrillingly abstract have been crucial to the motivation and genesis of computing. Experience may be figured as something innate to the computing person, or that is abstractable and thus mobile, shifting heterogeneously from one context to another, producing strange affinities between scales – residues and likeness among computational forms that can occasionally link the most austere and mundane or cacophonous of aesthetics. Among such, the fine and perplexing fun of paradox and ambiguity arises not simply in the interplay between formalisms and other kinds of life but as formalisms interweave releasing and congealing further dynamics. There are many ways in which mathematics has been linked to culture as a means of ordering, describing, inspiring or explaining ways of being in the world, but it is less often that mathematics thinks about itself as producing figurations of existence, and such moments are useful to turn to in gaining a sense of some of the patternings of computational culture

The hare and the tortoise: the problems with the notion of action in ethics

Wittgenstein once asked, "What is left over if I subtract the fact that my arm goes up from the fact that I raise my arm?" What would be left is, presumably, the quality of 'agency,' which differentiates between legitimate actions and mere behaviors. In my dissertation I investigate the way we conceive of this quality and recommend a change of the prevalent model for one that is developed in a more empirically informed way. Most current work in ethics employs a historically acquired and folk-psychology approved notion of agency. On this view, the distinction between actions and behaviors is fairly clear-cut. Actions proper are characteristic of human beings. They are 'rational' in either the deliberative process that preceded it or in terms of their efficacy; they are launched `autonomously' by the agent's self rather than influenced by context, emotion or habit. These, and a few other conditions have to be fulfilled for an act to earn the badge of an action; falling short of that standard disqualifies it, or, at the very least renders it an imperfect, faulty instance of agency. An agent is thus typically viewed as a disembodied, rational source of conduct, who can withhold her desires and choose between different courses of action using some form of deliberation. I submit that this model survives neither due to its empirical adequacy nor because it is otherwise valuable for ethics (or, more generally, for understanding human behavior). Rather, there is (I argue), a certain widespread philosophical attitude that determines its persistence--a general longing for the stability of the self and an orderly, controllable relationship between the agent and the world. I call the proponents of this attitude "tortoises" and offer a critique of their main claims. I conclude that we must alter this model. The empirical results from psychology and neuroscience suggest that an agent is best viewed as a bundle of modules that are governed by different rules. None of them is "more" the agent than another, but all operate to achieve a state of homeostasis between so the different processes within the agent and the environment

Negotiating ludic normativity in Facebook meme pages

Title: Negotiating ludic normativity in Facebook meme pages Author: Ondřej Procházka Affiliation: Department of Culture Studies, Tilburg School of Humanities and Digital Sciences This thesis explores the capacity of Internet memes to inflect social realities in the communities organized around them on social media, particularly Facebook. Memes are not mere playful ‘jokes’ or ‘parodies’ spreading virally on the Internet in countless variations, they are also powerful tools for political investment aimed to sway public attention and opinions. Memes have been increasingly documented as a vital component in the unprecedented spread and ‘normalization’ of hateful sentiments and ideologies characterized by ‘fake news’ and ‘post-truth’ politics appealing to emotions rather than ‘facts’ in the digital mainstream. Based on author’s more than five-year observation of communities around Countryball memes, this work argues that much of the socio-cultural and communicative dynamics involving memes can be understood in terms of ludic play. The object of the study – Countryballs memes – are simple meme-comics featuring ball-shaped creatures in colors denoting nation-states while satirically reinventing international ‘drama’ through the prism of socio-cultural and linguistic stereotypes. Having become a household name among memes, Countryballs offer communicative resources to playfully engage not only with wider socio-political issues, but also to with the linguistic, semiotic and ideological boundaries of our communicative norms shaped by the affordances of social media. The present work demonstrates how play can be used as a useful concept for understanding not only how matters of public attention are packed, framed and transmitted in the digital culture via (Countryball) memes, but more importantly how such matters are in fact interpreted by those who engage with them. More specifically, it shows how play enables alternative modes of expression and meaning making with different normative patterns and preferences which stand outside ‘standard’, ‘rational’ or ‘civil’ expectations. And it is precisely ludic play that fosters different types of communication and sociality which are often done ‘just for fun’, however serious or offensive their effects may be. To identify these effects and their implications in the contemporary digital age, the thesis employs a discourse-analytical methodology informed by current advances in digital ethnography and sociolinguistics. It focuses on negotiations among participants in memetic communities about what counts as ‘appropriate’, ‘acceptable’ or ‘correct’ in their socio-communicative behavior. Together in four case studies, the present work provides a comprehensive account of how participants articulate, police, break and re-construct ludic normativity in connection with recent socio-political issues and digital culture at large. This includes the role of memes in the newly emerging forms of communication, in the rise of populism and nationalism, algorithmic manipulation and exploitation, curating digital content and more. The concept of play is continually revisited throughout the discussion against the developments in the scholarship on Internet memes and their ludic genealogy. In doing so, the thesis also revisits some of the traditional concepts such as the notion of ‘community’ and ‘communicative competence’ to arrive at more precise accounts of the concrete processes of globalization and digitalization in our societies and their effects

Development and implementation of in silico molecule fragmentation algorithms for the cheminformatics analysis of natural product spaces

Computational methodologies extracting specific substructures like functional groups or molecular scaffolds from input molecules can be grouped under the term “in silico molecule fragmentation”. They can be used to investigate what specifically characterises a heterogeneous compound class, like pharmaceuticals or Natural Products (NP) and in which aspects they are similar or dissimilar. The aim is to determine what specifically characterises NP structures to transfer patterns favourable for bioactivity to drug development. As part of this thesis, the first algorithmic approach to in silico deglycosylation, the removal of glycosidic moieties for the study of aglycones, was developed with the Sugar Removal Utility (SRU) (Publication A). The SRU has also proven useful for investigating NP glycoside space. It was applied to one of the largest open NP databases, COCONUT (COlleCtion of Open Natural prodUcTs), for this purpose (Publication B). A contribution was made to the Chemistry Development Kit (CDK) by developing the open Scaffold Generator Java library (Publication C). Scaffold Generator can extract different scaffold types and dissect them into smaller parent scaffolds following the scaffold tree or scaffold network approach. Publication D describes the OngLai algorithm, the first automated method to identify homologous series in input datasets, group the member structures of each group, and extract their common core. To support the development of new fragmentation algorithms, the open Java rich client graphical user interface application MORTAR (MOlecule fRagmenTAtion fRamework) was developed as part of this thesis (Publication E). MORTAR allows users to quickly execute the steps of importing a structural dataset, applying a fragmentation algorithm, and visually inspecting the results in different ways. All software developed as part of this thesis is freely and openly available (see https://github.com/JonasSchaub)

Situated creativity-inspired problem-solving

Creativity is a useful attribute for people to have. It allows them to solve unfamiliar problems, introduce novelty to established domains, and to understand and assimilate new information and situations - all things we would like computers to be able to do too. However, these creative attributes do not exist in isolation: they occur in a context in which people tend to solve problems routinely where possible rather than consider non-standard ideas. These more mundane attributes might also be useful for problem solving computers, for the same reasons they are useful for us. However, they are often ignored in attempts to implement systems capable of producing remarkable outputs. We explore how the study of both human and computational creativity can inform an approach to help computers to display useful, complete problem-solving behaviour similar to our own: that is, robust, exible and, where possible and appropriate, surprising. We describe a knowledge-based model that incorporates a genetic algorithm with some characteristics of our own approach to knowledge reuse. The model is driven by direct interactions with problem scenarios. Descriptions of the role or appearance of key themes and concepts in literature in functioning problem-solving systems is lacking; we suggest that they appear as artefacts of the operation of our model. We demonstrate that it is capable of solving routine problems flexibly and effectively. We also demonstrate that it can solve problems that would be effectively impossible for a genetic algorithm operating without the benefit of knowledge-driven biasing. Artefacts of the behaviour of the model could, in certain scenarios, lead to the appearance of non-routine or surprising solutions

Applying blended conceptual spaces to variable choice and aesthetics in data visualisation

Computational creativity is an active area of research within the artificial intelligence domain that investigates what aspects of computing can be considered as an analogue to the human creative process. Computers can be programmed to emulate the type of things that the human mind can. Artificial creativity is worthy of study for two reasons. Firstly, it can help in understanding human creativity and secondly it can help with the design of computer programs that appear to be creative. Although the implementation of creativity in computer algorithms is an active field, much of the research fails to specify which of the known theories of creativity it is aligning with. The combination of computational creativity with computer generated visualisations has the potential to produce visualisations that are context sensitive with respect to the data and could solve some of the current automation problems that computers experience. In addition theories of creativity could theoretically compute unusual data combinations, or introducing graphical elements that draw attention to the patterns in the data. More could be learned about the creativity involved as humans go about the task of generating a visualisation. The purpose of this dissertation was to develop a computer program that can automate the generation of a visualisation, for a suitably chosen visualisation type over a small domain of knowledge, using a subset of the computational creativity criteria, in order to try and explore the effects of the introduction of conceptual blending techniques. The problem is that existing computer programs that generate visualisations are lacking the creativity, intuition, background information, and visual perception that enable a human to decide what aspects of the visualisation will expose patterns that are useful to the consumer of the visualisation. The main research question that guided this dissertation was, “How can criteria derived from theories of creativity be used in the generation of visualisations?”. In order to answer this question an analysis was done to determine which creativity theories and artificial intelligence techniques could potentially be used to implement the theories in the context of those relevant to computer generated visualisations. Measurable attributes and criteria that were sufficient for an algorithm that claims to model creativity were explored. The parts of the visualisation pipeline were identified and the aspects of visualisation generation that humans are better at than computers was explored. Themes that emerged in both the computational creativity and the visualisation literature were highlighted. Finally a prototype was built that started to investigate the use of computational creativity methods in the ‘variable choice’, and ‘aesthetics’ stages of the data visualisation pipeline.School of ComputingM. Sc. (Computing

The emerging landscape of Social Media Data Collection: anticipating trends and addressing future challenges

[spa] Las redes sociales se han convertido en una herramienta poderosa para crear y compartir contenido generado por usuarios en todo internet. El amplio uso de las redes sociales ha llevado a generar una enorme cantidad de información, presentando una gran oportunidad para el marketing digital. A través de las redes sociales, las empresas pueden llegar a millones de consumidores potenciales y capturar valiosos datos de los consumidores, que se pueden utilizar para optimizar estrategias y acciones de marketing. Los beneficios y desafíos potenciales de utilizar las redes sociales para el marketing digital también están creciendo en interés entre la comunidad académica. Si bien las redes sociales ofrecen a las empresas la oportunidad de llegar a una gran audiencia y recopilar valiosos datos de los consumidores, el volumen de información generada puede llevar a un marketing sin enfoque y consecuencias negativas como la sobrecarga social. Para aprovechar al máximo el marketing en redes sociales, las empresas necesitan recopilar datos confiables para propósitos específicos como vender productos, aumentar la conciencia de marca o fomentar el compromiso y para predecir los comportamientos futuros de los consumidores. La disponibilidad de datos de calidad puede ayudar a construir la lealtad a la marca, pero la disposición de los consumidores a compartir información depende de su nivel de confianza en la empresa o marca que lo solicita. Por lo tanto, esta tesis tiene como objetivo contribuir a la brecha de investigación a través del análisis bibliométrico del campo, el análisis mixto de perfiles y motivaciones de los usuarios que proporcionan sus datos en redes sociales y una comparación de algoritmos supervisados y no supervisados para agrupar a los consumidores. Esta investigación ha utilizado una base de datos de más de 5,5 millones de colecciones de datos durante un período de 10 años. Los avances tecnológicos ahora permiten el análisis sofisticado y las predicciones confiables basadas en los datos capturados, lo que es especialmente útil para el marketing digital. Varios estudios han explorado el marketing digital a través de las redes sociales, algunos centrándose en un campo específico, mientras que otros adoptan un enfoque multidisciplinario. Sin embargo, debido a la naturaleza rápidamente evolutiva de la disciplina, se requiere un enfoque bibliométrico para capturar y sintetizar la información más actualizada y agregar más valor a los estudios en el campo. Por lo tanto, las contribuciones de esta tesis son las siguientes. En primer lugar, proporciona una revisión exhaustiva de la literatura sobre los métodos para recopilar datos personales de los consumidores de las redes sociales para el marketing digital y establece las tendencias más relevantes a través del análisis de artículos significativos, palabras clave, autores, instituciones y países. En segundo lugar, esta tesis identifica los perfiles de usuario que más mienten y por qué. Específicamente, esta investigación demuestra que algunos perfiles de usuario están más inclinados a cometer errores, mientras que otros proporcionan información falsa intencionalmente. El estudio también muestra que las principales motivaciones detrás de proporcionar información falsa incluyen la diversión y la falta de confianza en las medidas de privacidad y seguridad de los datos. Finalmente, esta tesis tiene como objetivo llenar el vacío en la literatura sobre qué algoritmo, supervisado o no supervisado, puede agrupar mejor a los consumidores que proporcionan sus datos en las redes sociales para predecir su comportamiento futuro