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Sarti, Alessandro; Citti, Giovanna; Piotrowski, David
doi: 10.1515/sem-2018-0109pmid: N/A
AbstractIn this study, we analyse the notion of “differential heterogenesis” proposed by Deleuze and Guattari on a morphogenetic perspective. We propose a mathematical framework to envisage the emergence of singular forms from the assemblages of heterogeneous operators. In opposition to the kind of differential calculus that is usually adopted in mathematical-physical modelling, which tends to assume a homogeneous differential equation applied to an entire homogeneous region, heterogenesis allows differential constraints of qualitatively different kinds in different points of space and time. These constraints can then change in time, opening the possibility for new kinds of differential dynamics and the emergence of distinct entities and forms. Formally, we show that operators with different phase spaces can be assembled on the basis of a result of Rothschild & Stein (1976. Hypoelliptic differential operators and nilpotent groups. Acta Mathematica 137. 247–320). Furthermore, operators with different dynamics can be assembled by means of a partition of the unit.After stating the concept of differential heterogenesis in terms of contemporary mathematics, we show that this construction sheds light on the constitution of the semiotic function. In fact, both the Merleau-Pontian and the Deleuzian approaches share a common conceptualisation of the semiotic function and its emergence in terms of a morphodynamics of heterogeneous assemblages with a divergent actualisation. This divergent actualisation allows the co-constitution of various expression and content planes. Finally, we show that the divergent actualisation can be interpreted as the directions of principal eigenvectors of the actualized flow.
Chartier, Jean-François; Pulizzotto, Davide; Chartrand, Louis; Meunier, Jean-Guy
doi: 10.1515/sem-2018-0120pmid: N/A
AbstractThe rise of big digital data is changing the framework within which linguists, sociologists, anthropologists, and other researchers are working. Semiotics is not spared by this paradigm shift. A data-driven computational semiotics is the study with an intensive use of computational methods of patterns in human-created contents related to semiotic phenomena. One of the most promising frameworks in this research program is the Semantic Vector Space (SVS) models and their methods. The objective of this article is to contribute to the exploration of the SVS for a computational semiotics by showing what types of semiotic analysis can be accomplished within this framework. The study is applied to a unique body of digitized artworks. We conducted three short experiments in which we explore three types of semiotic analysis: paradigmatic analysis, componential analysis, and topic modelling analysis. The results reported show that the SVS constitutes a powerful framework within which various types of semiotic analysis can be carried out.
Reyes, Everardo; Sonesson, Göran
doi: 10.1515/sem-2018-0106pmid: N/A
AbstractIn this paper we summarize observations bridging the declared aspirations of pictorial semiotics and its real achievements. Pictorial semiotics is here understood as the general study of pictures as signs and it constituted a fundamental step beyond the art historical captivation with individual images. In the first part of our contribution we present a review of the most important methods that have been proposed as an answer to deal with several pictorial problems (multiple instances, segmentation, non-figurative meaning). In the second part, we offer some positive and on-going implementations designed to remedy the shortcomings observed. What is suggested is the proof of concept that human researchers need the assistance of computing methodologies. However, computers can only do their job once an adequate phenomenology of human experience is fed into the process.
Reboul, Marianne; Gefen, Alexandre
doi: 10.1515/sem-2018-0103pmid: N/A
Résumé L’analyse quantitative de l’histoire culturelle a été ouverte par la mise à disposition de corpus de masse tel que celui de Google fbooks (500 milliards de mots, 5 millions d’ouvrages, soit environ 4% de la littérature mondiale) et a été popularisé sous le nom de « culturonomics ». Elle s’ouvre désormais aux chercheurs, en promettant un accès profond aux faits culturels et à leurs évolutions qui affleurent à travers leurs traces textuelles dans les corpus textuelles numérisées. Encore faut-il pouvoir interroger ces corpus dont la taille et la nature posent des problèmes scientifiques nouveaux, leur dimension les rendant illisibles directement et mettant échec les méthodes de fouille et les outils traditionnels d’analyse statistique des données en imposant des méthodes statistiques nouvelles et le saut vers des formes d’intelligence visuelles originales. Dans le cadre d’un projet mené entre le Labex « Obvil » de Paris-Sorbonne et le Literary Lab de Stanford sur l’histoire de l’idée de littéraire (la définition de la littérature comme mot, comme concept et comme champ), et visant à produire une histoire empirique de la littérature, nous avons mené depuis deux ans des expériences de fouille d’un corpus de critique littéraire de 1618 titres, 140 millions de mots (dont plus de 50 000 occurrences du lemme « littérature ») de la fin de l’Ancien Régime à la Seconde Guerre mondiale. En présentant des exemples développés dans cette première expérimentation à grande échelle de mesure de l’histoire des idées, on présentera les méthodes de text mining contemporaines en essayant d’éprouver leur pertinence heuristique et de leur capacité à faire remonter des données signifiantes pour l’histoire et la théorie littéraire. On fera l’hypothèse que toute enquête quantitative sérieuse mobilise désormais non une échelle intermédiaire standard et immédiatement lisible, mais le maniement d’outils statistiques dont l’interprétation en sciences humaines pose des problèmes particuliers qui, paradoxalement, ne peuvent être résolus que par leur articulation étroite à du close reading et à des mesures fines.
doi: 10.1515/sem-2018-0104pmid: N/A
AbstractIn this article we explore the relationship between semiotic analysis of images and quantitative analysis of vast image corpora, in particular the work produced by Lev Manovich and the Cultural Analytics Lab, called “Media Visualization.” Media Visualization has been chosen as corpus because of its metavisual operation (images are visualized and analyzed by images) and its innovating way of conceiving analysis: by visual instruments. In this paper semiotics is used as an approach to Media Visualization and taken as an object of study as well, especially visual semiotics. In this sense, a comparison between visual semiotics (close reading of small corpora) and quantitative analyses of images (distant reading of vast collections) are conducted from a semiotic point of view. Post-Greimassian semiotics guides this study with respect to the issue of the image-within-an-image and metavisual visualization; Peircean semiotics is employed to explain and develop the notion of diagram.
doi: 10.1515/sem-2018-0114pmid: N/A
AbstractThe myth of transparency and truthfulness is the foundation for contemporary theories of information design. Avoiding distortion and ambiguity is the moral imperative of an upstanding data visualizer. Sometimes, though, data that is collected is not accurate enough and the sources use indirect indicators to approach a phenomenon: what to do then, if the need to graphically represent a phenomenon is urgent and necessary? Should the designer wait to have the exact data, or should he indicate a trend, expressing the hypothetical status of his statement? Can data visualization be designed to express doubt rather than to inform about facts?This essay will deal with the forms of expression of uncertainty in infographics. It will consider the designer as both an observer and a translator, whose position of neutrality is only one of the possible realms of discourse. In general, it will focus on the forms of visual expression of a self-criticizing mood in quantitative research today and it will explore the ways in which data that is not meaningful in statistical terms can become meaningful in semiotic terms.
doi: 10.1515/sem-2018-0105pmid: N/A
Abstract La cartographie thématique vise à produire des représentations visuelles de données comportant une dimension spatiale. Structurée dans les années 1970 selon une approche explicitement sémiotique, elle s’est peu à peu détachée des recherches dans ce domaine pour se stabiliser autour de pratiques largement standardisées. Ce constat, et celui de l’écart avec ce que peut produire une approche plus artistique par des infographistes, a motivé une recherche d’outils accessibles pour aider à comprendre cette sémiose. On a tout d’abord cherché à saisir la complexité des images cartographiques pour tenter d’en simplifier leur perception et interprétation. Les outils d’analyse de l’attention visuelle ont apporté des résultats encourageants. Ensuite, on s’est intéressés à la couleur : comment découvrir des compositions colorées plus expressives ? Dans la peinture ? On a ensuite cherché à assister la composition de dégradés de couleurs tirés de sources picturales. Ces idées ont pu être mises en pratique et évaluées grâce au support Internet : il est possible de proposer des traitements complexes de manière accessible et rapide. Ces outils sont décrits sur un carnet de recherche Hypothèses.org, tout en ouvrant le code source. Cela pourrait ouvrir la voie à une étude plus poussée des capacités expressives des signes plastiques utilisés en infographie.
Crémier, Lucile; Bonenfant, Maude; Lafrance St-Martin, Laura Iseut
doi: 10.1515/sem-2018-0110pmid: N/A
AbstractThe large-scale and intensive collection and analysis of digital data (commonly called “Big Data”) has become a common, popular, and consensual research method for the social sciences, as the automation of data collection, mathematization of analysis, and digital objectification reinforce both its efficiency and truth-value. This article opens with a critical review of the literature on data collection and analysis, and summarizes current ethical discussions focusing on these technologies. A semiotic model of data production and circulation is then introduced to problematize the view that digital data has ceased to stand for a formalization method (a possible kind of representation among others), and effectively “becomes the world itself” (a direct presentation of the world outperforming all other modes of representation). Following Charles Sanders Peirce’s semiotics and pragmaticist philosophy, we characterize digitalization as a hypersymbolic semiotic process, and we highlight the naturalization of meaning, the illusion of iconicity, and rhetorical efficiency on which data’s truth value relies within the context of its large-scale, profit-driven, and results-oriented research uses. This outlines some epistemological and ethical implications of data’s visualization, use, and authority, and indicates avenues for critical semiotics of contemporary data science and analysis.
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