Limen, portal, network subjectivities

The ambiguity of the term 'network subjectivities' is enticing: is there a subjectivity proper to networks? Is that subjectivity itself distributed? The inference in each case is that there is or has been a subjectivity that is or was not networked in either sense. It follows then that there must be a passage between non- or pre-networked subjectivity and networked, a threshold. Anne Friedman's work would suggest that the key threshold is the human-computer interface, the physical display and the software interface that appears in it. Her analysis concerns the actual, but subjectivity also concerns the potential. To pursue that we need to look at imaginary (fictitious, experimental) accounts of thresholds between worlds. This paper looks at liminal spaces and portals in popular culture as evidence for the potential of subjectivities in transition between IRL or individualist subjectivity towards networks and networking. From Odysseus' visit to the gates of the underworld and Orpheus' rescue of Eurydice, all the way to Malevich's black icon, the liminal has been approached with ritual and trepidation. Transitions between worlds retain their magic in the Narnia books of C.S. Lewis and the tesseract of Interstellar, but lose their ritual and their power to demand awe and fear in the promise of easy, cost-free travel between the mundane world and any one of thousands of networked worlds. Such transitions, we know from our GPS trackers, do not involve a change of place; therefore they must involve a change of state, whose essence will be temporal rather than spatial, and thus also historical. The major historical change of the period covering the rise of network communications has been the rise of dataveillance, and its corollary, the real subsumption of consumption under capital. With the approaching exhaustion or higher risks associated with the extraction of natural resources, capital turns to the exploitation of human nature, notably through mapping behaviours as predictors of future activity, exploiting the creativity of interactors as unpaid sources of innovation, and personal debt. The derivatives market in debt producers the singular temporality of contemporary network capital and its subjectivity. This paper follows the histories that have produced this condition, including those of individuation, the construction of states of affairs as data, and the variety of terms frequently used as binary opposites of truth, each constitutive of a different kind of subject. This analysis prompts a definition of ideology as the intersection of the wishful and the paranoid, a position characterisable as subjunctive that should be taken as the typical form of network subjectivity as liminal. This in turn suggests two further hypotheses, that the category and the reality of the human has become environmental, that is treated as economic externality and as divorced from the core of the social; and that this alienated, subjunctive, mass subject is now in process of dissolving its links with the subjectivity as sovereignty, to replace it with the grounds for a new sociality. The challenge of the present conjuncture is therefore to construct a new 'we' capable of expressing the newly interdependent networks, not only of communications, but of ecological and technological imbrication of humans and non-humans, in a new politics

Anotacijska shema i njezina evaluacija: primjer uvredljivoga jezika

The present paper focuses on the presentation and discussion of aspects of OFFENSIVE LANGUAGE linguistic annotation, including the creation, annotation practice, curation, and evaluation of an OFFENSIVE LANGUAGE annotation taxonomy scheme, that was first proposed in Lewandowska-Tomaszczyk et al. (2021). An extended offensive language ontology comprising 17 categories, structured in terms of 4 hierarchical levels, has been shown to represent the encoding of the defined offensive language schema, trained in terms of non-contextual word embeddings – i.e., Word2Vec and Fast Text, and eventually juxtaposed to the data acquired by using a pair wise training and testing analysis for existing categories in the HateBERT model (Lewandowska-Tomaszczyk et al. submitted). The study reports on the annotation practice in WG 4.1.1. Incivility in media and social media in the context of COST Action CA 18209 European network for Web-centred linguistic data science (Nexus Linguarum) with the INCEpTION tool (https://github.com/inception-project/inception) – a semantic annotation platform offering assistance in the annotation. The results partly support the proposed ontology of explicit offense and positive implicitness types to provide more variance among widely recognized types of figurative language (e.g., metaphorical, metonymic, ironic, etc.). The use of the annotation system and the representation of linguistic data were also evaluated in a series of the annotators’ comments, by means of a questionnaire and an open discussion. The annotation results and the questionnaire showed that for some of the categories there was low or medium inter-annotator agreement, and it was more challenging for annotators to distinguish between category items than between aspect items, with the category items offensive, insulting and abusive being the most difficult in this respect. The need for taxonomic simplification measures on the basis of these results has been recognized for further annotation practices.U ovome je radu predstavljen proces označavanja uvredljivoga jezika koji uključuje izradu klasifikacije toga jezika, označivačku praksu, vođenje procesa i evaluaciju. Klasifikacijska je shema prvi put predložena u Lewandowska-Tomaszczyk i dr. (2021). Proširena ontologija uvredljivoga jezika sadrži 17 kategorija posloženih u četiri hijerarhijske razine te tako predstavlja shemu uvredljivoga jezika koja je trenirana u okviru nekontekstualiziranih vektorskih prikaza riječi (engl. word embeddings) poput Word2Vec i Fast Text koji su naposljetku supostavljeni podatcima prikupljenima korištenjem analize parova i analize testiranja za postojeće kategorije u modelu HateBERT (Lewandowska-Tomaszczyk i dr., u postupku recenzije). U radu se izvještava o označivačkoj praksi u okviru radne grupe WG 4.1.1. Incivility in media and social media COST-ove akcije CA 18209 European network for Web-centred linguistic data science (Nexus Linguarum). Označavanje je provedeno u alatu INCEpTION (https://github.com/inception-project/inception) – platformi za semantičko označavanje koja ima ugrađene alate za takvu obradu podataka. Dobiveni rezultati podupiru predloženu ontologiju eksplicitnoga i implicitnoga uvredljivog jezika koja omogućuje veću raznovrsnost među već prepoznatim tipovima figurativnoga jezika (primjerice metafora, metonimija, ironija itd.). Upotreba sustava za označavanje i prikazivanje jezičnih podataka također je procijenjena u povratnim komentarima koje su pružili označivači. Komentari označivača prikupljeni su metodom upitnika te otvorenom raspravom. Na kraju je usustavljen niz preporuka za buduće označivačke prakse

Intelligent Information Access to Linked Data - Weaving the Cultural Heritage Web

The subject of the dissertation is an information alignment experiment of two cultural heritage information systems (ALAP): The Perseus Digital Library and Arachne. In modern societies, information integration is gaining importance for many tasks such as business decision making or even catastrophe management. It is beyond doubt that the information available in digital form can offer users new ways of interaction. Also, in the humanities and cultural heritage communities, more and more information is being published online. But in many situations the way that information has been made publicly available is disruptive to the research process due to its heterogeneity and distribution. Therefore integrated information will be a key factor to pursue successful research, and the need for information alignment is widely recognized. ALAP is an attempt to integrate information from Perseus and Arachne, not only on a schema level, but to also perform entity resolution. To that end, technical peculiarities and philosophical implications of the concepts of identity and co-reference are discussed. Multiple approaches to information integration and entity resolution are discussed and evaluated. The methodology that is used to implement ALAP is mainly rooted in the fields of information retrieval and knowledge discovery. First, an exploratory analysis was performed on both information systems to get a first impression of the data. After that, (semi-)structured information from both systems was extracted and normalized. Then, a clustering algorithm was used to reduce the number of needed entity comparisons. Finally, a thorough matching was performed on the different clusters. ALAP helped with identifying challenges and highlighted the opportunities that arise during the attempt to align cultural heritage information systems

Barry Smith an sich

Festschrift in Honor of Barry Smith on the occasion of his 65th Birthday. Published as issue 4:4 of the journal Cosmos + Taxis: Studies in Emergent Order and Organization. Includes contributions by Wolfgang Grassl, Nicola Guarino, John T. Kearns, Rudolf Lüthe, Luc Schneider, Peter Simons, Wojciech Żełaniec, and Jan Woleński

AN ENSEMBLE MODEL FOR CLICK THROUGH RATE PREDICTION

Internet has become the most prominent and accessible way to spread the news about an event or to pitch, advertise and sell a product, globally. The success of any advertisement campaign lies in reaching the right class of target audience and eventually convert them as potential customers in the future. Search engines like the Google, Yahoo, Bing are a few of the most used ones by the businesses to market their product. Apart from this, certain websites like the www.alibaba.com that has more traffic also offer services for B2B customers to set their advertisement campaign. The look of the advertisement, the maximum bill per day, the age and gender of the audience, the bid price for the position and the size of the advertisement are some of the key factors that are available for the businesses to tune. The businesses are predominantly charged based the number of clicks that they received for their advertisement while some websites also bill them with a fixed charge per billing cycle. This creates a necessity for the advertising platforms to analyze and study these influential factors to achieve the maximum possible gain through the advertisements. Additionally, it is equally important for the businesses to customize these factors rightly to achieve the maximum clicks. This research presents a click through rate prediction system that analyzes several of the factors mentioned above to predict if an advertisement will receive a click or not with improvements over the existing systems in terms of the sampling the data, the features used, and the methodologies handled to improve the accuracy. We used the ensemble model with weighted scheme and achieved an accuracy of 0.91 on a unit scale and predicted the probability for an advertisement to receive a click form the user

Modeling and design of heterogeneous hierarchical bioinspired spider web structures using generative deep learning and additive manufacturing

Spider webs are incredible biological structures, comprising thin but strong silk filament and arranged into complex hierarchical architectures with striking mechanical properties (e.g., lightweight but high strength, achieving diverse mechanical responses). While simple 2D orb webs can easily be mimicked, the modeling and synthesis of 3D-based web structures remain challenging, partly due to the rich set of design features. Here we provide a detailed analysis of the heterogenous graph structures of spider webs, and use deep learning as a way to model and then synthesize artificial, bio-inspired 3D web structures. The generative AI models are conditioned based on key geometric parameters (including average edge length, number of nodes, average node degree, and others). To identify graph construction principles, we use inductive representation sampling of large experimentally determined spider web graphs, to yield a dataset that is used to train three conditional generative models: 1) An analog diffusion model inspired by nonequilibrium thermodynamics, with sparse neighbor representation, 2) a discrete diffusion model with full neighbor representation, and 3) an autoregressive transformer architecture with full neighbor representation. All three models are scalable, produce complex, de novo bio-inspired spider web mimics, and successfully construct graphs that meet the design objectives. We further propose algorithm that assembles web samples produced by the generative models into larger-scale structures based on a series of geometric design targets, including helical and parametric shapes, mimicking, and extending natural design principles towards integration with diverging engineering objectives. Several webs are manufactured using 3D printing and tested to assess mechanical properties