Computational Knowledge Representation in Cognitive Science

2019 ◽  
Vol 56 (3) ◽  
pp. 138-152
Author(s):  
Igor F. Mikhailov ◽  
Keyword(s):  
Knowledge Representation ◽  
Cognitive Science ◽  
Network Architecture ◽  
Mathematical Theory ◽  
Computational Approach ◽  
Formal Epistemology ◽  
The Social ◽  
Parallel Network ◽  
Substrate Independent ◽  
Computational Systems

Cognitive research can contribute to the formal epistemological study of knowledge representation inasmuch as, firstly, it may be regarded as a descriptive science of the very same subject as that, of which formal epistemology is a normative one. And, secondly, the notion of representation plays a constitutive role in both disciplines, though differing therein in shades of its meaning. Representation, in my view, makes sense only being paired with computation. A process may be viewed as computational if it adheres to some algorithm and is substrate-independent. Traditionally, psychology is not directly determined by neuroscience, sticking to functional or dynamical analyses in the what-level and skipping mechanistic explanations in the how-level. Therefore, any version of computational approach in psychology is a very promising move in connecting the two scientific realms. On the other hand, the digital and linear computational approach of the classical cognitive science is of little help in this way, as it is not biologically realistic. Thus, what is needed there on the methodological level, is a shift from classical Turing-style computationalism to a generic computational theory that would comprehend the complicated architecture of neuronal computations. To this end, the cutting-edge cognitive neuroscience is in need of а satisfactory mathematical theory applicable to natural, particularly neuronal, computations. Computational systems may be construed as natural or artificial devices that use some physical processes on their lower levels as atomic operations for algorithmic processes on their higher levels. A cognitive system is a multi-level mechanism, in which linguistic, visual and other processors are built on numerous levels of more elementary operations, which ultimately boil down to atomic neural spikes. The hypothesis defended in this paper is that knowledge derives not only from an individual computational device, such as a brain, but also from the social communication system that, in its turn, may be presented as a kind of supercomputer of the parallel network architecture. Therefore, a plausible account of knowledge production and exchange must base on some mathematical theory of social computations, along with that of natural, particularly neuronal, ones.

scholarly journals Automated Classification of Fake News Spreaders to Break the Misinformation Chain

Information ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 248
Author(s):  
Simone Leonardi ◽  
Giuseppe Rizzo ◽  
Maurizio Morisio
Keyword(s):  
Social Media ◽  
Network Architecture ◽  
Diffusion Mechanism ◽  
Automated Classification ◽  
Fake News ◽  
Neural Network Architecture ◽  
User Classification ◽  
The Social ◽  
Network Topologies

In social media, users are spreading misinformation easily and without fact checking. In principle, they do not have a malicious intent, but their sharing leads to a socially dangerous diffusion mechanism. The motivations behind this behavior have been linked to a wide variety of social and personal outcomes, but these users are not easily identified. The existing solutions show how the analysis of linguistic signals in social media posts combined with the exploration of network topologies are effective in this field. These applications have some limitations such as focusing solely on the fake news shared and not understanding the typology of the user spreading them. In this paper, we propose a computational approach to extract features from the social media posts of these users to recognize who is a fake news spreader for a given topic. Thanks to the CoAID dataset, we start the analysis with 300 K users engaged on an online micro-blogging platform; then, we enriched the dataset by extending it to a collection of more than 1 M share actions and their associated posts on the platform. The proposed approach processes a batch of Twitter posts authored by users of the CoAID dataset and turns them into a high-dimensional matrix of features, which are then exploited by a deep neural network architecture based on transformers to perform user classification. We prove the effectiveness of our work by comparing the precision, recall, and f1 score of our model with different configurations and with a baseline classifier. We obtained an f1 score of 0.8076, obtaining an improvement from the state-of-the-art by 4%.

scholarly journals Paradox of integration — mean field approach

2017 ◽  
Vol 28 (11) ◽  
pp. 1750133 ◽  
Author(s):  
Krzysztof Kułakowski ◽  
Piotr Gronek ◽  
Alfio Borzì
Keyword(s):  
Social Status ◽  
Positive Emotions ◽  
Mean Field ◽  
Computational Approach ◽  
Transient Time ◽  
Field Approach ◽  
The Social ◽  
The Mean ◽  
High Social Status

Recently, a computational model has been proposed of the social integration, as described in sociological terms by Blau. In this model, actors praise or critique each other, and these actions influence their social status and raise negative or positive emotions. The role of a self-deprecating strategy of actors with high social status has also been discussed there. Here, we develop a mean field approach, where the active and passive roles (praising and being praised, etc.) are decoupled. The phase transition from friendly to hostile emotions has been reproduced, similarly to the previously applied purely computational approach. For both phases, we investigate the time dependence of the distribution of social status. There we observe a diffusive spread, which — after some transient time — appears to be limited from below or from above, depending on the phase. As a consequence, the mean status flows.

scholarly journals Representação e ciências sociais

2016 ◽  
Vol 1 (1) ◽  
pp. 109-126
Author(s):  
Drance Elias da Silva
Keyword(s):  
Social Sciences ◽  
Knowledge Representation ◽  
Human Life ◽  
Point Of View ◽  
General View ◽  
Dominant Culture ◽  
The Real ◽  
The Social ◽  
Long Time ◽  
Expression Form

This Article may be situated within the rapport field between Philosophy and Social Sciences, at the search regarding to the concept concerning the Representation. Regarding to Philosophy, under a general view, the concept, concerning Representation, has been, since a long time, understood as a trail which one would get througl reaching to the real and true ones. Representation, as the thought contents expression form had not been known departing from Philosophy as a barrier against the objectivity concerning the knowledge. Representation, in its source, has been constituting itself a cognictive, inmanent reflection, related to the conscience inner subjectivity. But departing from the episthemological point of view, it has been not so easy for the campus concerning the Culture Sciences as a totality. In the theory regarding to knowledge, the Social Sciences campus and, more specifically, in the human life Symbolic dimension constitutive aspects, it has been, often, accepted negatively as an entry door for the histotical social reality. Nowadays, one may conclude that the contents concerning the Culture are deeply rooted within the histotical reality, which may present new dimension the reading regarding to the Symbolical side concerning the human life, under the view regarding to the unseen aspect, such as the intellectualistic Western dominant Culture allows understanding the way which could be in.

scholarly journals Das Leben ist ein Spiel

2000 ◽  
Vol 43 (4) ◽  
pp. 315-326
Author(s):  
A. Grauvogl
Keyword(s):  
Sexual Reproduction ◽  
Mathematical Theory ◽  
Social Aspects ◽  
Genetic Elements ◽  
The Social ◽  
The Difference

Abstract. Title of the paper: Life is a game Sexual reproduction causes the independent combination of genetic elements. But not only the physiology of reproduction but also behavioural physiology is familiär with independent combinations; in this case the behavioural elements while playing. An attempt is made to analyse and discover the difference between the playing behaviour of animals versus the playing behaviour of humans during childhood. The mathematical theory of game also is based upon selective choice. The social aspects of play in animal and human collectives is explained as well as the possibilities of therapeutical games.

scholarly journals The contribution of cognitive anthropolinguistics to educational linguistics

1999 ◽  
Vol 1 ◽  
pp. 119
Author(s):  
José Manuel Martín Morillas
Keyword(s):  
Social Sciences ◽  
Cognitive Science ◽  
Cross Cultural ◽  
Social Psychological ◽  
Central Concept ◽  
Educational Linguistics ◽  
The Social ◽  
Pedagogical Grammar ◽  
The Relationship ◽  
And Linguistics

In this paper it is argued that, despite the welcome psycho-social emphasis in educational linguistic theories witnessed in recent decades, and with it, a rapprochement of the social sciences to the psychological sciences, the relationship between these fields has not gone far enough. The actual challenge is a move towards the unification of the social, psychological and language sciences (anthropology and sociology; cognitive science; and linguistics). A step in this interdisciplinary direction is offered by the discipline called 'cognitive anthropolinguistics', and its central concept of 'cultural cognition'. The paper discusses the implication of this concept for the field of educational linguistics, followed by a brief illustration of a cognitive-cultural application of that concept, namely the concept of 'ethnic stereotype', as part of a socio-cultural guide for a cross-cultural pedagogical grammar.

Designing a Socially Open Narrative Generation System

2016 ◽  
pp. 91-117 ◽  
Author(s):  
Taisuke Akimoto ◽  
Takashi Ogata
Keyword(s):  
Computer Program ◽  
Mechanism Design ◽  
Social Process ◽  
Social Activity ◽  
Computational Approach ◽  
Generation System ◽  
Narrative Generation ◽  
The Social ◽  
Key Concepts ◽  
Generation Technology

The authors propose the design of a Socially Open Narrative Generation System (SONGS) that co-creates a collection of diverse narratives from a narrative generation program and people. This is a challenge of the social application of narrative generation technology used for vitalizing the social activity of producing and sharing narratives. The key idea is to connect and unify individual narrative productions by many agents, including a computer program and many humans, via a collection of narratives produced and accumulated by these agents. At the same time, SONGS is the practice of a computational approach to narratology as a model for the social process of narrative production. This chapter describes the key concepts and mechanism design of SONGS with several experimental programs.

A Novel Hierarchical Group-Based Overlay Healthcare Network

2017 ◽  
Vol 8 (4) ◽  
pp. 81-102
Author(s):  
Foteini Andriopoulou ◽  
Konstantinos Birkos ◽  
Dimitrios Lymberopoulos
Keyword(s):  
Network Architecture ◽  
Response Times ◽  
Healthcare Services ◽  
Peer To Peer ◽  
Dynamic Features ◽  
Healthcare Network ◽  
The Social ◽  
Peer To Peer Networks ◽  
Secure Network ◽  
Structured Overlays

In the healthcare domain, there is a challenge on how to design a scalable, dynamic, robust and secure network for provisioning personalized healthcare services remotely with an efficient and accurate manner. In the present work, motivated by innovations in the networking domain and the benefits of clustering in the peer-to-peer networks as well as the group-based approach of the social networks, we propose a novel hierarchical peer-to-peer overlay healthcare network for communication and collaboration among healthcare professionals, paramedical staff and patients. The proposed network includes two types of hierarchy: the first type is used for regular requests and communication while the second type handles emergency requests. The network architecture is based on multiple and enhanced structured overlays that provide scalability, dynamic features, load-balancing and low response times with guaranteed information retrieval. Moreover, a novel and effective lookup mechanism supports complex queries with significantly lower response time and messaging overhead.

Vygotsky and cognitive science: Language and the unification of the social and computational mind. William Frawley. Cambridge, MA: Harvard University Press, 1997. Pp. 384.

2000 ◽  
Vol 21 (3) ◽  
pp. 425-426 ◽  
Author(s):  
Diane Beals
Keyword(s):  
Information Processing ◽  
Cognitive Science ◽  
Human Mind ◽  
Harvard University ◽  
Computational Approaches ◽  
The Social ◽  
Sociocultural Theories ◽  
Ways Of Thinking ◽  
Important Position

Vygotsky's social psycholinguist approach is not incompatible with computational approaches to the study of mind. In this way William Frawley sets the stage for a Vygoskyan cognitive science. Socioculturalists' theorizing on the work of the human mind has long maintained boundaries against cognitive science's information processing approaches and language, and vice versa. Frawley argues that no such division is entirely necessary and offers powerful ways of linking the two ways of thinking. Frawley's background in both Vygotskyan and other sociocultural theories, as well as in cognitive science and computational theories, places him in an important position to make these links.

Modeling The Tower Of Hanoi Using Neural Network

1993 ◽  
pp. 47-56
Author(s):  
Mohamed Othman ◽  
Mohd. Hassan Selamat ◽  
Zaiton Muda ◽  
Lili Norliya Abdullah
Keyword(s):  
Neural Network ◽  
Knowledge Representation ◽  
Network Architecture ◽  
Learning Algorithm ◽  
Learning Rule ◽  
Neural System ◽  
Neural Systems ◽  
Tower Of Hanoi ◽  
Artificial Neural ◽  
The Given

This paper discusses the modeling of Tower of Hanoi using the concepts of neural network. The basis idea of backpropagation learning algorithm in Artificial Neural Systems is then described. While similar in some ways, Artificial Neural System learning deviates from tradition in its dependence on the modification of individual weights to bring about changes in a knowledge representation distributed across connection in a network. This unique form of learning is analyzed from two aspects: the selection of an appropriate network architecture for representing the problem, and the choice of a suitable learning rule capable qf reproducing the desired function within the given network. Key words: Tower of Hanoi; Backpropagation Algorithm; Knowledge Representation;

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