Elaboration of the New Paradigm of Interdisciplinary Investigations

In the article, the problem of construction a meta-theory for approaching the complex phenomena of Reality is discussed. The integrated information system is formulated. Such postulate is a suggested basis for creation of a unified methodology of cognition (investigation) which makes it possible to elaborate a new paradigm of interdisciplinary investigations as a separate scientific discipline which has its own methods and special objects. The article will be of interest to philosophers and methodologists of scienc

Review of Edward Branigan, Narrative Comprehension and Film. London and New York: Routledge, 1992. (Distributed by the Law Book Company Ltd.). 325pp. ISBN 0415075114. (pbk), $45.00.

If Point of View in the Cinema introduced its author as one of the leading film analysts by its attention to the details of the process of cinematic presentation, Narrative Comprehension and Film establishes Edward Branigan as a creative theorist beyond the boundaries of film. The book's voice is that of a craftsman speaking from his workshop. No deconstructive symplok and certainly no rhetorical terrorism. Instead, we find a certain modesty of style, which is deceptive considering that Branigan offers a great deal of substance and a range of attractive speculative insights. The author's mastery of technical intricacies within the broader frame of general narrative makes Narrative Comprehension and Film an outstanding teaching book for film studies as well as other disciplines in the humanities. What makes it especially appealing is its careful elaboration of an inferential account of how we make sense of narrative. For this and other reasons, it is well worth paying closer attention than is perhaps usual for a review article to how the book's argument unfolds and in particular to how it manages to relate the double argument about narrative in film and human perception as interpretive construals

Comments to Neutrosophy

Any system based on axioms is incomplete because the axioms cannot be proven from the system, just believed. But one system can be less-incomplete than other. Neutrosophy is less-incomplete than many other systems because it contains them. But this does not mean that it is finished, and it can always be improved. The comments presented here are an attempt to make Neutrosophy even less-incomplete. I argue that less-incomplete ideas are more useful, since we cannot perceive truth or falsity or indeterminacy independently of a context, and are therefore relative. Absolute being and relative being are defined. Also the "silly theorem problem" is posed, and its partial solution described. The issues arising from the incompleteness of our contexts are presented. We also note the relativity and dependance of logic to a context. We propose "metacontextuality" as a paradigm for containing as many contexts as we can, in order to be less-incomplete and discuss some possible consequences

Local Tomography of Large Networks under the Low-Observability Regime

This article studies the problem of reconstructing the topology of a network of interacting agents via observations of the state-evolution of the agents. We focus on the large-scale network setting with the additional constraint of $partial$ observations, where only a small fraction of the agents can be feasibly observed. The goal is to infer the underlying subnetwork of interactions and we refer to this problem as $local$ $tomography$. In order to study the large-scale setting, we adopt a proper stochastic formulation where the unobserved part of the network is modeled as an Erd\"{o}s-R\'enyi random graph, while the observable subnetwork is left arbitrary. The main result of this work is establishing that, under this setting, local tomography is actually possible with high probability, provided that certain conditions on the network model are met (such as stability and symmetry of the network combination matrix). Remarkably, such conclusion is established under the $low$-$observability$ $regime$, where the cardinality of the observable subnetwork is fixed, while the size of the overall network scales to infinity.Comment: To appear in IEEE Transactions on Information Theor

Quantifying the Effect of Sentiment on Information Diffusion in Social Media

Social media have become the main vehicle of information production and consumption online. Millions of users every day log on their Facebook or Twitter accounts to get updates and news, read about their topics of interest, and become exposed to new opportunities and interactions. Although recent studies suggest that the contents users produce will affect the emotions of their readers, we still lack a rigorous understanding of the role and effects of contents sentiment on the dynamics of information diffusion. This work aims at quantifying the effect of sentiment on information diffusion, to understand: (i) whether positive conversations spread faster and/or broader than negative ones (or vice-versa); (ii) what kind of emotions are more typical of popular conversations on social media; and, (iii) what type of sentiment is expressed in conversations characterized by different temporal dynamics. Our findings show that, at the level of contents, negative messages spread faster than positive ones, but positive ones reach larger audiences, suggesting that people are more inclined to share and favorite positive contents, the so-called positive bias. As for the entire conversations, we highlight how different temporal dynamics exhibit different sentiment patterns: for example, positive sentiment builds up for highly-anticipated events, while unexpected events are mainly characterized by negative sentiment. Our contribution is a milestone to understand how the emotions expressed in short texts affect their spreading in online social ecosystems, and may help to craft effective policies and strategies for content generation and diffusion.Comment: 10 pages, 5 figure