information among networks and systems of knowledge

José María Díaz NafríaSENESCYT – University of Santa Elena, Ecuador | Universidad de León, Spain | Hochschule München, Germany

Context

2INFORMATION: among networks and systems of knowledge

Contents

1. Abstract Networks2. Information and

Interaction models3. Semantic & knowledge

networks4. The study of

information


Abstract Networks

• Essentially, a network is just a set of nodes and linkssuch that there is a characteristic structure of connections among the nodes.

• Abstraction: What we see in the drawing is in fact, a representation of the network rather than the network itself. Hence, what we deal with is a mathematical graph, and as such we define this as a set of verticesand edges.


Abstract Networks

• The abstraction (parallel to representation) achieves a kind of universalization. (Observe we have not defined the meaning of nodes and links so far). Up to now, we simply deal with a formaltype of representation.

• Connection in nature usually implies interaction. This is the reason for visualizing links in a network as expression for interactions among nodes.

• The idea is that the dynamics of an observable phenomenology is inherent in a diagram which is static itself.

• In principle, the main point of the diagrammatic graphism is to express what cannot be expressed by a drawing alone: motion.

• It is the link in a network, or the edge of its representation, that stands for this motion.


Abstract Networks

• We usually deal with diagrams whose vertices are just points and whose edges are directedlines (commonly indicated by the head of an arrow).

• Vertices are visualized as agents that operate onto other agents by means of their respective interaction.

• We characterize the type of agent and the type of interaction (usually codified by labels or colours).

• Relevant difference between internal and external types of interaction (active/passive).

• We visualize the effect of one agent on the other as information.


N1

N3N2

I1,2I2,1

Information

• What is information?• If we only refer to signals exchange (MTC): what one agent is

doing to the other is reducing the uncertainty (s)he has with respect to the transmitted signals.

• Which is the case within a finite set of given signals/messages?


Z=Si{S1, S2,… SN}

Noise

Z’=Si’ Comparing with{S1, S2,… SN}

Si=X

Uncertainty: {p1, p2,… pN}

Ni Nj

Information

Initial uncertainty

1 bit of Information

Reduced uncertainty



Reduced uncertainty

Certainty

{p1, p2,… pN}, here: pi =1/M

What is the case? I = log2 (N = No. choices) = - log2 (1/N) = - log2 p

s1 s2 s3 s4 s5 s6 s7 s8

INFORMATION: among networks and systems of knowledge

Information

Information (MTC)syn:


Information has however 3 clear dimensions: syntactic | semantic | pragmatic

Information (AIT)synt-sem:

Two adittional essential aspects (Weizäcker): potentiality | actuality

→

Interaction model (communication)

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“The fundamental problem of communication is that of reproducing at one point either exactly or approximately a message selected at another point. Frequently the messages have meaning; that is they refer to or are correlated according to some system with certain physical or conceptual entities. These semantic aspects of communication are irrelevant to the engineering problem.” (Shannon, 1948)



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MTC aims at solving the technical problem:• Removing noise• Minimal resources for a given information amount• Maximal throughput for some given channel resourcesTo this purpose it needed:1. Quantitative information account (decontextualized)2. Not interfering in semantic and pragmatic questions (good postman)


Source Coder DestinationDecoder

Original Message Coded

Message

DecodifiedMessage

Noise

Canal

Noiseless Channel (transparent)Code: {m1, m2,… mN}Rules (grammar)

Code: {m1, m2,… mN}Rules (grammar)

Code: {m’1, m’2,… m’N}Rules (grammar)

Code: {m’1, m’2,… m’N}Rules (grammar)

?

12


“the signs of general ideas, and ideas become general, by separating from them the circumstances of time and place, and any other ideas that may determine them to this or that particular existence.” (J. Locke, ECHU, 1690)

Jul. 2014 Cuestión semántica

Technical model of digital communication (syntactic-semantic)

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1) the emitter (according to some convention ~ code) to communicate X sends Z;

2) the receptor, after receiving Z accompanied by a certain amount of noise, holds the

hypothesis that the emitter tried to communicate X.

1’) the emitter (according to some convention ~ code) ‘to do X’, being C the contextperceived by emitter, transmits Z;

2’) the receptor, after receiving Z accompanied by a certain amount of noise, being C’the context it perceives, holds the hypothesis that the emitter tried ‘to do X’.

Inferential model of communication (semantopragmatic)

The efficiency of communication in the inferential model lie in:1st the amount of noise is low enough so that receptor is not

mistaken, which will depend on the difference among the signals used in the code.

2nd the perceived contexts at both sides are close enough, 3rd the code is complex enough in order to make possible not only the

perception of the semantic content but also what may be considered of a higher logic level: ‘what is tried to be done when a signal Z is sent’.

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Recursive model for an interacting agent:

15



1’’) The agent, perceiving Zn‐1 in a context C’, decides to do Xn. In order to reach itand according with a convention CV’, Zn (communicative act) is done

Schema of agent’s life:• Sequence of decisions {..., Xn-2, Xn-1, Xn, ...}, • taken towards a sequence of objectives

{..., On-2, On-1, On, ...}, • together with actions that are done {..., Zn-2,

Zn-1, Zn, ...}

N1

N3N2

I1,2I2,1

Semantic Network

16Information: among networks and systems of knowledge

In an abstract network we can differentiate interactions as • internal (if caused by active agents, as before) and • external (if caused by different active agents –communicators, knowers-

that utilize passive agents –words, concepts-).

This difference also implies a difference of representations: namely whether they are utilized in order to map:• potentialities (as in the case of geographic maps or semantic networks of

concepts) or• actualities (as in the case of dynamic processes, e.g. concerning the

communication between persons).

Semantic Network (passive-active)


Semantic Network Analysis of Twitter reaction to court decision (Huang):• We see here an actualization of the semantic network to reflect a kind of theory about

what was the case, driven by strong prejudices.

In the realm of scientific knowledge:• We find an actualization of

the concept network reflecting the theories about what is the case in a given field, driven by definitions and axioms.



Semantic Network Analysis of Tweets in South-Korean Presidential Election Debates (Park et al.)

1st2nd

3rdIssue Network



In the previous case we visualize the dynamics of social relevance concerning political issues (at the national level):• The issue network maps the social relevance, as an average of the communicative

interaction of communicative agents (people)• Each agent has an inherent semantic network (conscious and un-conscious)

ISi

ISkISj

Ii,jIj,i

E[{R}] E[{R’}] Aj

AkAi

Ij,iIi,j

{R} {R’}



e-Participation project in European Universities (2011-2013):



Conclusions of myUniversity proj.: • the issues are differently

structured at different levels (dep., fac., univ., national system, inter-national): different semantic networks

• Hierarchical structure with percolation of relevant issues(VSM):

• each level reduces complexity to the upper level (Ashby’s law of required variety)

• Nested participatory systems (levels of recursion)



In the scientific realm what is being actualized is the knowledge base (what is the case):• The passive networks in a given discipline reflect its theoretical framework T = {{d}, {a}}• The interaction lets Ai know:

• what the case is: {pi} expressed in T• If it cannot be expressed in the passive K network, it has to be actualized: T T’

• Normal science• Revolutionary science• Laudan’s dynamics of scientific knowledge

Ci

CkCj

Ii,jIj,i

Q[{K}] Q[{K’}] Aj

AkAi

Ij,iIi,j

{K} {K’}

Semantic Network (interdisciplinarity)


What happen in the interdisciplinary science? (Hermida Quintela et al.)

The study of information (passive networks)


Information throughout the natural and social realms

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Industrial Society Information SocietyUse of Energy Information

Based on Transformation materialized in a (stabilized) industrial system

Hyper-flexible selection of changes in the socio-economic system

Model Steam Engine: focus onintensive Energy > Work

Turing Machine: focus on intensive selection of changes

• We need a general understanding of information allowing us to apprehend the complexity of reality at its different levels (physical, biological, cognitive, human, socio-technical), its emergence and evolution:

E what enables the generation of changes in the system (state space)I what enables the selection of changes in the system (state space)

Information: among networks and systems of knowledge

Aviso legalEsta obra está protegido por una licencia de Reconocimiento - No Comercial - Sin Obra Derivada 3.0 de Creative Commons. Se permite la reproducción, distribución y comunicación pública, siempre y cuando se cite adecuadamente la obra y sus responsables: J.M. Díaz Nafría, (2016). Information: among networks and systems of knowledge. (Presentation). Yachay, Ecuador.

[email protected] studies, Complexity

Hochschule München | Senescyt-Santa ElenaUniversidad de León | BITrum

information among networks and systems of knowledge

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