In recent years it has become possible to
computationally calculate relations between people, documents and words in
terms of the analysis of communications and the modelling of social dynamics. The
implications of this “computational social science” on naturalistic social
inquiry are disputed. The way that utterances between individuals relate can be investigated: this might
entail analysing the correspondences between the use of words, phrases and
topics in different contexts, determining the relative probabilities of those
topics or words occurring across contexts and making inferences about the
related semantic content between different contexts as a result. This approach
belongs to a tradition of studying information in terms of the probabilities of
the occurrences of symbols which was instigated by Shannon, and which a number
of authors have related to the processes of human communication (although
Shannon himself excluded this possibility). As more communication practices are bound by technology, probabilistic analysis of communication
presents remarkable results in affording the clustering of cognate areas
through automatic analysis, making possible automatic topic identification, the
clustering of social groups through communication patterns, automatic
identification of learning needs, preferences, and so on. Consequently,
economic opportunities present themselves through the emergence of recommendation
services, direct marketing, learning support, social prediction, and so on.
In contrast to the statistical techniques which view
communications as ‘bags of words’, purposeful and meaningful utterances
constitute lived experience where communications implicate and manipulate social
positions between agents: expectations, intentions, meanings, ambitions,
experiences and power struggles contribute to the constitution of both social
institutions and individual experience. Unlike relations, positions are
inhabited by agents. Despite the success of the algorithmic analysis of
communication relations, most communicating occurs away from the internet. What
is the possibility of a computational analysis of the inter-human positioning
of meanings, expectations and power struggles? What is its connection to the
computational analysis of relation between people, words and documents? What
import does this bear for a naturalistic approach to the social sciences?
Objects of Analysis
and Analytical Objects
A computational analysis examines data produced through
social interaction (usually from the internet). Internet-based interactions are
declarations of facts, feelings, opinions, states of affairs made by agents for
the purpose of positioning between agents. An analysis of the words that
constitute declarations is also a declaration – also for the purpose of
positioning. The present analysis here is also a declarative contribution to
discourse and the purpose here is positional. How might an understanding of the
social dynamics of what might be considered ‘codes of communication’ arise
through what can only be a participatory process in the reproduction and
transformation of those codes of communication?
We might begin by making a distinction between experience,
utterance and analysis. Searle has recently suggested one way of doing this, making
a distinction presenting “ontological subjectivity” and “epistemological
subjectivity”. For Searle, consciousness belongs to the category of the
“epistemological subjective”: these are the as-yet uncodified transcendental
constructs relating to Husserls’s “horizon of co-givenness”, Freud’s primary
process or Luhmann’s ‘psychic system’. By constrast Searle presents the “ontologically
subjective” as a way of characterising social institutions, documents,
artefacts, practices, technologies and social roles. Searle argues that ontologically
subjective objects are brought into being by a particular kind of speech act
called a ‘status function’. In arguing for this, he argues for a ‘collective
intentionality’ which upholds status functions and thus serves to constitute
social reality. Searle’s collective intentionality can be compared to a
coordination of expectations within a system of communication as is described
by Luhmann. Status functions are
themselves utterances – among their basic forms is the statement “X counts as Y
in C”, but this is one of many forms of utterance. In this way, Searle’s categories serve as a
way of distinguishing between objects of analysis – spreadsheets, social network graphs, economic forecasts and
so on – about which status functions as expressions of collective
intentionality and positioning will be made (“X counts as Y in C”), and the
epistemically subjective realm of consciousness within which coordinations of
utterances emerge.
Considering the difference between relations and positions
in this light, it is possible to make the status function “this relation is a
position” – indeed, this is a common status function among those who would wish
to assert the legitimacy of simple social network analysis as isomorphic to
social ordering. Such confusion between relation and position presents an
opportunity to explore related status functions concerning the legitimacy of
data analytics in the first place and the particular algorithms concerned. Since
positions are inhabited by agents, we might expect the false assertion of
positions to lead to difficulties in establishing the appropriate collective
intentionality required to uphold the status function. However, assertions of
relations as positions sometimes do become accepted for periods of time,
supported by acceptance of other status functions (of the deontic power of
those making the declarations, for example), only for them to eventually be
critiqued and overturned. Indeed,
radical changes in positioning involve the dramatic overturning of
status functions relating to social role or position: revolution is the name we
give to the overturning
of the status function “I am the king”; Western powers are currently engaged in an attempt to overturn the status function "This is a caliphate".
The Analysis of
collective intentionality
Since status functions are upheld by collective intentionality, status functions are themselves
positional (they implicate power, ambition, expectation and meaning). It is
reasonable to ask whether algorithmic analysis which exposes position rather
than relation is possible. Such an analysis depends on postulating dynamics of
multi-dimensional communications of everyday life. Techniques for analysing
relation rely on Shannon’s theories about information, entropy and redundancy
which can be applied to the distribution of symbols of communication in a large
system like the internet. These techniques applied the analysis of relation
appear to produce striking and revealing results. However, the experience of
encountering such an analysis is effectively one of being subject to a status
function relating to the analysis by various means of other status functions
contained in internet communications in which many agents (possibly including
the viewers of the analysis) participate. In short, to be ‘convinced’ by a
relational analysis is to be positioned by those making the status declaration
about the analysis. This then raises the question as whether it is possible to
produce a computational analysis where the positioning itself might be
revealed, thus revealing the deeper dynamics of collective intentionality.
Before addressing this question, there is an obvious
concern: is a status function concerning a positional analysis any different
from a status function concerning a relational analysis? The problem here
becomes one of assessing the impact of a status function of any analysis. Status functions of all
kinds are positional – they implicate what Searle calls the ‘deontic power’ of
the person making the declaration – however sophisticated, power, ambition,
meaning and expectation all play a role. They further implicate status
functions concerning the method (algorithms) and underlying epistemology of any
analysis that is pursued. Since methods and epistemologies will entail
transcendental components which are
metaphysical (and therefore unprovable) methods, and analytical objects will
always be vulnerable to critique. So why bother attempting to develop an
analysis of positioning between agents?
Moving beyond a relational algorithmic analysis to one that
attempts to capture the dynamics of collective intentionality presents an
opportunity to explore different empirical metrics whose values may be compared
to logical structures which express different social theories. If a connection
between logical structure and empirical measure can be established, then a
naturalistic inquiry emerges as a possibility in the social sciences whereby
theorized social ordering can be compared to measured data. This would address
a problem in the social sciences whereby research practice frequently exhibits
a kind of ‘naturalistic gap’ as theories are used to design interventions, but
where theory-practice gaps result in changes to practice at the expense of
theoretical critique (resulting in
pathological positioning). In other
words, richer analysis – particularly the analysis of collective intentionality
should be seen in the context of an empirical activity which stimulates
disputation and analysis between statements of logic (theorized social structures)
and status of empirical fact (empirically measured structures). Might an analysis
of positional data present an opportunity to exploit data analytics with regard
to social naturalism?
The Logical
characterisation of social structure and the possibility of naturalism
Social analysis – particularly as it is undertaken in
economics – tends towards quantification of social structure through
econometric modelling (Hodgson, 1988; Lawson, 1999). Social network analysis
has provided new means of representing social structure as relational entities.
Both econometric and social network analysis presents logical and empirical
aspects. The logic of econometrics has been heavily critiqued in recent years
as not only divorced from reality, but responsible for economic pathology
whereby econometric models which have little predictive or explanatory power
are nevertheless forced on the population (Lawson, 1999). A similar story of
forcing social network idealisations on a population have emerged in the manipulation
of user responses to social software and gamification. In such situations, the
theories that sit beneath the models are not critiqued, whilst economic policy
attempts to force practice so that its measurement fits the econometric models
used for analysis. In other words, there is a ‘naturalistic gap’ between
prescribing policy interventions without theoretical development or refinement.
Social network analyses, however, do provide a glimpse of
the logic of a social structure: indeed, the graphs of positional social
network analysis are essentially logical, not empirical. In representing
relations between nodes and arcs, the logical structure of the diagrams bears
comparison with what Kauffman (1995) calls ‘arrow epistemology’ alluding to
Category Theory (Mac Lane, 1972; Goldblatt, 1982). In arguing for such logical
presentation of structures as a network of arrows, Kauffman argues that “it
enables us to draw connections with the kind of diagrammatics that occurs in
artistic, linguistic, physical and philosophical contexts.” (Kauffman, 1995, p
38). Extending this to the category-theoretical constructs of objects, limits,
exponents, push-outs, pull-backs and sub-object classifiers, Badiou (2006),
Meillassoux (2008) and others have
argued that logical mathematical representations of social structures may present
new directions for naturalistic investigation. In the present context, the connection
between such logical structures and empirically-derived networks pertaining not
only to relation but also to position are of interest. This is to address the
naturalistic gap between theory and practice through the comparison of two
status function: one which asserts the status of the empirical object (the
social network analysis of relation or position); and the other which asserts the
status of the logical description. A naturalistic approach may then explore the
differences in ordering between the two, which in turn represents the gap
between theory (as represented by the logical) and practice (as represented by
the empirical).
This may be described at a simple level. Any status
function, if it is to be upheld within its context (in other words, if it is
maintained within a particular code of communication), will exist by virtue of
the dynamics of other communications. Kauffman has suggested how certain ‘knot’
topologies may be mutually reinforcing. Using the example of the Trefoil knot, it
is possible to see where a particular topology of communication may serve to
maintain those communications owing to the mutual constraint that each
communication bears on the others. Noting this, a logical representation can
find fuller description in Category theory by articulating the limits bearing
upon each aspect of the communication dynamics, and the way in which each limit
relates to each other limit.
Within the empirical technique for identifying positions
described above, the logical representation of constraint identified in
category theoretical limits becomes translated into the empirical measurement
of mutual redundancy. The empirical measurement of positions rests on the
identification of redundant expectations which can be analysed through communications.
A theory may express the view that certain status functions are upheld within
certain dynamics of communication. Measurement of redundancies of communication
can confirm or deny this, thus requiring changes to the representation of
logical structures and deeper analysis of empirical data.
In normal science, reproducible experiment and regular
successions of events (as described by Hume) may itself be reinterpreted as a
probabilistic exercise in the identification of redundant expectations (Meillassoux).
By this description, theory-building emerges from the identification of mutual
redundancy produced through empirical practice. A positional data analysis
coupled with the articulation of theory as logical structure similarly is a
process of identifying mutual redundancies of expectation between the theory
and empirical results. In particular, category theoretical articulations of
social order articulate limits at different points in a structure which
empirically correspond to the constraints of redundancies. The correlation
between limits and redundancies only works in a positional analysis, since a
relational analysis simply considers connections between nodes rather than
constraints bearing upon them.
References
Badiou, A (2006) Logics of Worlds
Bhaskar, R (1979) The Possibility of Naturalism
Goldblatt, R (1982) Topoi: The categorial analysis of logic
Hodgson, G (1988) Economics and Institutions
Kauffmann, L.H. (1995) Knots and Applications
Lawson, T (1999) Economics and Reality
Luhmann, N (1980) Social Systems
Mac Lane, S (1972) Categories for the working Mathematician
Meillasoux, Q (2008) After Finitude
Searle, J (2007) Making the Social World
Shannon, C; Weaver, W (1952) The Mathematical Theory of
Communication
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