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Dynamics of Galois Lattices The case of epistemic communities

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Dynamics of Galois Lattices The case of epistemic communities Camille Roth & Paul Bourgine {roth,bourgine}_at_shs.polytechnique.fr CREA Centre de Recherche in Applied ... – PowerPoint PPT presentation

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Title: Dynamics of Galois Lattices The case of epistemic communities


1
Dynamics of Galois LatticesThe case of epistemic
communities
Camille Roth Paul Bourgine roth,bourgine_at_shs.
polytechnique.fr CREA Centre de Recherche in
Applied EpistemologyCNRS / Ecole Polytechnique -
Paris, France.
Sunbelt XXV, Redondo Beach, CA, USA - Feb 16-20th
2005
2
ObjectiveEpistemic community taxonomy/dynamics
  • Describe communities of knowledge, in particular
    scientific communities, and their taxonomy e.g.
    trends/subfields within a paradigm.
  • Epistemic community group of agents who share
    a common set of topics, concerns, problems who
    share a common goal of knowledge creation.
  • (Haas (1992), Cowan et al. (2000), Dupouet et al.
    (2001)).
  • Definition used here  an epistemic community
    is the largest set of agents that share a given
    concept set

3
Formal frameworkDefinitions
Epistemic community taxonomy/dynamics
  • Consider the bipartite graph on R
  • Intent of an agent set S all concepts used by
    every agent in S
  • Epistemic group pair (S, C), where C is the
    intent of S.
  • Epistemic community (based on a concept set C)
    the maximal epistemic group based on C.
  • Dual notions
  • examples (A,B,C,E, McB)
  • (B,C, McB,EmG)

4
Formal frameworkGalois lattice
Epistemic community taxonomy/dynamics
  • Good news the extent of the intent of an agent
    set yields its epistemic community.
  • e.g. from C,D, whose intent is EmG, whose
    extent is B,C,D, we get ? (B,C,D, EmG)
    epistemic community
  • Pb there may be many such communities

5
Formal frameworkGalois lattice
Epistemic community taxonomy/dynamics
6
CategorizationGalois lattice
Epistemic community taxonomy/dynamics
  • Hypotheses on scientific communities they are
    structured (i) into fields, with common concerns,
    and (ii) hierarchically, through
    generalization/specialization relations.
  • We need a categorization method that allows
    overlap.
  • The Galois lattice is the ordered set of all
    epistemic communities (closed couples), provided
    with the natural partial order on sets.

7
CategorizationGalois lattice
Epistemic community taxonomy/dynamics
 basic-level 
more general more specific
8
Galois latticeClosed couple relevance
empirical results
Epistemic community taxonomy/dynamics
  • Try to find a relevant level of
    generality/precision for the closed sets so that
    the lattice is manageable.
  • Given the assumptions, first criterion fields
    agent set size.
  • Very poor linguistic assumptions small
    stop-word list, basic lemmatization, no
    contextual processing, no homonymy, synonymy,
    syllepsis, nominal groups
  • Computation of the lattice for a relation from
    MedLine data on zebrafish, 1990-1995 (6 years).

9
Galois latticeEmpirical results
Epistemic community taxonomy/dynamics
Galois lattice on  zebrafish  community
density of closed sets against extension sizes
(author sets) as a proportion of agents of the
whole community (200 authors) (1800 concepts)
10
Galois latticeEmpirical results
Epistemic community taxonomy/dynamics
  • Large ECs remarkable stylized fact of the data.
  • Partial real lattice successfully checked by
    domain experts

11
Galois latticeSelection
Epistemic community taxonomy/dynamics
  • -gt Improve selection criteria, since agent set
    size is
  • Over-selective Large yet less significant sets.
  • Additional criterion Ratio between set and
    superset sizes.
  • (2) Under-selective Small yet significant sets.
  • Additional criterion Distance from the top.

12
Galois latticeSelection and dynamics
Epistemic community taxonomy/dynamics
  • Three 6-year periods 90-95, 94-99 and 98-03.
    Selection on 70 words.
  • Booming community from 1000 authors at the end
    of 1995, to 9700 by 2004 (and 3700 in 1999).
  • Selection criteria
  • (1) catch large communities Size/distance
    attributes
  • (2) catch isolated communities Size/distance
    number of sons

13
DynamicPartialLattice
Epistemic community taxonomy/dynamics
90-95
98-03
14
thanks
to be continued on http//camille.roth.free.fr
15
extra stuff
16
Formal frameworkDefinitions
Objective 1 - Epistemic community
taxonomy/dynamics
  • More formally for X ? S, Y ? C,
  • Properties
  • and as such, it is a closure operation. X
    is said closed iff XX.
  • Closed coupleA closed couple is thus an
    epistemic community.

17
Galois latticeEmpirical results
Epistemic community taxonomy/dynamics
Decreasing cumulated frequencies
18
Categorization
Epistemic community taxonomy/dynamics
  • Many epistemic communities how to categorize ?
  • Computer science methods (euclidian distances
    derivates, based more on computational than
    sociological hypotheses)
  • Approaches stemming from sociology structural
    balance, blockmodeling, structural cohesion...
  • pb 1 few hierarchical methods, and if so,
    mostly trees or dendrograms
  • pb 2 they work fine on small sets
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