I present here my work on how to identify memes in the scientific literature by using the citation network.

1. Meme Extraction from Corpora of Scienti

2. c
Literature using Citation Networks
Tobias Kuhn
http://www.tkuhn.ch
@txkuhn
ETH Zurich
Colloquium
Institute of Computational Linguistics
University of Zurich
25 November 2014

3. Reference
Journal article on the content of this talk:
Tobias Kuhn, Matjaz Perc, and Dirk Helbing. Inheritance patterns in
citation networks reveal scienti

4. c memes. Physical Review X, 4,
041036, 21 November 2014. https://journals.aps.org/prx/
abstract/10.1103/PhysRevX.4.041036
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6. Meme Detection
I am presenting an approach on meme detection", which is related
to a number of existing problems and approaches:
Named-entity extraction
Keyphrase extraction
Topic modeling
Terminology extraction
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8. Context for NLP
Most NLP approaches focus on the analysis of the texts themselves:
Grammar
Morphology
Text Structure
Statistical Patterns
Some also take the contexts of the texts into account:
Comparison to properties of entire corpus (e.g. tf{idf)
Training on particular corpus/domain/speaker
Citation graph of scienti

9. c publications
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11. Citation Graph of Scienti

12. c Publications
Nodes: publications
Edges: citations (in gray)
Tobias Kuhn, ETH Zurich Meme Extraction from Corpora of Scienti

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14. Citation Graph of Scienti

15. c Publications
Nodes: publications
Edges: citations (in gray)
Legend:
Natural/Agricultural Sciences
(except Physical Sciences)
Physical Sciences
Engineering and Technology
Medical and Health Sciences
Social Sciences / Humanities
Tobias Kuhn, ETH Zurich Meme Extraction from Corpora of Scienti

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17. Citation Graph of Scienti

18. c Publications
Nodes: publications
Edges: citations (in gray)
Legend:
Natural/Agricultural Sciences
(except Physical Sciences)
Physical Sciences
Engineering and Technology
Medical and Health Sciences
Social Sciences / Humanities
Tobias Kuhn, ETH Zurich Meme Extraction from Corpora of Scienti

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20. Citation Graph of Scienti

21. c Publications
Entire giant component (33
million nodes) of the citation
graph of Thomson Reuter's
Web of Science dataset.
Legend:
Natural/Agricultural Sciences
(except Physical Sciences)
Physical Sciences
Engineering and Technology
Medical and Health Sciences
Social Sciences / Humanities
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23. Citation Graph: American Physical Society
Citation graph of the Phys-
ical Review journals (463k
nodes).
Legend:
A: Atomic, molecular,
optical phys.
B: Condensed matter,
materials phys.
C: Nuclear phys.
D: Particles,

24. elds, gravitation,
cosmology
E: Statistical, nonlinear,
soft matter phys.
other journals
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26. Citation Graph: Memes
Speci

27. c phrases or memes
localize to speci

28. c regions in
the citation graph.
Legend:
quantum

29. ssion
graphene
self-organized criticality
trac
ow
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31. Scienti

32. c Memes
Meme was coined by Richard Dawkins:
Just as genes propagate themselves in the gene pool by leaping from body
to body via sperm or eggs, so memes propagate themselves in the meme pool
by leaping from brain to brain via a process which, in the broad sense, can
be called imitation. [Dawkins, The Sel

33. sh Gene]
Examples of memes:
Melodies
Recipes
Cultural habits
Words, grammar rules, text style
Scienti

34. c concepts
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36. Genes/Memes as Network Patterns!
Dawkins' De

37. nition of Gene:
I am using the word gene to mean a genetic unit that is small enough to last
for a number of generations and to be distributed around in many copies.
[Dawkins, The Sel

38. sh Gene]
Our Working De

39. nition of Scienti

40. c Meme:
A scienti

41. c meme is a short unit of text in a publication that is replicated in
citing publications and thereby distributed around in many copies.
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43. Propagation Score
Propagation score P quanti

44. es the degree to which a meme's
occurrence aligns with the citation graph:
Pm =
sticking factor
sparking factor
=
?
,
?
=
dm!m
d!m
dm!m
d!m
To prevent that some infrequent phrases get a high propagation score
by chance, we can add small amount of controlled noise (we use
= 3):
Pm =
dm!m
d!m +
dm!m +
d!m +
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46. Frequency/Propagation Score for APS Data
10
relative frequency !
−2
10
0
10
2
10
4
10
6
10
−2
10
−4
10
−6
10
0
APS
N = 1,372,365
quantum
fission
graphene
self-organized
criticality
traffic flow
propagation score !
density of n-grams:
105
104
103
102
101
100
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48. Meme Score
Meme score M as the Product of relative frequency f and
propagation score P:
Mm = fmPm
Top 20 Memes for APS (Physics):
1. loop quantum cosmology+* 11. dark energy+*
2. unparticle+* 12. Rashba
3. sonoluminescence+* 13. CuGeO3
+
4. MgB2
+ 14. strange nonchaotic
5. stochastic resonance+* 15. in NbSe3
6. carbon nanotubes+* 16. spin Hall+
7. NbSe3
+ 17. elliptic
ow+*
8. black hole+* 18. quantum Hall+*
9. nanotubes+ 19. CeCoIn5
+
10. lattice Boltzmann+* 20. in
ation+
+ annotators agreed that this is an interesting and important physics concept
* also found on the list of terms extracted from Wikipedia
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50. Properties of the Meme Score
The meme score has a number of nice properties:
Can be calculated eciently and exhaustively even on very large
dataset
No upper limit on the length of n-grams
No dependence on external linguistic or ontological knowledge
No stop-word lists or other kinds of arbitrary

51. lters or thresholds
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53. Manual Annotation
Two annotators (A1, A2): PhD students with physics degree
Annotation with respect to (1) physics concept or not and (2)
linguistic category
Randomly extracted phrases for comparison
physics concept not a physics concept
noun phrase verb adjective or adverb other
meme score
A1
A2
A1
A2
random
A1
A2
A1
A2
weighted random
30 60 90 120 150
terms
A1
A2
A1
A2
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55. Comparison to Alternative Metrics
100
80
60
40
0
1
2
3 0 0.1 0.2 0.3 0.4 0.5
max. relative
difference
across journals
max. absolute
difference
across journals
max. relative
change
over time
max. absolute
change
over time
frequency
meme score
A (area under curve)
10
10
10
20
top x terms by meme score
percentage of Wikipedia terms
40% of top 50
terms are found
on Wikipedia list
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57. Evolution over Time: Exemplary Memes
0.5 1 1.5 2 2.5 3 3.5 4 4.5
5
x 10
14
12
10
8
6
4
2
0
publication count
meme score (d = 1)
1940
1960
1970
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
quantum
fission
graphene
self−organized criticality
traffic flow
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59. Evolution over Time
0.5 1 1.5 2 2.5 3 3.5 4 4.5
x 105
12
10
8
6
4
2
0
publication count
meme score
1940
1960
1970
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008graphene
entanglement
MgB2
nanotubes
carbon nanotubes
quark
neutrino
Bose−Einstein
quantum Hall
black
C60
Hubbard model
quantum wells
graphite
reactions
photoemission
black hole
tricritical
Kondo
superconducting
fission
MeV
diffuse scattering
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61. Conclusions
The citation graph is a very powerful resource to detect memes.
Combined with other existing approaches, this seems to be a
promising tool for NLP on scienti

62. c publications.
Could be applied to other types of texts that have a certain kind of
citation structure (legal texts?).
Allows for studying memes in an exhaustive manner.
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64. Thank you for your Attention!
Questions?
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66. Randomized Network
10
relative frequency !
−2
10
0
10
2
10
4
10
6
10
−2
10
−4
10
−6
10
0
APS
randomized
(time preserving)
N = 89,356
propagation score !
density of n-grams:
105
104
103
102
101
100
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68. Meme Score Calculation
1 Collect all phrases that stick at least once (not counting
free-riding on larger memes)
2 Calculate sticking and sparking factors for all collected phrases
Mm = fmPm with Pm =
sticking factor
sparking factor
=
dm!m
d!m +
,
d
m!m
+
d!m
+
!
Example
Citing title:
covariant eective action for loop quantum cosmology from order reduction
Cited titles:
{ quantum nature of the big bang
{ absence of a singularity in loop quantum cosmology
{ large scale eective theory for cosmological bounces
Sticking phrases: loop quantum cosmology, quantum, eective, for
Sparking phrases: covariant, covariant eective action, order reduction, ...
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70. Top Meme Scores for Web of Science Data
1. MgB2 11. loop quantum cosmology
2. lattice Boltzmann 12. zero-divisor
3. graphene 13. BiFeO3
4. on chalcogenolates 14. Neospora
5. Ti3SiC2 15. Papuloerythroderma
6. harmony search 16. Neospora caninum
7. seasonal climate summary 17. metal dusting
southern hemisphere 18. porcine circovirus
8. empirical likelihood 19. cone metric
9. proxy re-encryption 20. ranked set
10. spiking neural P systems
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72. Top Meme Scores for PubMed Central Data
1. Buruli ulcer 11. Nipah virus
2. G-quadruplex 12. miRNA
3. miRNAs 13. microRNAs
4. chronic cerebrospinal venous 14. hepatitis E virus
insuciency 15. the 45 and Up Study
5. cerebrospinal venous 16. chronic cerebrospinal venous
6. Mycobacterium ulcerans insuciency (CCSVI)
7. enterovirus 71 17. EV71
8. G-quadruplexes 18. bluetongue
9. CCSVI 19. Schmallenberg virus
10. malaria 20. Nipah
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