The document discusses the analysis and comparison of Polish citations in Wikipedia, focusing on citation extraction, linking, and exploration methods. It presents challenges related to citation templates and data processing, while proposing enhancements for citation identification and ontology mapping. Additionally, the findings reveal patterns in citation frequency and type across different languages, contributing to the understanding of citation dynamics in Wikipedia.

1. DBpedia Citation Challenge
(Not only) Polish Citations in Wikipedia:
analysis, comparison, directions
Krzysztof Węcel, Włodzimierz Lewoniewski, Paweł Sobociński
DBpedia Community Meeting, Leipzig, 15.09.2016

2. Outline
• Extraction
• Linking
• Exploration
• Ranking
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3. Extraction
3

4. References and citation templates
<ref name="Trimble 1987">{{cite journal
|last=Trimble |first=V.
|date=1987
|title=Existence and nature of dark matter in the
universe
|journal=[[Annual Review of Astronomy and
Astrophysics]]
|volume=25|pages=425–472
|bibcode=1987ARA&A..25..425T
|doi=10.1146/annurev.aa.25.090187.002233
}}</ref>
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5. Citation rendering – external sites
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6. Citation templates
• {{cite web …
• {{cite journal …
• {{cite book …
• {{cite conference
but also
• {{Google books|ID|title|page=|
keywords=|text=|plainurl=}}
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7. Citation templates cnt’d
• Polish
– {{cytuj
– {{cytuj stronę …
– {{cytuj pismo …
– {{cytuj książkę …
• German
– {{Literatur …
– {{Internetquelle …
– but also
• {{DOI …
• {{ISSN …
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8. Number of templates
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9. Number of templates
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10. Number of templates
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11. Number of templates
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12. Number of templates
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13. Number of templates
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14. Methods
• DBpedia Extraction Framework
– CitationExtractor
• adaptation to Polish templates for citation
• hard-coded rules
– several issues
• incorrect titles for some publications
– <http://doi.org/10.1051/aas:1999404> dc:title
"3.15576E8"^^<http://dbpedia.org/datatype/second> .
• processing limits
– JAXP00010004: The accumulated size of entities is "50 000
001" that exceeded the "50 000 000" ;limit set by
"FEATURE_SECURE_PROCESSING"
• PyCiExtractor
– own implementation in Python
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15. Specific issues
• titles can vary significantly
• given name and family name are sometimes distinguished
• specific naming of consecutive authors
– first1, last1, first2, last2, …
– imię1, nazwisko1, imię2, nazwisko2, …
• date field
– various formats
• access data is (an should be) different for individual items
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16. Sample variants of title
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17. Linking
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18. Reuse of attributes
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19. Completeness of attributes
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20. Ontologies/Vocabularies
• bibo:
– The Bibliographic Ontology, http://bibliographic-
ontology.org/, 2016
– http://purl.org/ontology/bibo/
• fabio:
– FaBiO, the FRBR-aligned Bibliographic Ontology,
http://www.sparontologies.net/ontologies/fabio/so
urce.html, 2016
– http://purl.org/spar/fabio
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21. Mappings to ontologies
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22. External citation databases
• benefits and tasks
– disambiguation of reference details
– fusion of references
– real statistics on publication’s citation
– classification of publications (topic, quality, IF, stats)
• dereferencing identifiers:
– DOI, arXiv, bibcode, LCCN, …
• libraries/repositories
– Google Scholar, Mendeley, ResearchGate, BibSonomy, Microsoft
Academic Search, many more
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23. Our scenario: Worldcat
• the world’s largest library catalog
• collections of 72,000 libraries in 170 countries
• WorldCat Search API
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24. Exploration
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25. Characteristics of citations
• focus on Polish citations
• other languages for comparison
• several aspects analysed:
– citing templates
– citing articles
– cited domains
• charts
– frequency vs. frequency rank (Zipf law)
– frequency vs. number of citations
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26. Frequency vs. number of citations (PL)
Observation
Zipf’s law is
suprisingly
accurate
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27. Frequency vs. frequency rank (PL)
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28. Frequency rank – articles (PL)
Observation
Zipf works for
articless, too
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29. Number of citations – articles (PL)
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30. Frequency rank for domains (PL)
Comment
unique citation,
i.e. counted in
Wikipedia
article only
once
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31. Frequency rank for articles (PL)
Comment
ID’d, i.e.
identified
citation, e.g. by
URL, ISBN or
DOI
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32. Citations by type (PL)
Observation
books seem to
dominate in
Polish
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33. Citations by type (EN)
Observation
other/hash
sources seem
to dominate in
English
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34. Identification of articles (EN)
Observation
there is
probably an
issue with
hashed articles
in English, i.e.
no stright line
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35. Comparison: freq rank for domains
Observation
more domains
are cited in
English
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36. Comparison: freq rank for all articles
Observation
there are more
citations in
Polish than in
English
(cited at least
10 times)
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37. New data, all languages - domains
Comment
data extracted
using
PyCiExtractor,
numbers seem
to better reflect
reality
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38. New data, all languages - articles
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39. Ranking
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40. Wikirank.net
• we develop a portal for ranking Wikipedia articles in various
language according to their quality criteria
• languages: Belarusian, English, French, German, Polish,
Russian, Ukrainian
• current modules:
– WikiRank
– Top Articles
– Citation Index
– Websites Rank
http://wikirank.net
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41. WikiRank – sample article
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42. Wikirank – sample article cnt’d
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43. Citation Index
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44. Websites Rank
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45. CiteRank
• a new module with a goal to rank citations used within
various language editions of Wikipedia
http://cite.wikirank.net/ (DBpedia framework)
http://cite2.wikirank.net/ (PyCiExtractor)
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46. Top titles
• still a problem with title extraction
• geography is a dominating topic
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47. Top titles
• some titles are very popular
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48. Top titles
• even for frequent references there are plenty of ambiguities
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49. Completeness
• yes, we agree, it might be misleading…
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50. Most cited in Poland
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51. Most cited – plants taxonomy
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52. Details of citation – author name variants
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53. Surprise – 7th place in Polish Wiki
• www.navin.org.np – National Association of Village
Development Committees in Nepal (NAVIN)
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54. NAVIN citation – details
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55. Sample article citing NAVIN
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56. Surprise 2 – 1st place in English wiki
but: 404 Link broken 56Krzysztof Węcel

57. Lessons learnt
• Extraction methods should be improved.
• Mapping to ontologies can be useful for comparison.
• Identification of publications (better than hash) is needed.
• External repositories are not open enough.
• Distributions point at some problems with extraction.
• The are plenty of use cases for analyses of citations.
Citation statistics can improve quality modelling
of Wikipedia articles.
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