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Time-focused analysis of connectivity and popularity of historical persons in Wikipedia

  • Adam Jatowt
  • Daisuke Kawai
  • Katsumi Tanaka
Article

Abstract

Wikipedia contains large amounts of content related to history. It is being used extensively for many knowledge intensive tasks within computer science, digital humanities and related fields. In this paper, we look into Wikipedia articles on historical people for studying link-related temporal features of articles on past people. Our study sheds new light on the characteristics of information about historical people recorded in the English Wikipedia and quantifies user interest in such data. We propose a novel style of analysis in which we use signals derived from the hyperlink structure of Wikipedia as well as from article view logs, and we overlay them over temporal dimension to understand relations between time periods, link structure and article popularity. In the latter part of the paper, we also demonstrate several ways for estimating person importance based on the temporal aspects of the link structure as well as a method for ranking cities using the computed importance scores of their related persons.

Keywords

Wikipedia Historical persons Temporal analysis Link analysis Collective memory 

Notes

Acknowledgements

This research was supported in part by MEXT Grants-in-Aid for Scientific Research (#17H01828, #15K12158) and by MIC/SCOPE (#171507010).

References

  1. 1.
    Assmann, A.: Introduction to Cultural Studies. Schmidt Erich Verlag, Wirtschaft (2008). (in German)Google Scholar
  2. 2.
    Auer, S., Bizer, C., Kobilarov, G., Lehmann, J., Cyganiak, R., Ives, Z.: DBpedia: A Nucleus for a Web of Open Data. In: ISWC’07/ASWC’07, pp. 722–735. Springer (2007)Google Scholar
  3. 3.
    Yeung, C.-M. Au, Jatowt, A.: Studying how the past is remembered: towards computational history through large scale text mining. In: CIKM, pp. 1231–1240 (2011)Google Scholar
  4. 4.
    Burns, J.F.: Bones under parking lot belonged to Richard III, 2/2013. http://www.nytimes.com/2013/02/05/world/europe/richard-the-third-bones.html?_r=1
  5. 5.
    Carr, E.H.: What is History?. Penguin, London (1961)Google Scholar
  6. 6.
    Cook, J., Das Sarma, A., Fabrikant, A., Tomkins, A.: Weeks, your two, of fame and your grandmother’s. In: WWW: ACM, New York, NY. USA, pp. 919–928 (2012)Google Scholar
  7. 7.
  8. 8.
    Düring, M.: Can Network Analysis Reveal Importance? Degree Centrality and Leaders in the EU Integration Process. Social Informatics, pp. 314–318. Springer, Berlin (2014)Google Scholar
  9. 9.
    Ebbinghaus, H.: Memory: A Contribution to Experimental Psychology. Columbia University, New York (1913)Google Scholar
  10. 10.
    Eom, Y.-H., Aragón, P., Laniado, D., Kaltenbrunner, A., Vigna, S., Shepelyansky, D.L.: Interactions of cultures and top people of Wikipedia from ranking of 24 language editions. PLoS ONE 10(3), e0114825 (2014)CrossRefGoogle Scholar
  11. 11.
    Ferron, M., Massa, P.: Collective memory building in Wikipedia: the case of North African uprisings. In: WikiSym ’11. ACM, New York, NY, USA, 114–123 (2011)Google Scholar
  12. 12.
    Friedman, R.: The Life Millennium: The 100 Most Important Events and People of the Past 1000 Years. Bulfinch, New York City (1998)Google Scholar
  13. 13.
    Gabrilovich, E., Markovitch, S.: Computing semantic relatedness using Wikipedia-based explicit semantic analysis. Proc. IJCAI 2007, 1606–1611 (2007)Google Scholar
  14. 14.
    Gabrilovich, E., et al.: Overcoming the brittleness bottleneck using Wikipedia: Enhancing text categorization with encyclopedic knowledge. In: AAAI (2006)Google Scholar
  15. 15.
    Gadamer, H.-G.: Truth and Method. Sheed and Ward, London (1975)Google Scholar
  16. 16.
    Garcia-Fernandez, A., Ligozat, A.-L., Dinarelli, M., Bernhard, D.: When was it written? Automatically determining publication dates. In: SPIRE (2011)Google Scholar
  17. 17.
    Geipel, M.: Self-organization applied to dynamic network layout. Int. J. Mod. Phys. C 18(10), 1537–1549 (2007)CrossRefzbMATHGoogle Scholar
  18. 18.
    Giles, J.: Internet Encyclopaedias go head to head. Nature 438, 900–901 (2005)CrossRefGoogle Scholar
  19. 19.
    Gyöngyi, Z., Garcia-Molina, H., Pedersen, J.: Combating web spam with trustrank. In VLDB 576–587, 2004 (2004)Google Scholar
  20. 20.
    Halbwachs, M.: La Mémoire Collective. Les Presses Universitaires de France (1950) (in French)Google Scholar
  21. 21.
    Hart, M.H.: The 100: A Ranking of the Most Influential Persons in History. Citadel; Revised edition (2000)Google Scholar
  22. 22.
    Hoerl, C., McCormack, T.: Time and Memory: Issues in Philosophy and Psychology. Oxford University Press, Oxford (2001)Google Scholar
  23. 23.
    Hoffart, J., et al.: YAGO2: Exploring and querying world knowledge in time, space, context, and many languages. In: WWW pp. 229–232 (2011)Google Scholar
  24. 24.
    Hoffmann, L.: Looking back at big data. Commun. ACM 56(4), 21–23 (2013)CrossRefGoogle Scholar
  25. 25.
    Huet, T., Biega, J., Suchanek, F.: Mining history with Le Monde. In: AKBC 2013 workshop at CIKM2013 (2013)Google Scholar
  26. 26.
    Jacoby, R.: Social Amnesia: A Critique of Contemporary Psychology. Transaction Publishers, Piscataway (1997)Google Scholar
  27. 27.
    Jatowt, A., Antoine, E., Kawai, Y., Akiyama, T.: Mapping temporal horizons. Analysis of collective future and past related attention in microblogging. In: WWW, pp. 484–494 (2015)Google Scholar
  28. 28.
    Jatowt, A., Kawai, D., Tanaka, K.: Digital history meets Wikipedia: analyzing historical persons in Wikipedia. In: Proceedings of the 16th ACM/IEEE-CS Joint Conference on Digital Libraries. (JCDL 2016). ACM Press, Newark, USA, pp. 17–26 (2016)Google Scholar
  29. 29.
    Jatowt, A., Kawai, D., Tanaka, K.: Predicting importance of historical persons using Wikipedia. In: Proceedings of the 25th ACM International Conference on Information and Knowledge Management (CIKM 2016), ACM Press, Indianapolis, IN, USA, pp. 1909–1912 (2016)Google Scholar
  30. 30.
    Jatowt, A., Kawai, D., Tanaka, K.: Timestamping entities using contextual information. In: Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2017). ACM Press, Tokyo, Japan, pp. 1205–1208 (2017)Google Scholar
  31. 31.
    Joho, H., Jatowt, A., Blanco, R.: Temporal information searching behaviour and tactics. Inf. Process. Manag. J. 51(6), 834–850 (2015)CrossRefGoogle Scholar
  32. 32.
    Kanhabua, N., Niederée, C., Siberski, W.: Towards concise preservation by managed forgetting: research issues and case study. In: iPres (2013)Google Scholar
  33. 33.
    Kanhabua, N., Nguyen, T.N., Niederée, C.: What triggers human remembering of events? A large-scale analysis of catalysts for collective memory in Wikipedia. In: JCDL, pp. 341–350 (2014)Google Scholar
  34. 34.
    Kinzler, D.: WikiSense—Mining the Wiki. In: Proceedings of Wikimania 2005. In: The First International Wikimedia Conference. Wikimedia Foundation (2005)Google Scholar
  35. 35.
    Kittur, N., Chi, E.H., Suh, B.: What’s in Wikipedia? Mapping topics and conflict using socially annotated category structure. In: CHI ’09, pp. 1509–1512 (2009)Google Scholar
  36. 36.
    Kremer, M.: Population growth and technological change: one million B.C. to 1990. Quart. J. Econ. 108, 681–716 (1993)CrossRefGoogle Scholar
  37. 37.
    Lazer, D., et al.: Computational social science. Science 323, 721–723 (2009)CrossRefGoogle Scholar
  38. 38.
    Lendvai, P., Zervanou, K.: In: Proceedings of the 7th workshop on language technology for cultural heritage, social sciences, and humanities (LaTeCH 2013) at ACL’13 (2013)Google Scholar
  39. 39.
    Malik, T.: Google Doodle Honors 16th Century Astronomer Nicolaus Copernicus, February 19, (2013). http://www.space.com/19868-nicolaus-copernicus-google-doodle.html
  40. 40.
    McPherson, M., Smith-Lovin, L., Cook, J.M.: Birds of a feather: homophily in social networks. Annu. Rev. Sociol. 27, 415–444 (2001)CrossRefGoogle Scholar
  41. 41.
    Medelyan, O., Milne, D., Legg, C., Witten, Ian H.: Mining Meaning from Wikipedia. Int. J. Hum.-Comput. Stud. 67(9), 716–754 (2009)CrossRefGoogle Scholar
  42. 42.
    Michel, J.-B., et al.: Quantitative analysis of culture using millions of digitized books. Science 331(6014), 176–182 (2011)CrossRefGoogle Scholar
  43. 43.
    Milne, D., Medelyan, O., Witten, I.H.: Mining domain-specific thesauri from Wikipedia: a case study. In: WI’06, pp. 442–448 (2006)Google Scholar
  44. 44.
    Nicolas Steno Google doodle Marks his 374th Birth Anniversary (2012). http://www.theguardian.com/technology/2012/jan/11/nicolas-steno-google-doodle
  45. 45.
    Nunes, S., Ribeiro, C., David, G.: Using neighbors to date web documents. In: Proceedings of the WIDM’07 workshop associated to CIKM’07, pp. 129–136 (2007)Google Scholar
  46. 46.
    Page, L., Brin, S., Motwani, R., Winograd, T.: The PageRank citation ranking: bringing order to the web. Technical Report, Stanford University (1998)Google Scholar
  47. 47.
    Rosenzweig, R.: Can history be open source? Wikipedia and the future of the past. J. Am. Hist. 93(1), 117–46 (2006)CrossRefGoogle Scholar
  48. 48.
    Skiena, S., Ward, C.B.: Who’s Bigger. Where Historical Figures Really Rank. Cambridge University Press, Cambridge (2014)Google Scholar
  49. 49.
    Strube, M., Ponzetto, S.: WikiRelate! Computing semantic relatedness using Wikipedia. In: AAAI-06, pp. 1419–1424 (2006)Google Scholar
  50. 50.
    Sturrock, J.: Structuralism and since: from Lévi Strauss to Derrida, Introduction (1979)Google Scholar
  51. 51.
    Takahashi, Y., Ohshima, H., Yamamoto, M., Iwasaki, H., Oyama, S., Tanaka, K.: Evaluating significance of historical entities based on tempo-spatial impacts analysis using wikipedia link structure. In: Proceedings of HT ’11. ACM, New York, NY, USA, pp. 83–92 (2011)Google Scholar
  52. 52.
    Whiting, S., Jose, J.M., Alonso, O.: Wikipedia as a time machine. In: TempWeb’14 at WWW2014, pp. 857–861 (2014)Google Scholar
  53. 53.
    Wood, T.: An introduction to civil registration. Federation of Family History Societies (Publications) (1994)Google Scholar
  54. 54.
    Vrandečić, D., Krötzsch, M.: A free collaborative knowledge base. Commun. ACM 57(1), 78–85 (2014)CrossRefGoogle Scholar
  55. 55.
    Zaagsma, G.: On digital history. BMGN Low Ctries. Hist. Rev. 128(4), 3–29 (2013)CrossRefGoogle Scholar
  56. 56.
    Zhang, X., Asano, Y., Yoshikawa, M.: Mining knowledge on relationships between objects from the web. IEICE Trans. 97–D(1), 77–88 (2014)CrossRefGoogle Scholar
  57. 57.
    Au Yeung, C.M., Tomoharu, T.: Extracting multi-dimensional relations: a generative model of groups of entities in a corpus. In: Proceedings of the 20th ACM International Conference on Information and Knowledge ManagementGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Kyoto UniversityKyotoJapan

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