Has Large-Scale Named-Entity Network Analysis Been Resting on a Flawed Assumption?

PLoS ONE

Volumn 8, Issue 7, 2013, Pages

  Fegley, Brent D ^a   Torvik, Vetle I ^a  

^a UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AMBIGUITY; ARTICLE; BIBLIOGRAPHIC DATABASE; BIOMEDICINE; CLUSTER ANALYSIS; CODING AND CLASSIFICATION; CONTROLLED STUDY; INFORMATION PROCESSING; LUMPING; NOMENCLATURE; PUBLICATION; SIMULATION; SPLITTING; WRITING;

EID: 84880764942     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0070299     Document Type: Article

References (66)

1. Newman MEJ, (2004) Coauthorship networks and patterns of scientific collaboration. Proc Natl Acad Sci U S A 101Suppl 1: 5200-5205 doi:10.1073/pnas.0307545100.
2. Barabási AL, Jeong H, Néda Z, Ravasz E, Schubert A, et al. (2002) Evolution of the social network of scientific collaborations. Physica A 311: 590-614 doi:10.1016/S0378-4371(02)00736-7.
3. Moody J, (2004) The structure of a social science collaboration network: Disciplinary cohesion from 1963 to 1999. Am Sociol Rev 69: 213-238 doi:10.1177/000312240406900204.
4. Steyvers M, Smyth P, Rosen-Zvi M, Griffiths T (2004) Probabilistic author-topic models for information discovery. In: Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; 2004; Seattle, WA. ACM. 306-315. doi:10.1145/1014052.1014087.
5. Radev DR, Joseph M, Gibson B, Muthukrishnan P (2009). A bibliometric and network analysis of the field of computational linguistics. Unpublished manuscript [credited erroneously in literature to J Am Soc Inf Sci Technol]. Available: http://clair.si.umich.edu/~radev/papers/biblio.pdf.
6. Milojević S, (2010) Modes of collaboration in modern science: Beyond power laws and preferential attachment. J Am Soc Inf Sci Technol 61: 1410-1423 doi:10.1002/asi.21331.
7. He B, Ding Y, Ni C, (2011) Mining enriched contextual information of scientific collaboration: A meso perspective. J Am Soc Inf Sci Technol 62: 831-845 doi:10.1002/asi.21510.
8. White HD, McCain KW (1998) AID-ASI4>3.0.CO;2-4.
9. Scott JP (2000) Social network analysis: A handbook. 2nd ed. Thousand Oaks, CA: SAGE. 240 p.
10. Rosen-Zvi M, Griffiths T, Steyvers M, Smyth P (2004) The author-topic model for authors and documents. In: Proceedings of the 20th Conference on Uncertainty in Artificial Intelligence; 2004; Banff, Canada. AUAI Press. 487-494.
11. Guimerà R, Uzzi B, Spiro J, Amaral LAN, (2005) Team assembly mechanisms determine collaboration network structure and team performance. Science 308: 697-702 doi:10.1126/science.1106340.
12. Leskovec J, Kleinberg J, Faloutsos C (2005) Graphs over time: Densification laws, shrinking diameters and possible explanations. In: Proceedings of the 11th ACM SIGKDD International Conference on Knowledge Discovery in Data Mining; 2005; Chicago, IL. ACM. 177-187. doi:10.1145/1081870.1081893.
13. Martins GS, Rossoni L, Csillag JM, Martins ME, Pereira SCF (2010) Gestão de operaçoes no Brasil: uma análise do campo científico a partir da rede social de pesquisadores [Operations management in Brazil: an analysis of the scientific field from the social network of researchers]. RAE eletrônica 9. doi:10.1590/S1676-56482010000200004.
14. Amblard F, Casteigts A, Flocchini P, Quattrociocchi W, Santoro N (2011) On the temporal analysis of scientific network evolution. In: Abraham A, Corchado E, Alhaj R, Snasel V, editors. Proceedings of the 2011 International Conference on Computational Aspects of Social Networks (CASoN 2011); 2011; Salamanca, Spain. IEEE. 169-174. doi:10.1109/CASON.2011.6085938.
15. De Stefano D, Giordano G, Vitale MP, (2011) Issues in the analysis of co-authorship networks. Qual Quant 45: 1091-1107 doi:10.1007/s11135-011-9493-2.
16. Velden TA, Haque A, Lagoze C (2011) Resolving author name homonymy to improve resolution of structures in co-author networks. In: Proceedings of the 11th Annual International ACM/IEEE Joint Conference on Digital Libraries; 2011; Ottawa, ON, Canada. ACM. 241-250. doi:10.1145/1998076.1998122.
17. Torvik VI, Weeber M, Swanson DR, Smalheiser NR, (2005) A probabilistic similarity metric for MEDLINE records: A model for author name disambiguation. J Am Soc Inf Sci Technol 56: 140-158 doi:10.1002/asi.v56:2.
18. Torvik VI, Smalheiser NR, (2009) Author name disambiguation in MEDLINE. ACM Trans Knowl Discov Data 3: 1-29 doi:10.1145/1552303.1552304.
19. Lai R, D'Amour A, Fleming L (2009) The careers and co-authorship networks of U.S. patent-holders, since 1975 (Version 3) [documentation, data, and analysis]. Boston, MA: Harvard Business School; Harvard Institute for Quantitative Social Science [producer and distributor]. Available: http://hdl.handle.net/1902.1/12367.
20. Börner K, Conlon M, Corson-Rikert J, Ding Y (2012) VIVO: A semantic approach to scholarly networking and discovery. USA: Morgan & Claypool. doi:10.2200/S00428ED1V01Y201207WBE002 178 p.
21. Salo D, (2009) Name authority control in institutional repositories. Cataloging & Classification Quarterly 47: 249-261 doi:10.1080/01639370902737232.
22. Jiang W, Wang A, Wu C, Chen J, Yan J (2009) Approach for name ambiguity problem using a multiple-layer clustering. In: CSE '09: Proceedings of the 2009 International Conference on Computational Science and Engineering 4; 2009; Vancouver, Canada. IEEE Computer Society. 874-878. doi:10.1109/CSE.2009.110.
23. Elliott S (2010) Survey of author name disambiguation: 2004 to 2010. Library Philosophy and Practice. Available: http://digitalcommons.unl.edu/libphilprac/473/.
24. Rotenberg E, Kushmerick A, (2011) The author challenge: Identification of self in the scholarly literature. Cataloging & Classification Quarterly 49: 503-520 doi:10.1080/01639374.2011.606405.
25. Piantadosi ST, Tily H, Gibson E, (2012) The communicative function of ambiguity in language. Cognition 122: 280-291 doi:10.1016/j.cognition.2011.10.004.
26. Smalheiser NR, Torvik VI (2009) Author name disambiguation. In: Cronin B, editor. Annual Review of Information Science and Technology 43. Medford, NJ: Information Today, Inc. 287-313.
27. Soames S (2002) Beyond rigidity: The unfinished semantic agenda of Naming and Necessity. New York, NY: Oxford University Press. 379 p.
28. Qiu J, (2008) Scientific publishing: Identity crisis [News Feature]. Nature 451: 766-767 doi:10.1038/451766a.
29. Treeratpituk P, Giles CL (2009) Disambiguating authors in academic publications using random forests. In: Proceedings of the 9th ACM/IEEE-CS Joint Conference on Digital Libraries; 2009; Austin, TX. ACM. 39-48. doi:10.1145/1555400.1555408.
30. Strotmann A, Zhao D, (2012) Author name disambiguation: What difference does it make in author-based citation analysis? J Am Soc Inf Sci Technol 63: 1820-1833 doi:10.1002/asi.22695.
31. Diesner J, Carley KM (2009) He says, she says. Pat says, Tricia says. How much reference resolution matters for entity extraction, relation extraction, and social network analysis. In: CISDA'09: Proceedings of the Second IEEE International Conference on Computational Intelligence for Security and Defense Applications; 2009; Ottawa, Ontario, Canada. Piscataway, NJ: IEEE Press. 9-16.
32. Kang IS, Kim P, Lee S, Jung H, You BJ, (2011) Construction of a large-scale test set for author disambiguation. Inf Process Manag 47: 452-465 doi:10.1016/j.ipm.2010.10.001.
33. Lai R, D'Amour A, Yu A, Sun Y, Fleming L (2011) Disambiguation and co-authorship networks of the U.S. patent inventor database (1975-2010) (Version 3) [documentation, data, and analysis]. Boston, MA: Harvard Business School; Harvard Institute for Quantitative Social Science [producer and distributor]. Available: http://hdl.handle.net/1902.1/15705.
34. Martin MJ, (2011) INSPIRE: Managing metadata in a global digital library for high-energy physics. Communications in Computer and Information Science 240 Part 2: 269-274 doi:_10.1007/978-3-642-24731-6_28.
35. Weiler H, Meyer-Wegener K, Mele S (2011) Authormagic- An approach to author disambiguation in large-scale digital libraries. In: Proceedings of the International Conference on Information and Knowledge Management; 2011; Glasgow, Scotland, UK. ACM. 2293-2296. doi:10.1145/2063576.2063949.
36. Academic Patenting in Europe (2009) Name game algorithm challenge & tools- APE-INV. Available: http://www.esf-ape-inv.eu/index.php?page=15. Accessed 2012 Sep 6.
37. Newman MEJ, (2001) The structure of scientific collaboration networks. Proc Natl Acad Sci U S A 98: 404-409 doi:10.1073/pnas.98.2.404.
38. Holland PW, Leinhardt SL, (1971) Transitivity in structural models of small groups. Small Group Research 2: 107-124 doi:10.1177/104649647100200201.
39. Wasserman S, Faust K (1994) Social network analysis: Methods and applications. New York, NY: Cambridge University Press. 857 p.
40. Newman MEJ, (2003) The structure and function of complex networks. SIAM Rev Soc Ind Appl Math 45: 167-256 doi:10.1137/S003614450342480.
41. Kolaczyk ED (2009) Statistical analysis of network data: Methods and models. New York, NY: Springer. 398 p.
42. Katz JS, Martin BR, (1997) What is research collaboration? Res Policy 26: 1-18 doi:10.1016/S0048-7333(96)00917-1.
43. Granovetter MS, (1973) The strength of weak ties. Am J Sociol 78: 1360-1380.
44. Granovetter M (1983) The strength of weak ties: A network theory revisited. In: Collins R, editor. Sociological Theory 1. San Francisco, CA: Jossey-Bass. 201-233.
45. Watts DJ, Strogatz SH, (1998) Collective dynamics of "small-world" networks. Nature 393: 440-442 doi:10.1038/30918.
46. Soffer SN, Vázquez A, (2005) Network clustering coefficient without degree-correlation biases. Physical Review E 71: 057101 doi:10.1103/PhysRevE.71.057101.
47. Albert R, Jeong H, Barabási AL, (2000) Error and attach tolerance of complex networks. Nature 406: 378-382 doi:10.1038/35019019.
48. Keegan B, Ahmed MA, Williams D, Srivastava J, Contractor N (2010) Dark gold: Statistical properties of clandestine networks in massively multiplayer online games. In: 2010 IEEE Second International Conference on Social Computing (SocialCom 2010), 2010; Minneapolis, MN. IEEE Press. 201-208. doi:10.1109/SocialCom.2010.36.
49. Newman MEJ, (2002) Assortative mixing in networks. Phys Rev Lett 89: 208701 doi:10.1103/PhysRevLett.89.208701.
50. Dorogovtsev SN, Ferreira AL, Goltsev AV, Mendes JFF, (2010) Zero Pearson coefficient for strongly correlated growing trees. Physical Review E 81: 031135 doi:10.1103/PhysRevE.81.031135.
51. Raschke M, Schläpfer M, Nibali R, (2010) Measuring degree-degree association in networks. Physical Review E 82: 037102 doi:10.1103/PhysRevE.82.037102.
52. Litvak N, van der Hofstad R (2013) Uncovering disassortativity in large scale-free networks. Available: http://arxiv.org/abs/1204.0266v4.
53. Friedkin NE, (1981) The development of structure in random networks: An analysis of the effects of increasing network density on five measures of structure. Soc Networks 3: 41-52 doi:10.1016/0378-8733(81)90004-6.
54. Berge C (1966) The theory of graphs and its applications. Doig A, translator. New York, NY: Wiley & Sons. 246 p. [Original work published 1958.].
55. Harary F (1969) Graph theory. Reading, MA: Addison-Wesley. 274 p.
56. Berge C (1973) Graphs and hypergraphs. Minieka E, translator. New York, NY: American Elsevier Publishing Company, Inc. 528 p. [Original work published 1970.].
57. Cormen TH, Leiserson CE, Rivest RL, Stein C (2009) Introduction to algorithms. 3rd ed. Cambridge, MA: MIT Press. 1312 p.
58. Clauset A, Shalizi CR, Newman MEJ, (2009) Power-law distributions in empirical data. SIAM Rev Soc Ind Appl Math 51: 661-703 doi:10.1137/070710111.
59. Clauset A (2012) Power-law distributions (Version 0.0.10) [Software]. Available: http://tuvalu.santafe.edu/~aaronc/powerlaws/.
60. Handcock MS, Jones JH, (2004) Likelihood-based inference for stochastic models of sexual network formation. Theor Popul Biol 65: 413-422 doi:10.1016/j.tpb.2003.09.006.
61. Perline R, (2005) Strong, weak and false inverse power laws. Stat Sci 20: 68-88 doi:10.1214/088342304000000215.
62. Wagner CS, Leydesdorff L, (2005) Network structure, self-organization, and the growth of international collaboration in science. Res Policy 34: 1608-1618 doi:10.1016/j.respol.2005.08.002.
63. Kowalski CJ, (1972) On the effects of non-normality on the distribution of the sample product-moment correlation coefficient. J R Stat Soc Ser C Appl Stat 21: 1-12.
64. Girvan M, Newman MEJ, (2002) Community structure in social and biological networks. Proc Natl Acad Sci U S A 99: 7821-7826 doi:10.1073/pnas.122653799.
65. Newman MEJ, Park J, (2003) Why social networks are different from other types of networks. Physical Review E 68: 036122 doi:10.1103/PhysRevE.68.036122.
66. Foster DV, Foster JG, Grassberger P, Paczuski M, (2011) Clustering drives assortativity and community structure in ensembles of networks. Physical Review E 84: 066117 doi:10.1103/PhysRevE.84.066117.