Measuring long-term impact based on network centrality: Unraveling cinematic citations

PLoS ONE

Volumn 9, Issue 10, 2014, Pages

  Spitz, Andreas ^a   Horvát, Emoke Ágnes ^a,b  

^a UNIVERSITY OF HEIDELBERG   (Germany)

^b Northwestern University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; AUDIOVISUAL EQUIPMENT; CITATION ANALYSIS; COMPARATIVE STUDY; DATA BASE; INFORMATION PROCESSING; INTERNET; NETWORK CENTRALITY; QUANTITATIVE STUDY; SCORING SYSTEM;

EID: 84907805579     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0108857     Document Type: Article

References (56)

1. De Vany A (2011) Hollywood economics: how extreme uncertainty shapes the film industry. Routledge.
2. Bordwell D (1997) On the history of film style. Harvard University Press.
3. Hidalgo CA, Castro A, Rodriguez-Sickert C (2006) The effect of social interactions in the primary consumption life cycle of motion pictures. New Journal of Physics 8: 52.
4. Boatwright P, Basuroy S, Kamakura W (2007) Reviewing the reviewers: The impact of individual film critics on box office performance. Quantitative Marketing and Economics 5: 401-425.
5. Gemser G, Oostrum M, Leenders MA (2007) The impact of film reviews on the box office performance of art house versus mainstream motion pictures. Journal of Cultural Economics 31: 43-63.
6. Doshi L, Krauss J, Nann S, Gloor P (2010) Predicting movie prices through dynamic social network analysis. Procedia Social and Behavioral Sciences 2: 6423-6433.
7. Mestyán M, Yasseri T, Kertész J (2013) Early prediction of movie box office success based on Wikipedia activity big data. PLoS ONE 8: e71226.
8. Pardoe I, Simonton DK (2008) Applying discrete choice models to predict Academy Award winners. Journal of the Royal Statistical Society: Series A (Statistics in Society) 171: 375-394.
9. Sreenivasan S (2013) Quantitative analysis of the evolution of novelty in cinema through crowd-sourced keywords. Scientific Reports 3: 2758.
10. Holbrook MB, Addis M (2008) Art versus commerce in the movie industry: a two-path model of motion-picture success. Journal of Cultural Economics 32: 87-107.
11. McCusker JJ (1992) How much is that in real money?: A historical price index for use as a deflator of money values in the economy of the United States. American Antiquarian Society Worcester, Massachusetts.
12. Atkinson M (2012). Listomania! Sight and Sound.
13. Holbrook MB (1999) Popular appeal versus expert judgments of motion pictures. Journal of Consumer Research 26: 144-155.
14. Thompson K, Bordwell D (1994) Film history: an introduction. McGraw-Hill New York.
15. Wasserman M, Mukherjee S, Scott K, Zeng XHT, Radicchi F, et al. (2014) Correlations between user voting data, budget, and box office for films in the internet movie database. Journal of the Association for Information Science and Technology: n/a-n/a.
16. Garfield E (1955) Citation indexes for science: A new dimension in documentation through association of ideas. Science 122: 108-111.
17. de Solla Price DJ (1965) Networks of scientific papers. Science 149: 510-515.
18. Egghe L, Rousseau R (1990) Introduction to Informetrics: quantitative methods in library, documentation and information science, Elsevier Science Publishers, chapter Citation Analysis. pp. 203-289.
19. Newman MEJ (2001) The structure of scientific collaboration networks. Proceedings of the National Academy of Sciences 98: 404-409.
20. Barabási AL, Jeong H, Néda Z, Ravasz E, Schubert A, et al. (2002) Evolution of the social network of scientific collaborations. Physica A: Statistical mechanics and its applications 311: 590-614.
21. Wuchty S, Jones BF, Uzzi B (2007) The increasing dominance of teams in production of knowledge. Science 316: 1036-1039.
22. Leicht EA, Clarkson G, Shedden K, Newman ME (2007) Large-scale structure of time evolving citation networks. The European Physical Journal B-Condensed Matter and Complex Systems 59: 75-83.
23. Radicchi F, Fortunato S, Castellano C (2008) Universality of citation distributions: Toward an objective measure of scientific impact. Proceedings of the National Academy of Sciences 105: 17268-17272.
24. Peterson GJ, Press S, Dill KA (2010) Nonuniversal power law scaling in the probability distribution of scientific citations. Proceedings of the National Academy of Sciences 107: 16023-16027.
25. Wang D, Song C, Barabási AL (2013) Quantifying long-term scientific impact. Science 342: 127-132.
26. Uzzi B, Mukherjee S, Stringer M, Jones B (2013) Atypical combinations and scientific impact. Science 342: 468-472.
27. Radicchi F, Fortunato S, Vespignani A (2012) Citation networks. In: Scharnhorst A, Börner K, van den Besselaar P, editors, Models of Science Dynamics, Springer Berlin Heidelberg, Understanding Complex Systems. pp. 233-257.
28. Fowler JH, Jeon S (2008) The authority of supreme court precedent. Social networks 30: 16-30.
29. Jaffe A, Trajtenberg M (2002) Patents, Citations, and Innovations: A Window on the Knowledge Economy. MIT Press.
30. Csárdi G, Strandburg KJ, Zalányi L, Tobochnik J, Érdi P (2007) Modeling innovation by a kinetic description of the patent citation system. Physica A: Statistical Mechanics and its Applications 374: 783-793.
31. The Internet Movie Database (IMDb). Alternative interfaces. Available: http://imdb.com/interfaces/. Accessed 2014 September 8.
32. Watts DJ, Strogatz SH (1998) Collective dynamics of 'small-world' networks. Nature 393: 440-442.
33. Amaral LAN, Scala A, Barthlmy M, Stanley HE (2000) Classes of small-world networks. Proceedings of the National Academy of Sciences 97: 11149-11152.
34. Barabási AL, Albert R (1999) Emergence of scaling in random networks. Science 286: 509-512.
35. Albert R, Barabási AL (2000) Topology of evolving networks: Local events and universality. Physical Review Letters 85: 5234-5237.
36. Neville J, Jensen D, Friedland L, Hay M (2003) Learning relational probability trees. In: Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. KDD '03, pp. 625-630.
37. Newman ME (2002) Assortative mixing in networks. Physical review letters 89: 208701.
38. Foster JG, Foster DV, Grassberger P, Paczuski M (2010) Edge direction and the structure of networks. Proceedings of the National Academy of Sciences 107: 10815-10820.
39. Barabási AL (2005) The origin of bursts and heavy tails in human dynamics. Nature 435: 207-211.
40. Kossinets G, Watts DJ (2006) Empirical analysis of an evolving social network. Science 311: 88-90.
41. Palla G, Barabási AL, Vicsek T (2007) Quantifying social group evolution. Nature 446: 664-667.
42. Leskovec J, Kleinberg J, Faloutsos C (2007) Graph evolution: Densification and shrinking diameters. ACM Transactions on Knowledge Discovery from Data 1.
43. Hidalgo CA, Rodriguez-Sickert C (2008) The dynamics of a mobile phone network. Physica A: Statistical Mechanics and its Applications 387: 3017-3024.
44. Szell M, Lambiotte R, Thurner S (2010) Multirelational organization of largescale social networks in an online world. Proceedings of the National Academy of Sciences 107: 13636-13641.
45. Mucha PJ, Richardson T, Macon K, Porter MA, Onnela JP (2010) Community structure in time-dependent, multiscale, and multiplex networks. Science 328: 876-878.
46. Davis DA, Chawla NV (2011) Exploring and exploiting disease interactions from multi-relational gene and phenotype networks. PLoS ONE 6: e22670.
47. Gómez-Gardeñes J, Reinares I, Arenas A, Floría LM (2012) Evolution of cooperation in multiplex networks. Scientific Reports 2: 620.
48. Cardillo A, Gómez-Gardeñes J, Zanin M, Romance M, Papo D, et al. (2013) Emergence of network features from multiplexity. Scientific Reports 3: 1344.
49. Newman ME (2010) Networks. An introduction. Oxford.
50. Magnani M, Rossi L (2011) The ML-model for multi-layer social networks. In: Proceedings of the 2011 International Conference on Advances in Social Networks Analysis and Mining. pp. 5-12.
51. Grindrod P, Parsons MC, Higham DJ, Estrada E (2011) Communicability across evolving networks. Physical Review E 83: 046120.
52. Holme P, Saramäki J (2012) Temporal networks. Physics Reports 519: 97-125.
53. Padgett JF, Ansell CK (1993) Robust action and the rise of the Medici, 1400- 1434. American journal of sociology: 1259-1319.
54. Baxandall M (1985) Patterns of intention: On the historical explanation of pictures. Yale University Press.
55. See L, Comber A, Salk C, Fritz S, van der Velde M, et al. (2013) Comparing the quality of crowdsourced data contributed by expert and non-experts. PLoS ONE 8: e69958.
56. Callaway DS, Newman ME, Strogatz SH, Watts DJ (2000) Network robustness and fragility: Percolation on random graphs. Physical Review Letters 85: 5468.