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      Identification of key films and personalities in the history of cinema from a Western perspective

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          Abstract

          The success of a film is usually measured through its box-office revenue or through the opinion of professional critics; such measures, however, may be influenced by external factors, such as advertisement or trends, and are not able to capture the impact of a film over time. Thanks to the recent availability of data on references among movies, some researchers have started to use citations patterns as an alternative method for ranking movies. In this paper, we propose a novel ranking method for films based on the network of references among movies, calculated by combining four well known centrality indexes: in-degree, closeness, harmonic and PageRank. Our objective is to measure the success of a movie by accounting how much it has influenced other movies produced after its release, from both the artistic and the economic point of view. We apply our method on a subset of the IMDb (Internet Movie Database) citation network consisting of around 47,000 international movies, and we derive a list of films that can be considered milestones in the history of cinema. For each movie we also collect data on its year of release, genres and countries of production, to analyze trends and patterns in the film industry according to such features. We also collect data on 20,000 directors and almost 400,000 performers (actors and actresses), and we use the network of references and our score of movies for evaluating their career, and for ranking them. Since the IMDb dataset we employ is highly biased toward European and North American movies and personalities, our findings can be considered relevant principally for Western culture.

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          Emergence of scaling in random networks

          Systems as diverse as genetic networks or the world wide web are best described as networks with complex topology. A common property of many large networks is that the vertex connectivities follow a scale-free power-law distribution. This feature is found to be a consequence of the two generic mechanisms that networks expand continuously by the addition of new vertices, and new vertices attach preferentially to already well connected sites. A model based on these two ingredients reproduces the observed stationary scale-free distributions, indicating that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.
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            Communication Patterns in Task‐Oriented Groups

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              Word of Mouth for Movies: Its Dynamics and Impact on Box Office Revenue

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                Author and article information

                Contributors
                livio.bioglio@di.unito.it
                ruggero.pensa@unito.it
                Journal
                Appl Netw Sci
                Appl Netw Sci
                Applied Network Science
                Springer International Publishing (Cham )
                2364-8228
                30 November 2018
                30 November 2018
                2018
                : 3
                : 1
                : 50
                Affiliations
                ISNI 0000 0001 2336 6580, GRID grid.7605.4, University of Turin - Dept. of Computer Science, ; C.so Svizzera, 185, Turin, I-10149 Italy
                Author information
                http://orcid.org/0000-0002-4112-067X
                Article
                105
                10.1007/s41109-018-0105-0
                6276061
                562946d1-3450-4276-bbff-528000e52ff1
                © The Author(s) 2018

                Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

                History
                : 10 April 2018
                : 11 October 2018
                Categories
                Research
                Custom metadata
                © The Author(s) 2018

                complex networks,network analysis,citation analysis,centrality,cinema,directors,actors,actresses

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