Evolutionary Dynamics of Cultural Memes and Application to Massive Movie Data Seungkyu Shin Graduate School of Culture Technology and BK21 Plus Postgraduate Programme for Content Science, Korea Advanced Institute of Science & Technology, Daejeon, Republic of Korea 34141 Juyong Park Graduate School of Culture Technology and BK21 Plus Postgraduate Programme for Content Science, Korea Advanced Institute of Science & Technology, Daejeon, Republic of Korea 34141 and Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom CB2 1LR The profound impact of Darwin's theory of evolution on biology has led to the acceptance of the theory in many complex systems that lie well beyond its original domain. Culture is one example that also exhibits key Darwinian evolutionary properties: Differential adoption of cultural variants (variation and selection), new entities imitating older ones (inheritance), and convergence toward the most suitable state (adaptation). In this work we present a framework for capturing the details of the evolutionary dynamics in cultural systems on the \meme"|the cultural analog of the biological gene|level, and analyze large-scale, comprehensive movie{meme association data to construct a timeline of the history of cinema via the evolution of genres and the rise and fall of prominent sub- genres. We also identify the impactful movies that were harbingers to popular memes that we may say correspond to the proverbial \Eve" of the human race, shining light on the process by which certain genres form and grow. Finally, we measure how the impact of movies correlates with the experts' and the public's assessment. I. INTRODUCTION illustrate his theory of biological evolution [1]. To make a deeper analogy with the current under- Charles Darwin's theory of evolution has been highly standing of biological evolution, we study cultural evolu- influential in understanding the universal properties of tion occurring on the level of the \meme"|the cultural systems that reproduce and change over generations. In analog of the biological gene|which acts as a unit car- his seminal work The Origin of Species, Darwin postu- rying cultural ideas that can be transmitted from one lated that all organisms share a common ancestor, change mind to another [13{16]. While the analogy between the over time through natural selection, and give rise to new evolution in biology and in culture are clear (as Darwin species that underlie the impressive present-day diversity himself has recognized), specific mechanisms at work can of living things on Earth. On the most fundamental level, be very different [17{19], as in the case of meme and gene. Darwinian evolution stipulates that organisms evolve to The most important difference is that in cultural evolu- adapt to the environment by an iterative process com- tion there can be an arbitrary number of \parents" from prising variation, competition, and inheritance [1{3]. Its whom a newly created work can take after since the ac- profound contribution to the understanding of biologi- tion of inheritance takes place in the mind of the creator cal evolution has prompted an active effort to apply the of new works, unlike the precisely two in sexual repro- theory to many domains other than biology, leading to duction of organisms. This is visualized in more detail the coinage of the expression \Universal Darwinism" [4]. in Fig. 1 (a) and (b). In biological evolution (Fig. 1 (a)), Culture is one example domain where evolution with each gene of an offspring always comes from either of identifiable key Darwinian properties can be observed, the two of its parents (or rare cases of mutations or re- evolving through a differential adoption of cultural vari- combination error). In cultural evolution (Fig. 1 (b)) on ants in a manner analogous to the evolution of biologi- the other hand, a new work's memes can originate from cal species [5{10]: A new cultural product displays de- an arbitrary number of \parents" and undergo frequent tectable variations from the others, competes with others mutations. in the marketplace to be selected by consumers. Success- While the study of cultural evolution is an active arXiv:1903.02197v1 [physics.soc-ph] 6 Mar 2019 ful variants are selected and thrive over others that may field [6, 17, 20{30], recent developments in data and then perish and disappear. The successful variants fur- machine-learning techniques are providing even newer ther inspire the creators of later products to imitate or in- opportunities for understanding cultural evolution by herit their properties and further adapt [11, 12]. Cultural leveraging the rich feature sets available of cultural prod- evolution is thus the idea that beliefs, knowledge, arti- ucts [31, 32]. In addition, the commodified nature of facts, and human creations that constitute culture un- cultural products in the present day means that the con- dergo a deeply analogous process by which species evolve sumer choice as selection pressure is increasing, speeding through selective retention of favorable variants. In fact, up the rate of evolution that could allows us to more eas- in The Origin of Speies, Darwin himself frequently cited ily observe the evolutionary process in a short time scale. cultural changes (primarily linguistic developments) to Cultural production in today's high-risk, high-return en- vironment of cultural production would also benefit from 2 (a) Biological Evolution (b) Cultural Evolution A couple of parenthood Possible single or multiple parenthood Rare Mutation Frequent Mutation or Recombination error (Creativity) Transmission between Possible transimission between adjacent generations distant generations (c) Representation of Movies with Meme Vector “Special “Love “Prison “Survival” Effects” Story” Escape” “Superhero” “Dreams” Schindler’s List 0.837 0.354 0.388 . 0.258 0.041 0.154 (1993) The Shawshank Redemption 0.697 0.471 0.384 . 0.986 0.14 0.475 (1994) Titanic 0.658 0.928 0.957 . 0.086 0.054 0.199 (1997) . The Matrix 0.435 0.984 0.462 . 0.336 0.417 0.527 (1999) The Dark Knight 0.473 0.686 0.249 . 0.178 0.96 0.165 (2008) Inception 0.46 0.852 0.313 . 0.302 0.219 0.995 (2010) FIG. 1. The analogy and the differences between evolutions in (a) biology on the gene level, and (b) culture on the meme level. Cultural evolution features an arbitrary number (from single to multiple) of parents, frequent mutations, and transmission between distant generations of memes. (c) Cultural products (movies in our paper) can be represented as a meme vector of the relevance score (association strength) with each meme. We use a meme vector of dimension 900, providing a rich set of descriptors for movies. The shaded components indicate the memes with particularly high relevance score (0:8 or greater). a deeper scientific understanding of the cultural evolu- March 2015. Tags are user-attached metadata that de- tionary process. scribe the movies' themes or related concepts, typically a single word or a short phrase such as \nostalgic," \ar- tificial intelligence," and so forth. The 1; 100 unique tags feature numerical relevance (association) scores between II. DATA AND MOVIE MEMES 0 and 1 to movies, computed via machine-learning algo- rithms on user-contributed reviews and ratings [34]. Tags We analyze the data from MovieLens, a movie rec- thus contain bits of information about the movies, and ommendation service that also provides a stable bench- each movie is composed of different combinations of such mark dataset to researchers [33]. The dataset contains tags with varying relevance scores. Therefore we can con- 20 million ratings and 465; 000 tags on 27; 000 movies sider each tag as a meme constituting the movies. The provided by 138; 000 users between January 1995 and 3 (a) Action (1788) : “Action / Fight Scenes / Fast paced” (b) Adventure (1475) : “Adventure / Special Effects / Franchise” Drama (5568) : “Drama / Relationships / Intimate” Romance (2094) : “Love story / Relationships / Love” Documentary (470) : “Intimate / Narrated / Political” Comedy (4029) : “Comedy / Humor / Goofy” Animation (465) : “Animal Movie / Computer Animation / Talking Animals” Fantasy (750) : “Fantasy / Special Effects / Magic” Sci-Fi (684) : “Sci Fi / Special Effects / Future” Thriller (1348) : “Suspense / Tense / Murder” Mystery (777) : “Mystery / Murder / Suspense” Horror (1029) : “Horror / Splatter / Supernatural” Crime (1829) : “Crime / Murder / Corruption” (c) Phylogeny of Movie History Musical Sci-Fi Fantasy Adventure Romance Comedy Animation Action Drama Horror Documentary Crime Thriller Mystery 1920 1940 1960 1980 2000 2020 Year FIG. 2. The correspondence between the network communities of movies and genres. (a) Network of movies based on the meme vector similarity between movies (PCC larger than 0:8). The communities detected in the network (colored) correspond well to established genres. (b) Top three relevant memes within each genre. (c) Phylogeny of movie history showing how the movie genres have grown over time. The movie production years are given in the x-axis. Cross-linkage between genres is shown to increase over time, leading to hybrid genres such as romantic comedy (romance and comedy). parallel between gene and meme are clear from Fig. 1; as production companies), \Oscar", \best of 2005", etc. In an individual organism can be viewed as a set of distinct addition, we consolidated tags that are synonyms, e.g. genomes, an individual movie can be viewed as a distinct “fight scenes" and “fighting", using hierarchical cluster- set of memes. In