Following the discussion in these two posts, and various conversations after a plenary talk of Pascal Boyer at the Human Behavior and Evolution Society Conference last summer, I decided, together with Alex Mesoudi, to write a paper comparing some aspects of cultural attraction and “standard” cultural evolution. (This is, by the way, my current main research interest, and I hope to have more to say about it in the future).
A new research I co-authored with Stefano Ghirlanda and Hal Herzog has just been published in PLOS ONE (the paper is open access and can be found here). In this paper we continue our analysis of dog breeds popularity as a particularly interesting (and data-rich) cultural domain. We had already shown that the choice of which puppy one buys seems largely driven by fashion, i.e. social influence, more than by functional considerations (see my post from last year). Now we looked explicitly at one source of social influence, i.e. movies featuring dogs.
We found that indeed there is a strong effect of movies on the popularity of dog breeds. While this is not probably a shocking result, it is quite interesting to have precise quantitative data. We used the AKC database, totalling over 65 million dog registrations from 1926 to 2005, and analysed a total of 87 movies featuring dogs. The impact of movies has been large. We found, for example, that movies have an influence that can last up to 10 years from the initial release. The 10 movies with the strongest 10-years effect are associated with 800,000 more registrations in the AKC then what would have been expected from pre-release trends. A striking example is the 1959 Disney movie The Shaggy Dog. The registrations of Old English Sheepdogs were stable on around 100 dogs per year in the ten years preceding the release of the movie. In 1969 only, ten years after, 4,226 Old English Sheepdogs were registered.
We also found that the more a movie was successful (we estimated the number of viewers from the opening weekend earnings) the more impacted on the popularity of the breeds of the dog featured. Another interesting finding is that the influence of movies has decreased during the century. Earlier movies are in general associated with larger trend changes than later movies. This suggests that movies – perhaps because of an increased competition with other media, such as television, and, more recently, the internet – have gradually lost their influence on pop-culture.
Together with our previous results, which showed that behavioural characteristics, longevity, or health were not correlated with breeds popularity, this new analysis provide a quite clear picture: we do not choose, on average, dogs because they are more healthy or, for example, trainable, but because we see them in the neighbours garden, or in the last blockbuster. Why this is not bad per se (copying what others do is a quite effective strategy in many situations) is definitely bad for dogs. The only feature that we found to positively correlate with popularity is indeed the presence of genetic diseases. Of course this does not mean that dog owners actively look for breeds with genetic diseases, but, as a minimum, that they do not keep this in consideration when choosing a puppy and, more worryingly, that the huge differences in popularity and the rapid increases of some breeds provoke over-breeding which results, in turn, in an increase of genetic disorders. My take-home message here is: don’t follow fashions when choosing a puppy!
Now a couple of more cultural-evolution related questions. First: how important is how the dog is presented in a movie for the effect on the popularity of the breed? We excluded few movies in which the dog was clearly a negative character (Cujo, for example) but we did not analyse in detail this issue. My feeling is that is not so important. While our data end in 2005, the AKC provides the rankings for more recent years. Hal noted the steady increase of French bulldogs (they were at the 54th position in 2003, and at the 11th last year). It happens that in a famous scene of the hugely popular movie The Hangover, Mike Tyson holds in his arm a French bulldog (see the video below from around 1:30). Since the movie is from 2009 (and we do not have the data…) is not clear whether the movie had an influence on the increase on popularity or if it is the other way around (i.e. the authors capitalised on the growing popularity of the breed and used it for the movie), but the dog is not more than a prop in the scene in question. The idea is that the mere presence of a dog in a popular movie makes it accessible and that, as features of different breeds are, in a sense, neutral (see below), a simple advantage in accessibility generates a cascade of effects (e.g. people will talk about that breed more than about other breeds) that may greatly influence popularity.
(the case of French bulldogs is also relevant for the previous point, as French bulldogs carry – in Hal’s words – a huge load of genetic disorders)
Second: does this result suggest that we are copy-machines, easily influenceable by evil Hollywood’s producers? I do not think so. As I mentioned above I consider the choice of a breed as being, by and large, neutral. This does not mean that all breeds are equal (of course they are not). However, given the choice of owning a dog (this, I think, is a non-neutral choice. Would be interesting to see whether movies influences the total number of dogs in time), the features of different breeds can be reasonably adapted to one’s own habits (or the other way around) so that the choice has, in the majority of cases, not enormous effects on the owners. Many people that are buying French bulldogs now would have probably bought poodles fifty years ago. Something similar happens, for example, for baby names (of course they are different; yes, some of them may have an effect on your life [but see here], but, in the majority of cases, being called Alberto or Stefano does not make much difference). For this kind of cultural traits I would indeed expect social influence and media having a strong effect on popularity, but less for traits that implies more important outcomes. We are not blind copy-machines, but selective copy-machines.
Ghirlanda S, Acerbi A, Herzog H (2014) Dog Movie Stars and Dog Breed Popularity: A Case study on Media Influence on Choice. PLoS ONE 9(9): e106565
Many studies of cultural evolution have focused on how transmission biases affect the likelihood of cultural traits of being transmitted. The concepts are quite intuitive. An useful distinction is between content biases, when the intrinsic features of a cultural trait make it more likely to spread (the effectiveness of a tool may be a content bias, but also a sexual hint in an image), and context biases, when the likelihood is determined by the context, as when we tend to dress as our friends/coworkers (conformist bias; but one can do the opposite, and prefer unpopular cultural traits), or as when I was trying to have a young Axl Rose haircut (prestige bias – see also my picture on the left).
Some interesting works in cultural evolution have examined, with analytical and simulation models, the adaptivity of transmission biases (e.g. did my Axl Rose haircut make me rich and/or attractive? It did not, but, on average, prestige bias may be useful) or examined the transmission biases long-trend dynamics in idealised situations (e.g. how fast will a new cultural trait “invade” a population of conformist individuals? or of anti-conformists? etc.). Other works investigated, in controlled experiments, if people are indeed subject to transmission biases when copying from others (they are, with caveat).
What is partly missing is an understanding of the impact of transmission biases in real life cultural dynamics. We recently had a paper accepted in Evolution and Human Behavior that tackles this problem. In brief (much more is in the paper!): (1) we focused on the turnover of popular traits, i.e. on how many new traits enter in a top-list of a certain size for a certain cultural domain (like here); (2) we used some predictions on how the turnover would look like if there were no biases, that is, if everybody would just copy others at random (neutral model of cultural evolution); and (3) we showed how these predictions differ if biases are instead present.
The turnover of some cultural domains, for example recent baby names in USA, looks like the red line in the figure above, signalling that people tend to prefer relatively un-common names. The turnover of others, like early baby names, musical preferences of Last.fm users who subscribed to genre-based groups (“80s Gothic”, “Acid Jazz”) , or usage of colour terms in English language books, looks instead like the blue line, signalling a conformist bias, or a content-based bias (which I call “attraction”).
Overall, turnover can be calculated when we have periodical top lists, or, more generally, when we can “count” the frequency of items trough time. Given the ubiquity of this kind of information in digital form, one can use this methodology to infer individual behaviour from population-level, aggregate, data for several cultural domains.
Acerbi, A. and Bentley, R.A. (2014), Biases in cultural transmission shape the turnover of popular traits, Evolution and Human Behavior, in press.
Almost one year ago, we published a paper in which we described a large scale analysis of cultural/literary trends, realised using the google books ngram corpus. In particular, we showed that, trough a relatively simple extraction of emotion-realted words (words semantically related to “main” emotions like joy, sadness, anger, etc.), it was possible to detect some clear tendencies, such as a general decline in the emotional “tone” of books published in the twentieth century – or at least in the frequencies of emotions words -, a divergence between American and British English – with the former being more emotional -, and, finally, the existence of distinct periods of “literary mood” in the last century.
Related to the last point, PLOS ONE just published a follow up of this research, in which we correlate this literary mood with the past century economic trend. The image below shows the main point of our study.
The red line is what we called “Literary Misery Index” (how “sad” are books in a certain year, on average), that we extracted from the books in the Google Corpus, while the black line is a 11-years moving average of the economic Misery index (how “bad” is economy in a certain year), a well-known economic index, realised adding inflation and unemployment rates. The two trends are strongly correlated (you can read more in the Bristol University press release here, and, of course, in the original paper).
As for the previous work, we are glad we had some media attention (see for example The New York Times and The Guardian), which generated quite a lot of buzz. Not surprisingly, this included some criticism. It is interesting that, while some commenters think that we are “stating the obvious”, others accuse us to apply a “crude” causal determinism, and to defend the implausible claim that economy “dictates” literature and culture.
To me, I am more sympathetic to the state-the-obvious side of the debate so I am not going to write on this (but: we are able to substantiate an “obvious” claim – economic conditions influence cultural mood – with empirical data, as well as provide some refinement, for example providing a possible estimate of a time lag). Regarding the other side of the debate, I would not say that economy “dictates” literature, but it is quite plausible that economic conditions may have an effect on mood. This is not just common sense: many studies link, for example, financial strain and depressive symptoms (here), or general psychological distress (here). If the google corpus is a good barometer of a culture mood, our results are not particularly surprising. This does not mean of course that all books published, for example, in the 80s, were gloomy (I feel like I am underestimating the intelligence of the readers, but some journalists seem to criticise our result on this shaky basis), or that economy alone has a causal effect on literature or culture.
On a related note, given that I can safely assume that most of the “crude determinism” critics come from literary, or, in general humanistic, departments: I like to imagine that a well-known German philosopher, that once was very praised in there, would be very supportive of our work!
Bentley R.A., Acerbi A., Ormerod P., Lampos V., (2014), Books Average Previous Decade of Economic Misery, PLoS ONE, 9 (1): e83147.
A book chapter written (now almost two years ago…) by Magnus Enquist, Stefano Ghirlanda, and myself has just been published. It sums up pretty well part of the research I was carrying with the Centre for the Study of Cultural Evolution in Stockholm.
We explored the concept of “regulatory traits”, that is, cultural traits that are both socially transmitted (they are “cultural”), and influence directly (“regulate”) cultural dynamics. While the distinction between regulatory and non-regualtory traits is not always clearcut (potentially everything one learns could influence her future behaviour), the regulatory aspects of some traits seem particularly evident. For example, consider the regulatory trait “learning from school teachers”. This is both socially transmitted (parents do an effort to convince their children that learning from teachers at school is good) and influences directly – at least this is what parents aim for – cultural dynamics (children will listen to what teachers say at school). Again, teenagers may attempt to persuade their peers (“socially transmitted” part) to not listen to adults (“regulatory” part).
At a more abstract level, the same propensity to engage in cultural learning can be subjected to cultural influence and hence be a regulatory trait (you learn from others whether – or how much – to learn from others). Although this may seem not more than the starting of an headache-y riddle, we showed previously that, if this is the only force working in a system, the paradoxical result is that everybody will converge to not learn from other at all. Why is it so? “Conservative” individuals (i.e. individuals who do not engage in cultural learning) have indeed an inherent advantage as cultural models in respect to “open” individuals (i.e. individuals who engage in cultural learning): when a conservative individual will meet with an open one, it is more likely that the open will copy the conservative than vice-versa, pushing the population towards conservatism. Another way to think about this: imagine a group of, say, ten people, with t-shirts of different colours, playing the (well-known, of course) “copy the colour of my t-shirt” game. One of the individual will never copy others, while the other nine have a variable probability to engage in social learning. The only possible outcome of this game, given enough repeated iterations, is that everybody will end up wearing the same colour of the conservative individual, even if there is nothing in his t-shirt that makes it better than the others.
Even though the outcomes described above are the product of extreme, and scarcely realistic, conditions, regulatory traits-driven dynamics can interact with other aspects involved in cultural transmission, generating more complex, and – hopefully – interesting, outcomes (we explore, among others, in-group biases and fashion-like dynamics). Conservatism itself is, in my opinion, an underestimated force with regard to the spreading of cultural traits. All other things being equal, a cultural trait that makes its bearers more conservative will be more likely to have success than a cultural trait that does not (I like to think in this term to the first of the ten commandments, which sounds “thou shalt have no other gods before me”, rather than “look around for other gods, and you’ll see I am the coolest”).
Moreover, a part from having effects in cultural dynamics, regulatory traits represent a difference between cultural and biological evolution. This is a “hot” topic in modern cultural evolutionary theory so I do not want to go in depth here (let me just say at least that I think it is interesting to study also the differences between the two evolutionary processes). “Rules” of genetic transmission tend to not be under genetic control, and models of cultural evolution inspired by evolutionary biology tend to consider the rules of cultural transmission (for example the propensity to learn from others) in the same way not under “cultural control” (they are usually considered under genetic control). However, the fact that cultural information can be transmitted in many different ways creates the opportunity to regulate the flow of information in a fine–grained and context–dependent way, and regulatory traits can have a role in this process.
Acerbi A., Ghirlanda S., Enquist M. (2014), Regulatory traits: Cultural Influences on Cultural Evolution, in: Cagnoni, S. et al. (Eds.), Evolution, Complexity, and Artificial Life, Springer, pp. 135 – 147