Modeling the Emergence of Contact Languages

Contact languages are born out of the non-trivial interaction of two (or more) parent languages. Nowadays, the enhanced possibility of mobility and communication allows for a strong mixing of languages and cultures, thus raising the issue of whether there are any pure languages or cultures that are unaffected by contact with others. As with bacteria or viruses in biological evolution, the evolution of languages is marked by horizontal transmission; but to date no reliable quantitative tools to investigate these phenomena have been available. An interesting and well documented example of contact language is the emergence of creole languages, which originated in the contacts of European colonists and slaves during the 17th and 18th centuries in exogenous plantation colonies of especially the Atlantic and Indian Ocean. Here, we focus on the emergence of creole languages to demonstrate a dynamical process that mimics the process of creole formation in American and Caribbean plantation ecologies. Inspired by the Naming Game (NG), our modeling scheme incorporates demographic information about the colonial population in the framework of a non-trivial interaction network including three populations: Europeans, Mulattos/Creoles, and Bozal slaves. We show how this sole information makes it possible to discriminate territories that produced modern creoles from those that did not, with a surprising accuracy. The generality of our approach provides valuable insights for further studies on the emergence of languages in contact ecologies as well as to test specific hypotheses about the peopling and the population structures of the relevant territories. We submit that these tools could be relevant to addressing problems related to contact phenomena in many cultural domains: e.g., emergence of dialects, language competition and hybridization, globalization phenomena.</p

Folksonomies, the Semantic Web, and Movie Recommendation

While the Semantic Web has evolved to support the meaningful exchange of heterogeneous data through shared and controlled conceptualisations, Web 2.0 has demonstrated that large-scale community tagging sites can enrich the semantic web with readily accessible and valuable knowledge. In this paper, we investigate the integration of a movies folksonomy with a semantic knowledge base about user-movie rentals. The folksonomy is used to enrich the knowledge base with descriptions and categorisations of movie titles, and user interests and opinions. Using tags harvested from the Internet Movie Database, and movie rating data gathered by Netflix, we perform experiments to investigate the question that folksonomy-generated movie tag-clouds can be used to construct better user profiles that reflect a user's level of interest in different kinds of movies, and therefore, provide a basis for prediction of their rating for a previously unseen movie

Data from: Significance and popularity in music production

Creative industries constantly strive for fame and popularity. Though highly desirable, popularity is not the only achievement artistic creations might ever acquire. Leaving a longstanding mark in the global production and influencing future works is an even more important achievement, usually acknowledged by experts and scholars. ‘Significant’ or ‘influential’ works are not always well known to the public or have sometimes been long forgotten by the vast majority. In this paper, we focus on the duality between what is successful and what is significant in the musical context. To this end, we consider a user-generated set of tags collected through an online music platform, whose evolving co-occurrence network mirrors the growing conceptual space underlying music production. We define a set of general metrics aiming at characterizing music albums throughout history, and their relationships with the overall musical production. We show how these metrics allow to classify albums according to their current popularity or their belonging to expert-made lists of important albums. In this way, we provide the scientific community and the public at large with quantitative tools to tell apart popular albums from culturally or aesthetically relevant artworks. The generality of the methodology presented here lends itself to be used in all those fields where innovation and creativity are in play

creole / non-creole transition.

<p>The two 3D graphs report the fraction of the Mulattos and Bozal populations speaking asymptotically <i>C</i> (<b>a</b>) and <i>E</i> (<b>b</b>), respectively, as a function of the coordinates <i>N</i>_<i>M</i>/(<i>N</i>_<i>B</i>+<i>N</i>_<i>M</i>) and (<i>N</i>_<i>M</i>+<i>N</i>_<i>B</i>)/(<i>N</i>_<i>M</i>+<i>N</i>_<i>B</i>+<i>N</i>_<i>Eu</i>). A relatively sharp transition line is observed separating the region where creole is predicted to emerge from the one in which the European language is predicted to dominate. Simulations are performed with parameters <i>γ</i> = 0.8, <i>ε</i> = 0.06, <i>δ</i> = 0.1 and <i>N</i> = <i>N</i>_<i>M</i>+<i>N</i>_<i>B</i>+<i>N</i>_<i>Eu</i> = 10000.</p

Clustering in the creole formation process.

<p>Points are the projection of the census data (See Tables A-D in the <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0120771#pone.0120771.s001" target="_blank">S1 Supporting Information</a>) in the plane (<i>N</i>_<i>M</i>/(<i>N</i>_<i>B</i>+<i>N</i>_<i>M</i>), (<i>N</i>_<i>M</i>+<i>N</i>_<i>B</i>)/(<i>N</i>_<i>M</i>+<i>N</i>_<i>B</i>+<i>N</i>_<i>Eu</i>)). Red circles mark States where a creole language emerged while purple ones identify States where a creole language historically did not emerge. The gray stripe is the outcome of our modeling scheme and separates the regions where respectively the creole <i>C</i> (above the stripe) and the European <i>E</i> (below the stripe) represent the dominant language (i.e., spread among more than the 80% of the population) in the Mulattos and Bozal populations in the asymptotic states of the model. The two black curves delimiting the gray stripe and the dashed line in the middle are obtained by simulations performed with the same parameters <i>γ</i> = 0.8, <i>δ</i> = 0.1 and <i>N</i> = <i>N</i>_<i>M</i>+<i>N</i>_<i>B</i>+<i>N</i>_<i>Eu</i> = 10000, with <i>ε</i> ranging from 0.05 (bottom black curve) to 0.07 (upper black curve), passing through 0.06 (dashed curve). The horizontal axis has been artificially expanded by a power 0.2.</p

Detailed analysis of Georgia and South Carolina Counties.

<p>Prediction about the emergence of a creole language in those Counties and Parishes of Georgia (GE) and South Carolina (SC) for which census data collected in year 1790 are available. Blue Counties lie below the transition stripe shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0120771#pone.0120771.g001" target="_blank">Fig 1</a> (see also Fig H and I in the <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0120771#pone.0120771.s001" target="_blank">S1 Supporting Information</a>) so that our model predicts that creole did not emerge. On the contrary, orange Counties lie above the transition stripe where our model predicts the formation of creole. The green Counties lie in the grey transition region. Although modern County boundaries are shown, only the labels corresponding to the Counties existing in year 1790 are displayed. Since only part of Georgia was colonized in 1790, modern Counties that were not yet colonized are depicted in white (the western part of modern Georgia has been cut out). The dark gray Counties, though already existing in 1790, were not involved in the census operations. The boundary between GE and SC is marked by the river Savannah. This map was produced with the <i>Inkscape</i> open source software (<i><a href="http://www.inkscape.org/" target="_blank">http://www.inkscape.org/</a></i>).</p

Interaction topology.

<p>Europeans (<i>Eu</i>), can speak only in their European language to Mulattos (<i>M</i>) and with probability <i>ϵ</i> to Bozal (<i>B</i>). Mulattos and Bozal communicate among them both as <i>speakers</i> and <i>hearers</i> (refer to the Materials and Methods section). They can speak European (<i>E</i>), African (<i>A</i>), or the emergent creole (<i>C</i>). As noted above, we cannot yet get in the multitude of languages spoken by the Bozal slaves and simply represent the set of languages as a unique language <i>A</i>. However, to model in a coarse grained fashion the African multilingualism, we introduce a parameter <i>δ</i> that accounts for the possibility that a Bozal slave would success to communicate with another in an African language (refer to the Materials and Methods section for details).</p