The interplay of migration and cultural similarity between countries: Evidence from Facebook data on food and drink interests.

Migration has been proposed as one of the factors that shape cultural similarities across countries. However, studying the relationship between culture and migration has been challenging, in part because culture is difficult to quantify. The traditionally used survey questionnaires have a number of drawbacks, including that they are costly and difficult to scale to a large number of countries. To complement survey data, we propose the use of passively-collected digital traces from social media. We focus on food and drink as markers of a country's culture. We then measure similarities between countries in terms of food and drink interests using aggregated data from the Facebook Advertising Platform. Methodologically, we offer approaches to measure the similarity between countries with both symmetric and asymmetric indices. Substantively, we assess the association between migration cultural similarity between countries by comparing our measure of cultural similarity with international migration data. In most countries, larger immigrant populations are associated with more similar food and drink preferences between their country of origin and the country of destination. Our results suggest that immigrants contribute to bringing the culture of their home countries to new countries. Moreover, our study identifies considerable variability in this pattern across countries.

Integrating, summarizing and visualizing GWAS-hits and human diversity with DANCE (Disease-ANCEstry networks).

MOTIVATION: The 1000 Genomes Project (1KGP) and thousands of Genome-Wide Association Studies (GWAS) performed during the last years have generated an enormous amount of information that needs to be integrated to better understand the genetic architecture of complex diseases in different populations. This integration is important in areas such as genetics, epidemiology, anthropology, as well as admixture mapping design and GWAS-replications. Network-based approaches that explore the genetic bases of human diseases and traits have not yet incorporated information on genetic diversity among human populations. RESULTS: We propose Disease-ANCEstry networks (DANCE), a graph-based web tool that allows to integrate and visualize information on human complex phenotypes and their GWAS-hits, as well as their risk allele frequencies in different populations. DANCE provides an interactive way to explore the human SNP-Disease Network and its projection, a Disease-Disease Network. With these functionalities, DANCE fills a gap in our ability to handle and understand the knowledge generated by GWAS and 1KGP. We provide a number of case studies that show how DANCE can be used to explore the relationships between human complex diseases, their genetic bases and variability in different human populations. AVAILABILITY AND IMPLEMENTATION: DANCE is freely available at http://ldgh.com.br/dance/ We recommend using DANCE with Mozilla Firefox, Safari, Chrome or Internet Explorer (v9 or v10). CONTACT: gilderlanio@gmail.com or maira.r.rodrigues@gmail.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

How Many Political Parties Should Brazil Have? A Data-Driven Method to Assess and Reduce Fragmentation in Multi-Party Political Systems.

In June 2013, Brazil faced the largest and most significant mass protests in a generation. These were exacerbated by the population's disenchantment towards its highly fragmented party system, which is composed by a very large number of political parties. Under these circumstances, presidents are constrained by informal coalition governments, bringing very harmful consequences to the country. In this work I propose ARRANGE, a dAta dRiven method foR Assessing and reduciNG party fragmEntation in a country. ARRANGE uses as input the roll call data for congress votes on bills and amendments as a proxy for political preferences and ideology. With that, ARRANGE finds the minimum number of parties required to house all congressmen without decreasing party discipline. When applied to Brazil's historical roll call data, ARRANGE was able to generate 31 distinct configurations that, compared with the status quo, have (i) a significant smaller number of parties, (ii) a higher discipline of partisans towards their parties and (iii) a more even distribution of partisans into parties. ARRANGE is fast and parsimonious, relying on a single, intuitive parameter.

BraX-Ray: an X-ray of the Brazilian computer science graduate programs.

Research productivity assessment is increasingly relevant for allocation of research funds. On one hand, this assessment is challenging because it involves both qualitative and quantitative analysis of several characteristics, most of them subjective in nature. On the other hand, current tools and academic social networks make bibliometric data web-available to everyone for free. Those tools, especially when combined with other data, are able to create a rich environment from which information on research productivity can be extracted. In this context, our work aims at characterizing the Brazilian Computer Science graduate programs and the relationship among themselves. We (i) present views of the programs from different perspectives, (ii) rank the programs according to each perspective and a combination of them, (iii) show correlation between assessment metrics, (iv) discuss how programs relate to another, and (v) infer aspects that boost programs' research productivity. The results indicate that programs with a higher insertion in the coauthorship network topology also possess a higher research productivity between 2004 and 2009.