Immigrant community integration in world cities

As a consequence of the accelerated globalization process, today major cities all over the world are characterized by an increasing multiculturalism. The integration of immigrant communities may be affected by social polarization and spatial segregation. How are these dynamics evolving over time? To what extent the different policies launched to tackle these problems are working? These are critical questions traditionally addressed by studies based on surveys and census data. Such sources are safe to avoid spurious biases, but the data collection becomes an intensive and rather expensive work. Here, we conduct a comprehensive study on immigrant integration in 53 world cities by introducing an innovative approach: an analysis of the spatio-temporal communication patterns of immigrant and local communities based on language detection in Twitter and on novel metrics of spatial integration. We quantify the "Power of Integration" of cities --their capacity to spatially integrate diverse cultures-- and characterize the relations between different cultures when acting as hosts or immigrants.Comment: 13 pages, 5 figures + Appendi

Considering a lexicographic plan for Gabon within the Gabonese language landscape

This article raises a number of questions that should be dealt with in drawing up a lexicographic plan for Gabon. For which of the Gabonese languages should lexicographic units be established? This question entrains the issue of inventorying the Gabonese languages and their standardization as well as the issue of language planning for Gabon. What is the status of those foreign languages widely spoken in Gabon? What about French? Should Gabon keep importing its French dictionaries from France, or should the Gabonese compile their own French dictionaries, including French words and expressions exclusively used in Gabon? Finally, after trying to answer these questions, a number of suggestions are made for the establishment of a lexicographic plan for Gabon

A Guide for Using a Dictionary

Learning vocabulary as the building blocks for communication plays an important role in foreign and second language learning as it is an essential component of becoming a fluent foreign language user. Very often vocabulary learning occurs as a product of reading. While reading, a sentence could be incomprehensible to the readers by the occurrence of a single unknown word and the learner can consult the dictionary to understand the text. Through regular reading the learner may remember and recognize some new words he/she came across in his/her reading. Of course, we all should be aware that no dictionary contains every word in the language. The sciences, medicine and technology generate a lot of words that never make it into a dictionary; numerous foreign words that appear in English-language contexts are left out. A great many words are invented all the time and then they simply vanish from the record. This material has been prepared as a guide for using various types of dictionaries with the aim of increasing foreign/second learners’ vocabulary in English as a foreign/second language. It is convenient for the learners of different levels of English language and appropriate to be used in different teaching/learning environments, both in face-to-face and elearning. A guide for using a dictionary is designed to be used by high school teachers in the field of agriculture and related fields, and agricultural advisors in Serbia. Also, it can be useful for the current and future students of both agriculture and other fields of science, and for professionals in other domains. Printing of the guide is funded by TEMPUS project CaSA Building Capacity of Serbian Agricultural Education to Link with Society, coordinated by University of Belgrade, Faculty of Agriculture

Gender detection of Twitter users based on multiple information sources

Twitter provides a simple way for users to express feelings, ideas and opinions, makes the user generated content and associated metadata, available to the community, and provides easy-to-use web and application programming interfaces to access data. The user profile information is important for many studies, but essential information, such as gender and age, is not provided when accessing a Twitter account. However, clues about the user profile, such as the age and gender, behaviors, and preferences, can be extracted from other content provided by the user. The main focus of this paper is to infer the gender of the user from unstructured information, including the username, screen name, description and picture, or by the user generated content. We have performed experiments using an English labelled dataset containing 6.5 M tweets from 65 K users, and a Portuguese labelled dataset containing 5.8 M tweets from 58 K users. We have created four distinct classifiers, trained using a supervised approach, each one considering a group of features extracted from four different sources: user name and screen name, user description, content of the tweets, and profile picture. Features related with the activity, such as number of following and number of followers, were discarded, since these features were found not indicative of gender. A final classifier that combines the prediction of each one of the four previous individual classifiers achieves the best performance, corresponding to 93.2% accuracy for English and 96.9% accuracy for Portuguese data.info:eu-repo/semantics/acceptedVersio

William Adams and Early English Enterprise in Japan

(Massarella paper): The William Adams story has been told many times, but not completely. This paper corrects matters of fact and revises matters of interpretation. It adds new information about Adams the man and examines the fabrication of the myth of William Adams or Miura Anjin that has developed since the late nineteenth century. (Farrington paper): The English factory at Hirado, Japan, which lasted from 1613 to 1623 was established in the hope of increasing East India Company trade with China and Ayuthaya, Thailand. Out of 7 voyages, only 4 reached destination; and the factory was wound up as a commercial failure.Williams Adams, Miura Anjin, the English factory, Hirado, Japan, East India Company.

Detecting portuguese and english Twitter users’ gender

Existing social networking services provide means for people to communicate and express their feelings in a easy way. Such user generated content contains clues of user’s behaviors and preferences, as well as other metadata information that is now available for scientific research. Twitter, in particular, has become a relevant source for social networking studies, mainly because: it provides a simple way for users to express their feelings, ideas, and opinions; makes the user generated content and associated metadata available to the community; and furthermore provides easy-to-use web interfaces and application programming interfaces (API) to access data. For many studies, the available information about a user is relevant. However, the gender attribute is not provided when creating a Twitter account. The main focus of this study is to infer the users’ gender from other available information. We propose a methodology for gender detection of Twitter users, using unstructured information found on Twitter profile, user generated content, and later using the user’s profile picture. In previous studies, one of the challenges presented was the labor-intensive task of manually labelling datasets. In this study, we propose a method for creating extended labelled datasets in a semi-automatic fashion. With the extended labelled datasets, we associate the users’ textual content with their gender and created gender models, based on the users’ generated content and profile information. We explore supervised and unsupervised classifiers and evaluate the results in both Portuguese and English Twitter user datasets. We obtained an accuracy of 93.2% with English users and an accuracy of 96.9% with Portuguese users. The proposed methodology of our research is language independent, but our focus was given to Portuguese and English users.Os serviços de redes sociais existentes proporcionam meios para as pessoas comunicarem e exprimirem os seus sentimentos de uma forma fácil. O conteúdo gerado por estes utilizadores contém indícios dos seus comportamentos e preferências, bem como outros metadados que estão agora disponíveis para investigação científica. O Twitter em particular, tornou-se uma fonte importante para estudos das redes socias, sobretudo porque fornece um modo simples para os utilizadores expressarem os seus sentimentos, ideias e opiniões; disponibiliza o conteúdo gerado pelos utilizadores e os metadados associados à comunidade; e fornece interfaces web e interfaces de programação de aplicações (API) para acesso aos dados de fácil utilização. Para muitos estudos, a informação disponível sobre um utilizador é relevante. No entanto, o atributo de género não é fornecido ao criar uma conta no Twitter. O foco principal deste estudo é inferir o género dos utilizadores através da informação disponível. Propomos uma metodologia para a detecção de género de utilizadores do Twitter, usando informação não estruturada encontrada no perfil do Twitter, no conteúdo gerado pelo utilizador, e mais tarde usando a imagem de perfil do utilizador. Em estudos anteriores, um dos desafios apresentados foi a tarefa de etiquetar manualmente dados, que revelou exigir bastante trabalho. Neste estudo, propomos um método para a criação de conjuntos de dados etiquetados de uma forma semi-automática, utilizando um conjunto de atributos com base na informação não estruturada de perfil. Utilizando os conjuntos de dados etiquetados, associamos conteúdo textual ao seu género e criamos modelos, com base no conteúdo gerado pelos utilizadores, e na informação de perfil. Exploramos classificadores supervisionados e não supervisionados e avaliamos os resultados em ambos os conjuntos de dados de utilizadores Portugueses e Ingleses do Twitter. Obtivemos uma precisão de 93,2% com utilizadores Ingleses e uma precisão de 96,9% com utilizadores Portugueses. A metodologia proposta é independente do idioma, mas o foco foi dado a utilizadores Portugueses e Ingleses

Da Kine Talk: From Pidgin to Standard English in Hawaii

Humanities Open Book Program, a joint initiative of the National Endowment for the Humanities and the Andrew W. Mellon FoundationHawaii is without parallel as a crossroads where languages of East and West have met and interacted. The varieties of English (including neo-pidgin) heard in the Islands today attest to this linguistic and cultural encounter. "Da kine talk" is the Island term for the most popular of the colorful dialectal forms--speech that captures the flavor of Hawaii's multiracial community and reflects the successes (and failures) of immigrants from both East and West in learning to communicate in English