Anak Jakarta; A Sketch Of Indonesian Youth Identity

Anak Jakarta refers to the youth of Jakarta, the trend-setters of the Indonesian youth. This paper gives a sketch of the youth in Jakarta as characterized by their appearance, language and lifestyle. Information is derived from discussions and personal contact with different groups of youth and parents (adults with children) in Jakarta; literature review, observations, as well as from flashbacks given by the adults, providing a portrait of anak Jakarta since late 1980's. The youth in Jakarta is Western (American) oriented, copying from the mass- and social media, often times conflicting with local norms and parental advices. Anak Jakarta profile includes: youth created slang language, school gang fights (tawuran) and brand minded consumerism. Jakarta youth has become the role model for most youth all over Indonesia, especially Jakarta migrant youth. Family upbringing, social contact, peer group and the media play a crucial role in forming, transforming and disseminating the characteristics anak Jakarta identity

Re-imagining French lexicography: The dictionnaire vivant de la langue française

The Dictionnaire vivant de la langue française (DVLF), developed by The ARTFL Project at the University of Chicago, represents an experimental, interactive, and community-based approach to French lexicography. The DVLF enables broad public access to a wide variety of linguistic tools and resources, with the goal of changing user interaction with dictionaries and providing better descriptions of emergent word use. In this article we describe the history of the DVLF and provide a survey of similar community-oriented electronic dictionaries. We then proceed to a presentation of the dictionary’s many features, including the variety of its definitions and mechanisms for user interaction. The article concludes with a discussion of ARTFL’s plans for the future developement of the DVLF

Using Contexts and Constraints for Improved Geotagging of Human Trafficking Webpages

Extracting geographical tags from webpages is a well-motivated application in many domains. In illicit domains with unusual language models, like human trafficking, extracting geotags with both high precision and recall is a challenging problem. In this paper, we describe a geotag extraction framework in which context, constraints and the openly available Geonames knowledge base work in tandem in an Integer Linear Programming (ILP) model to achieve good performance. In preliminary empirical investigations, the framework improves precision by 28.57% and F-measure by 36.9% on a difficult human trafficking geotagging task compared to a machine learning-based baseline. The method is already being integrated into an existing knowledge base construction system widely used by US law enforcement agencies to combat human trafficking.Comment: 6 pages, GeoRich 2017 workshop at ACM SIGMOD conferenc

Making "fetch" happen: The influence of social and linguistic context on nonstandard word growth and decline

In an online community, new words come and go: today's "haha" may be replaced by tomorrow's "lol." Changes in online writing are usually studied as a social process, with innovations diffusing through a network of individuals in a speech community. But unlike other types of innovation, language change is shaped and constrained by the system in which it takes part. To investigate the links between social and structural factors in language change, we undertake a large-scale analysis of nonstandard word growth in the online community Reddit. We find that dissemination across many linguistic contexts is a sign of growth: words that appear in more linguistic contexts grow faster and survive longer. We also find that social dissemination likely plays a less important role in explaining word growth and decline than previously hypothesized

Buzz monitoring in word space

This paper discusses the task of tracking mentions of some topically interesting textual entity from a continuously and dynamically changing flow of text, such as a news feed, the output from an Internet crawler or a similar text source - a task sometimes referred to as buzz monitoring. Standard approaches from the field of information access for identifying salient textual entities are reviewed, and it is argued that the dynamics of buzz monitoring calls for more accomplished analysis mechanisms than the typical text analysis tools provide today. The notion of word space is introduced, and it is argued that word spaces can be used to select the most salient markers for topicality, find associations those observations engender, and that they constitute an attractive foundation for building a representation well suited for the tracking and monitoring of mentions of the entity under consideration