Erik Borra
About
Erik Borra is a data scientist. He is PhD candidate and lecturer at the University of Amsterdam's M.A. program in New Media. Erik is also the lead programmer for the Digital Methods Initiative and is currently involved in the European research project 'Electronic Maps to Assist Public Science' (EMAPS).
Erik's employment as a programmer is the continuation of his work for Govcom.org, a foundation dedicated to creating and hosting political Web tools. This work consists of mapping issue networks on the Web by using the Issue Crawler software, as well as devising new tools such as the Issue Feed (beta), Issue Scraper - which makes comparative analyses of webspheres (e.g. news spheres and blogospheres), a surfer pathway browser, and tag ecology visualizers.
Together with artists and designers Erik worked on projects such as the WEX machine - a physical website recursively connecting the on- and the offline, iTea - an interactive RFID installation designed as a coffee table, tapemixer.com - a playlist recommendation mash-up between YouTube and Last.fm, and the IP-browser - an alternative browsing experience that foregrounds the Web’s machine habitat and returns the user back to the basics of orderly Web browsing.
Erik earned his BSc and MSc in Artificial Intelligence at the University of Amsterdam.
Curriculum Vitae Erik Borra
Digital Methods Initiative
Tools for Research with the Web
Rethinking the Web as a Source of Data
The aim of Erik's PhD is to make a contribution to the data-driven computational turn in the humanities and social sciences by examining the status of novel data types available online. This goal will be pursued through three sub-projects. First, search engine query histories will be investigated, analyzing the work performed to date on existing data releases and studying data made available through a working collaboration with Yahoo!. The second line of investigation will study how Wikipedia can be used to diagnose cultural matters of concern. Following actor-network theory, a novel approach to Wikipedia data treatment will be proposed to trace the evolution of controversies. The third exploration of data online, extracted from social network sites, will investigate whether rich data sets allow for profiling, not only on traditional demographic categories like gender and age, but as clusters of social and cultural categories on the basis of tastes and preferences. The proposed research thus aims to take stock of the cultural data on the Web, and evaluate their robustness for cultural and social research.