Empirical Implication of Theoretical Models Summer Institute 2016, June 25 - July 09
BIG DATA have become a buzzword in the social sciences, which are raising challenges described as the “Three V”s of Volume, Variety and Velocity (Laney 2001) or the “Five V”s, adding Vinculation and Validity (Monroe 2012). Although for most, BIG means volume with massive observations, the DATA are often delivered in a variety of text formats and generated with such speed that requires immediate storage and analysis. Furthermore, the interdependence of such data by serial, spatial correlation, etc. ask for vinculating their interactions as in social network analysis, while questions about data validity are in the heart of the EITM approach.
This summer institute offers scholarly insights into theory, statistics and applications in 4 modules and a refresher course that are taught by excellent colleagues from 25th June until 9th July 2016 at the University of Mannheim. We provide an introduction into R (the optional +1 module), followed by the statistical module from June 27th until June 29th taught by James Lo (Princeton University), the theoretical module from June 30th until July 2nd taught by Songying Fang (Rice University), the module on text as data from July 4th until July 6th taught by Arthur Spirling (New York University), and the module in text categorisation and classification from July 7th until July 9th taught by Nicole Baerg (University of Mannheim). For more details, see below.
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