“Here, There and Everywhere”: Classifying Location Information in Social Media Data - Possibilities and Limitations

Abstract

This paper provides an overview of possibilities to localize acts of communication and their agents based on digital traces and scrutinizes their advantages and disadvantages. It shows, (i) what types of geographic information exist in social media data and to what extent they are available to researchers, (ii) which approaches exist to classify locations and (iii) what the advantages and disadvantages of the various approaches are. Introducing an approach to automatically classify location information based on the location information in users’ profiles and a multi-step cross-validation with time zone information, we show that the less resource-intensive approach yields high precision comparable to the “gold standard” of human coding while recall is comparatively low. The discussion of advantages and limitations of all approaches shows that–depending on the research question–the specific research context and its presumed effect, the aspired granularity of location classification and resource considerations can guide a researchers’ decision.