  In the widely used message platform Twitter, about 2% of the tweets contains
the geographical location through exact GPS coordinates (latitude and
longitude). Knowing the location of a tweet is useful for many data analytics
questions. This research is looking at the determination of a location for
tweets that do not contain GPS coordinates. An accuracy of 82% was achieved
using a Naive Bayes model trained on features such as the users' timezone, the
user's language, and the parsed user location. The classifier performs well on
active Twitter countries such as the Netherlands and United Kingdom. An
analysis of errors made by the classifier shows that mistakes were made due to
limited information and shared properties between countries such as shared
timezone. A feature analysis was performed in order to see the effect of
different features. The features timezone and parsed user location were the
most informative features.
