We present Twitmo, a package that provides a broad range of methods to
collect, pre-process, analyze and visualize geo-tagged Twitter data. Twitmo
enables the user to collect geo-tagged Tweets from Twitter and and provides a
comprehensive and user-friendly toolbox to generate topic distributions from
Latent Dirichlet Allocations (LDA), correlated topic models (CTM) and
structural topic models (STM). Functions are included for pre-processing of
text, model building and prediction. In addition, one of the innovations of the
package is the automatic pooling of Tweets into longer pseudo-documents using
hashtags and cosine similarities for better topic coherence. The package
additionally comes with functionality to visualize collected data sets and
fitted models in static as well as interactive ways and offers built-in support
for model visualizations via LDAvis providing great convenience for researchers
in this area. The Twitmo package is an innovative toolbox that can be used to
analyze public discourse of various topics, political parties or persons of
interest in space and time.

Twitmo 是一个创新的工具包，可用于收集、预处理、分析和可视化地理标记的 Twitter 数据，以进行主题建模和公共话语分析。