Sentiment Analysis In R

Stefan Feuerriegel and Nicolas Pröllochs have a new package in CRAN:

Our package “SentimentAnalysis” performs a sentiment analysis of textual contents in R. This implementation utilizes various existing dictionaries, such as QDAP or Loughran-McDonald. Furthermore, it can also create customized dictionaries. The latter uses LASSO regularization as a statistical approach to select relevant terms based on an exogenous response variable.

I’m not sure how it stacks up to external services, but it’s another option available to us.

Related Posts

K Nearest Cliques

Vincent Granville explains an algorithm built around finding cliques of data points: The cliques considered here are defined by circles (in two dimensions) or spheres (in three dimensions.) In the most basic version, we have one clique for each cluster, and the clique is defined as the smallest circle containing a pre-specified proportion p of the points […]

Read More

Building An Image Recognizer With R

David Smith has a post showing how to build an image recognizer with R and Microsoft’s Cognitive Services Library: The process of training an image recognition system requires LOTS of images — millions and millions of them. The process involves feeding those images into a deep neural network, and during that process the network generates […]

Read More


June 2017
« May Jul »