stansent wraps Stanford's coreNLP sentiment tagger in a way that makes the process easier to get set up. The output is designed to look and behave like the objects from the sentimentr package. Plotting and the sentimentr::highlight functionality will work similar to the sentiment/sentiment_by objects from sentimentr. This requires less learning to work between the two packages. In addition to sentimentr and stansent, Matthew Jocker's has created the syuzhet package that utilizes dictionary lookups for the Bing, NRC, and Afinn methods. Similarly, Subhasree Bose has contributed RSentiment which utilizes dictionary lookup that atempts to address negation and sarcasm. Click here for a comparison between stansent, sentimentr, syuzhet, and RSentiment. Note the accuracy and run times of the packages.