Automated Measures of Sentiment via Transformer- and Lexicon-Based
Sentiment Analysis (TLSA)
Abstract
The last decade witnessed the proliferation of automated content
analysis in communication research. However, existing computational
tools have been taken up unevenly, with powerful deep learning
algorithms such as transformers rarely applied as compared to
lexicon-based dictionaries. To enable social scientists to adopt modern
computational methods for valid and reliable sentiment analysis of
English text, we propose an open and free web service named transformer-
and lexicon-based sentiment analysis (TLSA). TLSA integrates diverse
tools and offers validation metrics, empowering users with limited
computational knowledge and resources to reap the benefit of
state-of-the-art computational methods. Two cases demonstrate the
functionality and usability of TLSA. The performance of different tools
varied to a large extent based on the dataset, supporting the importance
of validating various sentiment tools in a specific context.