Text analysis has become increasingly important for psychological research, and measuring psychological and demographic properties using computational text analysis is slowly becoming a field norm.
Though several limited-method tools for text analysis are already available (e.g. LIWC), and some have become part of standard statistical packages (e.g., SPSS Text Analytics), a unified, open-source architecture for gathering, managing and analyzing text does not exist.
The Computational Social Science Lab (CSSL) at the University of Southern California introduces TACIT: An Open-Source Text Analysis, Crawling and Interpretation Tool.
TACIT's plugin architecture has three main components:
Crawling plugins, for automated text collection from online sources (e.g., US Senate and Supreme Court speech transcriptions, Twitter, Reddit)
Analysis plugins, including LIWC-type word count, topic modeling, sentiment analysis, clustering and classification.
Corpus management, for applying standard text preprocessing to prepare and store corpora.
TACIT's open-source plugin platform allows the architecture to easily adapt to today's rapid developments in text analysis.