With the recent advances in deep learning, the ability of algorithms to analyse text has improved considerably. Creative use of advanced artificial intelligence techniques can be an effective tool for doing in-depth research.
Under the Code and Analysis menu, ATLAS.ti offers five ways of searching for relevant information in your data that can then be automatically coded.
- Find Concepts and Auto-code
- Text search
- Expert search with regular expressions
- Named Entity Recognition (NER)
- Sentiment Analysis
If you enter a term for a text search, you can select similar words from a list of synonyms. Synonyms are available in English, German, Spanish, Portuguese, French, Dutch, Russian and Simplified Chinese.
Language models for the above-listed languages are also available for Named Entity Recognition, Sentiment Analysis, and Concept Search.
As ATLAS.ti is a tool for qualitative data analysis, the process is not fully automated. Before coding the data, you can review all results, make modifications or decide not to code certain finds.
Artificial intelligence techniques have been developed for big data analysis. The data corpora usually handled by ATLAS.ti are considerably smaller. Thus, you cannot expect all results to be perfect. Reviewing the results will be a necessary component of the analysis process when using these tools. When working with the tools, you will see that the tools will add another level to your analysis. You find things that you simply do not see when coding the data manually, or would have not considered to code. We, at ATLAS.ti, consider manual and automatic coding to be complementary; each enhancing your analysis in a unique way.