Text mining

Db preparation

Final Db exportation

Scopus

IEEE Explorer

Google Scholar

Google Scholar automated from citation to full data

Data Preparation for Topic Models. Preprocessing, n-grams, exclusion of reviews with a small number of terms can be adjusted as desired

Obtain topic solution. Users can test more than 1 topic solution and choose based on interpretability.

Find optimal k. Other methods can be implemented in KNIME (https://hub.knime.com/angusveitch/spaces/Public/latest/TopicKR~HRMp6v9Ip_ODMIob). Other Topic model algorithms that can be used in R or python are structural topic models (STM) and correlated topic models (CTM).

Python LDA visualization

Cloude word visualization

Data preparation

Theta preparation

Doc lenght preparation

Phi preparation

Vocabulary preparation

Visualizion

Checker box

If the python enviromental's is working use this section

Bibliography

Import the data if not excel