TSJ Dashboard enables interactive and real-time analysis of the users’ questions and counsellors’ answers in the online counselling service This is me, which is maintained by the National Institute of public health RS. Also, the data from Google Analytics can be analyzed in TSJ Dashboard. The tool is designed as a web application. This means that it can be used on any computer with a web browser and internet access. TSJ Dashboard offers different kinds of data analysis and visualizations. Partial analysis (aggregated data, tables) can be exported in .csv format (can be easily opened with MS Excel). Also, all microdata can be exported for further statistical analysis.

The 100 pages long automatic generated report outlines the basic descriptive statistics related to the operation of the This is me online counselling service in a given period. The current structure of the document was designed in cooperation with the This is me editorial office. The hottest topics and statistics in which they want to have a better insight were selected. However, there are still possibilities of adding any supplements at any time. The computer program used to generate the automatic generated report is written in Sweave, which combines the programming language for statistical analysis, namely R, and Latex, the document mark-up language. The input is the entire forum database, and the output is the document in PDF format.

The project aimed to identify cancer-related messages in the online healthcare community MedOverNet among approx. 3 million messages posted between 2015 and 2019. Different machine learning algorithms (naive Bayes classification, support vector machine, decision trees and random forests) were used on lematized text with removed stop-words. The most efficient was the random forest model with 92% sensitivity and 89% specificity. Around 0.6% messages were about cancer – 2.9% within health consulting discussions, 1.9% within social support discussions and 0.5% within socializing discussions. The identified messages were considered in the sampling procedure to analyze the quality of cancer-related information in the online healthcare community MedOverNet.

All questions posted between 2001 and 2021 in the Web counselling service were analyzed. The characteristics of the questions (e.g., age, gender and content of questions) have been determined by hand since 2012. These were used to determine the content of the remaining questions posted before 2012 (supervised machine learning algorithms were used). Overall, the physical, mental, and sexual health questions are equally represented. However, the number of questions about physical health decreased in the later years while the number of questions about mental health remained unchanged. According to gender: questions about drugs, addiction and sexuality, are more common among boys, while questions about mental health, relationships and body are more commonly asked by girls.