These are Supporting Materials for the paper "Mobile game evaluation method based on data mining of affective time-series" first presented at _International Conference on Computational Science_, 21-23 June, 2022 London, United Kingdom.
**If you use the data, please cite:**
- Ochab, J.K., Węgrzyn, P., Witaszczyk, P., Drążyk, D., Nalepa, G.J., 2025. Mobile Game Evaluation Method Based on Data Mining of Affective Time Series. Sensors 25, 2756. https://doi.org/10.3390/s25092756
**Contents:**
- Emotions:
- facial recognition data from MS Azure in .json format
-[player's ID]_[session number]_[game type]-[game]-[order of game presentation: dz=(MP, LP), zd=(LP, MP)]-[date].json
- Questionnaires: Polish and English language versions of
- recruitment questionnaire,
- Bartle's taxonomy of player types (Richard A. Bartle: Players Who Suit MUDs, 1996, https://mud.co.uk/richard/hcds.htm),
- after-session questionnaire,
- Supporting figures:
- examples of affective time series for "more profitable" games,
- plots of estimated marginal means of each game pair (stratified by emotion) for B and S index,
- Supporting tables:
- statistical tests for contrasts of estimated marginal means of each game pair (stratified by emotion) for B and S index.
- a summary table of p-values from all the above tests in long format (pvalues.csv)
See the paper for details on experimental procedures.
**Funding:**
This research was supported by the Polish National Centre for Research & Development (NCBR) within the Smart Growth Operational Programme grant No. POIR.01.02.00-00-0047/19 as a part of the European Regional Development Fund (ERDF).
The research for this publication was supported within the Priority Research Area DigiWorld under the Strategic Programme Excellence Initiative at Jagiellonian University. We would like to acknowledge Marek Wylon and Artur Piechnik from Stribog Games for conceptualising the study, organising participant recruitment and the experimental setup, and we would like to thank them for numerous discussions throughout the project.
