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December 6, 2024

Responsible Gaming

Responsible Gaming
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Data-Driven Insights:

Massive amounts of gameplay data, like in-game actions and player responses, can provide valuable psychological insights into user behavior and experience.

Understanding Player Patterns:

Identifying "game behaviors" and "play styles" through data sequences enables a deeper understanding of player interactions and can inform responsible gameplay initiatives.

Supporting Responsible Gameplay:

Insights from player behavior patterns can help promote responsible gameplay by identifying at-risk behaviors and fostering a safer gaming environment.

Innovative Analysis Approach:

Using a two-stage neural network, CognitionNet automatically uncovers player psychology and game tactics, providing consistent insights and outperforming standard methods.

References:

  1. Jagirdar, Hussain, Rukma Talwadker, Aditya Pareek,PulkitAgrawal, and Tridib Mukherjee. "Explainable and Interpretable Forecasts on Non-Smooth Multivariate Time Series for Responsible Gameplay." In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pp. 5126-5137. 2024. Link: https://dl.acm.org/doi/abs/10.1145/3637528.3671657
  2. Agrawal, Pulkit, Aditya Pareek, Rukma Talwadker, and Tridib Mukherjee. "ARGO-An AI Based Responsible Gamification Framework for Online Skill Gaming Platform." In Proceedings of the 7th Joint International Conference on Data Science & Management of Data (11th ACM IKDD CODS and 29th COMAD), pp. 412-421. 2024. Link: https://dl.acm.org/doi/abs/10.1145/3632410.3632455
  3. Talwadker, Rukma, Surajit Chakrabarty, Aditya Pareek, Tridib Mukherjee, and Deepak Saini. "Cognitionnet: A collaborative neural network for play style discovery in online skill gaming platform." In Proceedings of the28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pp. 3961-3969. 2022. Link: https://dl.acm.org/doi/abs/10.1145/3534678.3539179
  4. Chakrabarty, Surajit, Rukma Talwadker, and Tridib Mukherjee. "ScarceGAN: Discriminative Classification Framework for Rare Class Identification for Longitudinal Data with Weak Prior." In Proceedings of the 30th ACM International Conference on Information & Knowledge Management, pp. 140-150. 2021. https://dl.acm.org/doi/abs/10.1145/3459637.3482474
  5. Seth, Deepanshi, Sharanya Eswaran, Tridib Mukherjee, and Mridul Sachdeva. "A Deep Learning Framework for Ensuring Responsible Play in Skill-based Cash Gaming." In 202019th IEEE International Conference on Machine Learning and Applications (ICMLA), pp. 454-459. IEEE, 2020. https://ieeexplore.ieee.org/abstract/document/9356268/