Kasthurirathna, DKalansooriya, SKaluarachchi, AWeerawickrama, CNanayakkara, DAdeepa, D2023-01-242023-01-242022-11-03S. Kalansooriya, A. Kaluarachchi, C. Weerawickrama, D. Nanayakkara, D. Kasthurirathna and D. Adeepa, "“xīnlĭ” The Social Media App to Replenish Mental Health with the Aid of an Egocentric Network," 2022 IEEE 10th Region 10 Humanitarian Technology Conference (R10-HTC), Hyderabad, India, 2022, pp. 348-354, doi: 10.1109/R10-HTC54060.2022.9929642.25727621https://rda.sliit.lk/handle/123456789/3170The impact of social groups on one's emotional health is a crucial issue that must be addressed correctly. Emotions and social groups play significant roles in human mental and physical activities. It is difficult to detect and maintain track of changing emotional states. The main goal of this study is to build a social media app called Xinli, that proposes an aggregated method to predict emotions using a multimodal approach and to predict personalized activities based on the user's mental state, and to further track the improvement of emotional state with the impact of recommended activities and social support groups. The results suggest that the aggregated modalities method is more accurate in recognizing emotions, and activity prediction using reinforcement learning is a clean way to personalize activities based on the emotional state from user to user, which is the novelty of the proposed study.enemotionmultimodalpredictreinforcement learningsocial supportArticle10.1109/R10-HTC54060.2022.9929642