Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/3170
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dc.contributor.authorKasthurirathna, D-
dc.contributor.authorKalansooriya, S-
dc.contributor.authorKaluarachchi, A-
dc.contributor.authorWeerawickrama, C-
dc.contributor.authorNanayakkara, D-
dc.contributor.authorAdeepa, D-
dc.date.accessioned2023-01-24T09:38:09Z-
dc.date.available2023-01-24T09:38:09Z-
dc.date.issued2022-11-03-
dc.identifier.citationS. 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.en_US
dc.identifier.issn25727621-
dc.identifier.urihttps://rda.sliit.lk/handle/123456789/3170-
dc.description.abstractThe 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.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.relation.ispartofseriesIEEE Region 10 Humanitarian Technology Conference, R10-HTC;Volume 2022-, Pages 348 - 354-
dc.subjectemotionen_US
dc.subjectmultimodalen_US
dc.subjectpredicten_US
dc.subjectreinforcement learningen_US
dc.subjectsocial supporten_US
dc.title'xīnl' The Social Media App to Replenish Mental Health with the Aid of an Egocentric Networken_US
dc.typeArticleen_US
dc.identifier.doi10.1109/R10-HTC54060.2022.9929642en_US
Appears in Collections:Department of Computer Science and Software Engineering
Research Papers - Dept of Computer Science and Software Engineering
Research Papers - IEEE
Research Papers - SLIIT Staff Publications

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