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Exploratory Analysis of Human Mood Swings

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ICCCE 2021

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 828))

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Humans differ from each other. Every human is unique, and everyone has a different mindset. Human behavior also varies from person to person. They are solemnly dependent on many factors. Human mood swings are basically influenced by internal factors such as hormones, mental health, and depression; external factors such as other people's behavior, health styles, the environment they work in, responses, and critics by the people who influence them the most. Behavioral analysis can be performed using python language for understanding the emotional intelligence of a person. The insights can be very useful in understanding the subject’s mood and it gives an outline of their emotions. Data manipulation and data preprocessing is done using pandas. Hence, it gives a crystal clear view of the insights that we wish to see. These data which contribute to emotional intelligence of a person is very much helpful for the person to stabilize their mood.

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  1. Llamocca P et al, Data source analysis in mood disorder research. University of Belgrade

    Google Scholar 

  2. Javelot H et al (2014) Telemonitoring with respect to mood disorders and information and communication technologies: overview and presentation of the PSYCHE project. BioMed Res Int 2014:12, Article ID 104658

    Google Scholar 

  3. Taylor MA, Fink M (2006) Melancholia: the diagnosis, pathophysiology and treatment of depressive illness. Cambridge University Press, Cambridge

    Google Scholar 

  4. DeMasi O, Recht B (2017) A step towards quantifying when an algorithm can and cannot predict an individual’s wellbeing. In: Proceedings of the 2017 ACM international joint conference on pervasive and ubiquitous computing and proceedings of the 2017 ACM international symposium on wearable computers, pp 763–771.

  5. Thieme A, Belgrave D, Doherty G (2020) Machine learning in mental health: a systematic review of the HCI literature to support the development of effective and implementable ML systems. ACM Trans Comput-Hum 27(5), Article 34.

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All the research works and analysis are done with the knowledge of the subject and their analysis is presented individually to each one of them.

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Mahadevan, R., Arputha Rathina, X. (2022). Exploratory Analysis of Human Mood Swings. In: Kumar, A., Mozar, S. (eds) ICCCE 2021. Lecture Notes in Electrical Engineering, vol 828. Springer, Singapore.

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-7984-1

  • Online ISBN: 978-981-16-7985-8

  • eBook Packages: EngineeringEngineering (R0)

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