Emotion and Memory: The Most Opposed Elements under the Blanket Term Psychology with Levine's Case of Sentiment

Research Article
Open access

Emotion and Memory: The Most Opposed Elements under the Blanket Term Psychology with Levine's Case of Sentiment

Serena Xu 1*
  • 1 Shanghai High School International Division, Shanghai, China    
  • *corresponding author dao.sprefe@natains.org
LNEP Vol.6
ISSN (Print): 2753-7056
ISSN (Online): 2753-7048
ISBN (Print): 978-1-915371-37-9
ISBN (Online): 978-1-915371-38-6

Abstract

Emotion and memory are two of the most opposed elements under the blanket term psychology. Memory is logical, if sometimes inaccurate, while emotion is irrational and rash. Despite these clear differences, many studies show that emotion and memory are closely related and that emotion enhances memory. However, these studies are often misunderstood due to the use of confusing terminology, resulting in the theories presented being difficult to apply in everyday life. This paper seeks to clear up the misunderstandings and propose a few possible applications of the presented theory.

Keywords:

Memory, Emotion, Arousal, Sentiment

Xu,S. (2023). Emotion and Memory: The Most Opposed Elements under the Blanket Term Psychology with Levine's Case of Sentiment. Lecture Notes in Education Psychology and Public Media,6,459-464.
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References

[1]. Cacioppo, J. T., & Gardner, W. L. (1999). Emotion. Annual review of psychology, 50.

[2]. Barrett, L. F., Mesquita, B., Ochsner, K. N., & Gross, J. J. (2007). The experience of emotion. Annual review of psychology, 58, 373.

[3]. Kövecses, Z. (2012). Emotion concepts. Springer Science & Business Media.

[4]. Li, D., & Qian, J. (2016, October). Text sentiment analysis based on long short-term memory. In 2016 First IEEE International Conference on Computer Communication and the Internet (ICCCI) (pp. 471-475). IEEE.

[5]. Mather, M., & Sutherland, M. R. (2011). Arousal-biased competition in perception and memory. Perspectives on psychological science, 6(2), 114-133.

[6]. Dolcos, F., Wang, L., & Mather, M. (2014). Current research and emerging directions in emotion-cognition interactions. Frontiers in Integrative Neuroscience, 8, 83.

[7]. Mai, S., Hu, H., Xu, J., & Xing, S. (2020). Multi-fusion residual memory network for multimodal human sentiment comprehension. IEEE Transactions on Affective Computing.

[8]. Mayshak, R., Sharman, S. J., & Zinkiewicz, L. (2016). The impact of negative online social network content on expressed sentiment, executive function, and working memory. Computers in Human Behavior, 65, 402-408.

[9]. Mendi, A. F. (2022). A Sentiment Analysis Method Based on a Blockchain-Supported Long Short-Term Memory Deep Network. Sensors, 22(12), 4419.

[10]. Sutherland, M. R., McQuiggan, D. A., Ryan, J. D., & Mather, M. (2017). Perceptual salience does not influence emotional arousal’s impairing effects on top-down attention. Emotion, 17(4), 700.

Cite this article

Xu,S. (2023). Emotion and Memory: The Most Opposed Elements under the Blanket Term Psychology with Levine's Case of Sentiment. Lecture Notes in Education Psychology and Public Media,6,459-464.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the International Conference on Interdisciplinary Humanities and Communication Studies (ICIHCS 2022), Part 5

ISBN：978-1-915371-37-9(Print) / 978-1-915371-38-6(Online)
Editor：Muhammad Idrees, Matilde Lafuente-Lechuga
Conference website: https://www.icihcs.org/
Conference date: 18 December 2022
Series: Lecture Notes in Education Psychology and Public Media
Volume number: Vol.6
ISSN：2753-7048(Print) / 2753-7056(Online)

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References

[1]. Cacioppo, J. T., & Gardner, W. L. (1999). Emotion. Annual review of psychology, 50.

[2]. Barrett, L. F., Mesquita, B., Ochsner, K. N., & Gross, J. J. (2007). The experience of emotion. Annual review of psychology, 58, 373.

[3]. Kövecses, Z. (2012). Emotion concepts. Springer Science & Business Media.

[4]. Li, D., & Qian, J. (2016, October). Text sentiment analysis based on long short-term memory. In 2016 First IEEE International Conference on Computer Communication and the Internet (ICCCI) (pp. 471-475). IEEE.

[5]. Mather, M., & Sutherland, M. R. (2011). Arousal-biased competition in perception and memory. Perspectives on psychological science, 6(2), 114-133.

[6]. Dolcos, F., Wang, L., & Mather, M. (2014). Current research and emerging directions in emotion-cognition interactions. Frontiers in Integrative Neuroscience, 8, 83.

[7]. Mai, S., Hu, H., Xu, J., & Xing, S. (2020). Multi-fusion residual memory network for multimodal human sentiment comprehension. IEEE Transactions on Affective Computing.

[8]. Mayshak, R., Sharman, S. J., & Zinkiewicz, L. (2016). The impact of negative online social network content on expressed sentiment, executive function, and working memory. Computers in Human Behavior, 65, 402-408.

[9]. Mendi, A. F. (2022). A Sentiment Analysis Method Based on a Blockchain-Supported Long Short-Term Memory Deep Network. Sensors, 22(12), 4419.

[10]. Sutherland, M. R., McQuiggan, D. A., Ryan, J. D., & Mather, M. (2017). Perceptual salience does not influence emotional arousal’s impairing effects on top-down attention. Emotion, 17(4), 700.

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