State of the Art of Deep Learning Applications in Sentiment Analysis: Psychological Behavior Prediction

Maryame, Naji; Daoudi, Najima; Rahimi, Hasnae; Ajhoun, Rachida

doi:10.1007/978-981-15-0947-6_42

Cited by 6 publications

(3 citation statements)

References 14 publications

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“…There are two classes in ML methods to be specific directed ML and undirected ML [12]. In regulated ML information will be given by the engineer while in solo ML, a bunching method was found based on the separation among information [13]. Directed ML calculations have been utilized which permits computerized accumulated Figure 1.…”

Section: Introductionmentioning

confidence: 99%

A Novel Elephant Herd Random Forest Machine Learning Approach To Estimate the Sentiment Value of Online Customer Review

Sanshi¹,

Krishna²,

Vatambeti³

2023

IJCDS

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Nowadays, big data has attracted the attention of whole advanced world with its applications and features. Machine learning (ML) models are used to perform the online administrations in good manner .The ML approaches turned into a moving field in analyzing enormous data; consequently the accomplishment of online administrations or business depends on the client audits. Nearly the online customer review contains positive, negative and neutral sentiment value. In marketing system and product development fields the sentiment analysis value prediction has important role. In this paper, a novel Elephant Herd Random Forest Machine Learning (EHRFML) methodology is proposed to compute the sentiment value of online customer review. Moreover, customer review datasets are preprocessed and unwanted information is removed using machine learning approach. Sequentially, the outcomes of proposed system are compared with existing technique using parameters like accuracy, precision, recall, aspect term specification and opinion condition obtained good results by getting high accuracy based on opinion specification.

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Section: Introductionmentioning

confidence: 99%

A Novel Elephant Herd Random Forest Machine Learning Approach To Estimate the Sentiment Value of Online Customer Review

Sanshi¹,

Krishna²,

Vatambeti³

2023

IJCDS

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“…To target our study, and to attend a logical sequence of our previous works (Maryame et al, 2018(Maryame et al, , 2019(Maryame et al, , 2020(Maryame et al, , 2021, we are taking profit of the current pandemic COVID-19 to measure its effect on people's mental health based on machine learning and neural network approach.…”

Section: Introductionmentioning

confidence: 99%

Psychological Behavior Prediction through Sentiment Analysis Technics: Transformers and ML Approach

Maryame¹,

Ajhoun²

2022

Journal of Computer Science

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In the era of the COVID-19 epidemic, governments have imposed nationwide lockdowns, which make a huge change to people's daily routines. This last impacts indirectly the well-being of people's mental health. And due to social media, many conversations about these phenomena occur online, especially those related to people's emotions. Which brought challenges and opportunities for sentiment analysis researchers. In this article, we are interested in extracting correlations between this epidemic and its psychological effects by analyzing users' tweets through common Deep Learning and Machine Learning approaches used for text classification. This last goal is a crucial step to fulfill the main objective of our research: Developing an intelligent system that provides recommendations such as positive support and early alert to help people in case of specific needs particularly challenging mental states.

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“…In 2017, the State Council and the Central Committee of the Communist Party of China jointly issued the Opinions on Strengthening and Improving the Ideological and Political Work in Colleges and Universities under the New Situation, which mentioned that we must "adhere to whole-staff education, whole-process education and all-round education" or "three comprehensive education" for short. The "three comprehensive education" requires higher vocational colleges to integrate moral education resources and enhance the effectiveness of moral education among higher vocational college students [1][2][3][4][5]. The innovative "three comprehensive education" model can help mobilize the initiatives of higher vocational college students to conduct self-management, self-education and self-service [6][7][8], and students' book borrowing behaviours due to their interdisciplinary learning interests are just the manifestation of the "reading, culture and service-based education" mechanism in the "three comprehensive education" [9][10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Psychological Motivations of Students for Book Borrowing in Libraries of Higher Vocational Colleges from the Perspective of “Three Comprehensive Education”

Yan

2021

Int. J. Emerg. Technol. Learn.

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The innovative “three comprehensive education” model can mobilize the initiatives of students in higher vocational colleges, whose book borrowing behaviors are affected by “three comprehensive education”. This paper mainly studies the psychological motivations of students for book borrowing in libraries of higher vocational colleges from the perspective of “three comprehensive education”. Firstly, the psychological motivations for book borrowing were analyzed in details under the mechanism of “three comprehensive education”. Then, a dataset was created from the mass data on book borrowing and students. The relevant features were compressed as model inputs, aiming to improve model performance and reduce storage cost. Finally, a perception model was constructed to analyze the psychological motivations of students for book borrowing, and used to solve the five-class classification problem based on the directed acyclic graph. Experimental results prove the scientific of the psychological pattern analysis and the effectiveness of the proposed model. The research results provide a theoretical and practical reference for the effect analysis of “three comprehensive education”.

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State of the Art of Deep Learning Applications in Sentiment Analysis: Psychological Behavior Prediction

Cited by 6 publications

References 14 publications

A Novel Elephant Herd Random Forest Machine Learning Approach To Estimate the Sentiment Value of Online Customer Review

A Novel Elephant Herd Random Forest Machine Learning Approach To Estimate the Sentiment Value of Online Customer Review

Psychological Behavior Prediction through Sentiment Analysis Technics: Transformers and ML Approach

Psychological Motivations of Students for Book Borrowing in Libraries of Higher Vocational Colleges from the Perspective of “Three Comprehensive Education”

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