Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

25
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
25
Stereotype Content Model02:16

Stereotype Content Model

13.9K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
13.9K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Examination of hydrological variations and their effect on water shortage trends and water-energy production using convolutional neural network and ISSA.

Scientific reports·2025
Same author

Hepatoma-derived growth factor binds DNA through the N-terminal PWWP domain.

BMC molecular biology·2007
Same author

[Evaluation of bubble oxygen inhalators' performances and an investigation on their solutions for improvement].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation·2007
Same author

Relaxation mechanisms of neferine on the rabbit corpus cavernosum tissue in vitro.

Asian journal of andrology·2007
Same author

[Effect of niacin on HDL-induced cholesterol efflux and LXRalpha expression in adipocytes of hypercholesterolemic rabbits].

Zhonghua xin xue guan bing za zhi·2007
Same author

Total synthesis of (+/-)-communesin F.

Journal of the American Chemical Society·2007
Same journal

Turbulent flow in a vortex separator with a directed pipe inlet.

Scientific reports·2026
Same journal

Systematic characteristic evaluation of clay-based cementitious material derived from calcium carbide residue and waste tile powder.

Scientific reports·2026
Same journal

Retraction Note: Improvement of a rapid diagnostic application of monoclonal antibodies against avian influenza H7 subtype virus using Europium nanoparticles.

Scientific reports·2026
Same journal

Applying large language models to spam detection in the Kazakh low-resource language setting.

Scientific reports·2026
Same journal

An open-source 3D printing system enabling in-situ freeze-thaw processing of hydrogels.

Scientific reports·2026
Same journal

An enhanced EfficientNet framework for automated waste classification using cosine annealing and label smoothing.

Scientific reports·2026
See all related articles

Related Experiment Video

Updated: May 9, 2025

Protocol for Data Collection and Analysis Applied to Automated Facial Expression Analysis Technology and Temporal Analysis for Sensory Evaluation
07:12

Protocol for Data Collection and Analysis Applied to Automated Facial Expression Analysis Technology and Temporal Analysis for Sensory Evaluation

Published on: August 26, 2016

9.3K

Using BERT and ZFNet/ELM optimized by improved Orca optimization algorithm for sentiment analysis.

Jun Yang1, Jafar Safarzadeh2,3

  • 1Xijing University, Xi'an, 710123, Shaanxi, China.

Scientific Reports
|April 30, 2025
PubMed
Summary
This summary is machine-generated.

Sentiment analysis, using Bidirectional Encoder Representations from Transformers (BERT) and ZFNet/ELM optimized by Improved Orca Optimization Algorithm (IOPA), accurately classifies movie review polarity.

Keywords:
BERTExtreme learning machine (ELM)Improved orca optimization algorithm (IOPA)Sentiment analysisZFNet

More Related Videos

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.4K
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

2.4K

Related Experiment Videos

Last Updated: May 9, 2025

Protocol for Data Collection and Analysis Applied to Automated Facial Expression Analysis Technology and Temporal Analysis for Sensory Evaluation
07:12

Protocol for Data Collection and Analysis Applied to Automated Facial Expression Analysis Technology and Temporal Analysis for Sensory Evaluation

Published on: August 26, 2016

9.3K
Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.4K
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

2.4K

Area of Science:

  • Computational Linguistics
  • Artificial Intelligence
  • Machine Learning

Background:

  • Sentiment analysis, or opinion mining, is crucial for understanding public opinion in textual data.
  • Natural Language Processing (NLP) techniques are vital for extracting meaningful patterns from large text volumes.
  • Analyzing user-generated reviews is key to gauging audience reactions to media, like movies.

Purpose of the Study:

  • To investigate the effectiveness of sentiment analysis in understanding audience reactions to movies.
  • To propose and evaluate a novel sentiment analysis model for classifying review polarity.
  • To leverage advanced NLP techniques for improved accuracy in opinion mining.

Main Methods:

  • Utilized Bidirectional Encoder Representations from Transformers (BERT) for contextual word understanding.
  • Implemented data preprocessing to enhance the quality and efficacy of the textual data.
  • Employed a ZFNet/ELM model optimized with the Improved Orca Optimization Algorithm (IOPA) for classification.

Main Results:

  • Achieved high performance metrics: 96.24% precision, 97.41% recall, and 96.82% F1-score.
  • The proposed model demonstrated superior performance compared to existing sentiment analysis models.
  • Successfully recognized and classified the polarity of movie reviews with high accuracy.

Conclusions:

  • The developed sentiment analysis model, integrating BERT and IOPA-optimized ZFNet/ELM, is highly effective for movie review analysis.
  • The model's strong performance validates its capability in accurately determining the sentiment expressed in user-generated content.
  • This approach offers a robust solution for opinion mining and understanding audience reception in the film industry.