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

Cluster Sampling Method01:20

Cluster Sampling Method

12.1K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
12.1K
Extraction: Advanced Methods00:56

Extraction: Advanced Methods

504
Metal ions can be separated from one another by complexation with organic ligands–the chelating agent– to form uncharged chelates. Here, the chelating agent must contain hydrophobic groups and behave as a weak acid, losing a proton to bind with the metal. Since most organic ligands used in this process are insoluble or undergo oxidation in the aqueous phase, the chelating agent is initially added to the organic phase and extracted into the aqueous phase. The metal-ligand complex is...
504
Vesicular Tubular Clusters01:45

Vesicular Tubular Clusters

2.6K
After budding out from the ER membrane, some COPII vesicles lose their coat and fuse with one another to form larger vesicles and interconnected tubules called vesicular tubular clusters or VTCs. These clusters constitute a compartment at the ER-Golgi interface known as ERGIC (Endoplasmic Reticulum Golgi Intermediate Compartment). The ERGIC is a mobile membrane-bound cargo transport system that sorts proteins secreted from ER and delivers them to the Golgi.
With the help of motor proteins such...
2.6K
Empathy02:34

Empathy

9.6K
Some researchers suggest that altruism operates on empathy. Empathy is the capacity to understand another person’s perspective, to feel what he or she feels. An empathetic person makes an emotional connection with others and feels compelled to help (Batson, 1991). Empathy can be expressed in several ways, including cognitive, affective, and motor. 
9.6K
RNA-seq03:21

RNA-seq

10.2K
RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
10.2K
Classification of Signals01:30

Classification of Signals

620
In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
620

You might also read

Related Articles

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

Sort by
Same journal

An interpretable method for automated classification of spoken transcripts and written text.

Evolutionary intelligence·2023
Same journal

Intelligent contributions of the artificial orca algorithm for continuous problems and real-time emergency medical services.

Evolutionary intelligence·2023
Same journal

The application of blockchain algorithms to the management of education certificates.

Evolutionary intelligence·2023
Same journal

EEG signals classification using a new radial basis function neural network and jellyfish meta-heuristic algorithm.

Evolutionary intelligence·2023
Same journal

Epistemic neural network based evaluation of online teaching status during epidemic period.

Evolutionary intelligence·2022
Same journal

A review of recent advances in quantum-inspired metaheuristics.

Evolutionary intelligence·2022
See all related articles

Related Experiment Video

Updated: Aug 10, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

659

Text embedding techniques for efficient clustering of twitter data.

Jayasree Ravi1, Sushil Kulkarni1

  • 1Department of Computer Science, University of Mumbai, Kalina, Mumbai, Maharashtra 400098 India.

Evolutionary Intelligence
|February 13, 2023
PubMed
Summary
This summary is machine-generated.

This study explores Natural Language Processing (NLP) techniques for analyzing online content. Bidirectional Encoder Representations from Transformers (BERT) with K-means clustering proved most effective for tweet analysis.

Keywords:
BERTGloVeText embeddingTf-idfTwitter analyticsWord2Vec

More Related Videos

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
08:53

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

Published on: May 31, 2019

5.2K
ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data
05:12

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

Published on: January 16, 2019

11.5K

Related Experiment Videos

Last Updated: Aug 10, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

659
Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
08:53

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

Published on: May 31, 2019

5.2K
ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data
05:12

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

Published on: January 16, 2019

11.5K

Area of Science:

  • Natural Language Processing (NLP)
  • Machine Learning
  • Data Science

Background:

  • The internet contains vast amounts of unstructured text data from sources like blogs and social media.
  • Understanding this data is crucial for applications such as sentiment analysis and event detection.
  • Natural Language Processing (NLP) provides methods to analyze and derive insights from textual information.

Purpose of the Study:

  • To evaluate various word embedding techniques for analyzing tweets from popular news channels.
  • To cluster the resulting word vectors using the K-means algorithm.
  • To identify the most accurate word embedding method for this task.

Main Methods:

  • Application of multiple word embedding techniques on a dataset of news channel tweets.
  • Clustering of the generated word vectors using the K-means algorithm.
  • Comparative analysis of the accuracy of different word embedding methods.

Main Results:

  • Bidirectional Encoder Representations from Transformers (BERT) demonstrated superior performance.
  • BERT, when combined with K-means clustering, achieved the highest accuracy rate.
  • The study quantifies text data using word embeddings for better analysis.

Conclusions:

  • Word embedding techniques, particularly BERT, are effective for analyzing and clustering tweet data.
  • The combination of BERT and K-means clustering offers a highly accurate approach for NLP tasks.
  • This method can be applied to understand insights from large volumes of online text.