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Extraction: Advanced Methods00:56

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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...
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For solutions containing mixtures of different cations, the identity of each cation can be determined by qualitative analysis. This technique involves a series of selective precipitations with different chemical reagents, each reaction producing a characteristic precipitate for a specific group of cations. Metal ions within a group are further separated by varying the pH, heating the mixture to redissolve a precipitate, or adding other reagents to form complex ions.
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Updated: Jul 16, 2025

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A method for analyzing text using VOSviewer.

Umar Ali Bukar1, Md Shohel Sayeed1, Siti Fatimah Abdul Razak1

  • 1Centre for Intelligent Cloud Computing (CICC), Faculty of Information Science and Technology, Multimedia University, Melaka, Malaysia.

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|September 11, 2023
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Summary
This summary is machine-generated.

This study demonstrates VOSviewer, a bibliometric analysis tool, for effective text analysis and data visualization. It provides a scalable, user-friendly method for mapping text networks from diverse sources like social media transcripts.

Keywords:
Analysis and visualization of text dataDatasetText analysisVOSviewerVisualization

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Area of Science:

  • Data Science
  • Information Science
  • Computational Linguistics

Background:

  • Increasing data complexity necessitates advanced technical support for data handling and visualization.
  • Existing text analysis tools often lack scalability and advanced visualization capabilities.
  • VOSviewer, an open-source bibliometric analysis tool, shows potential for broader data visualization applications.

Purpose of the Study:

  • To evaluate VOSviewer's capability for text analysis.
  • To present an evidence-based implementation of VOSviewer for text data.
  • To demonstrate VOSviewer's utility in creating network maps from textual data.

Main Methods:

  • Utilized VOSviewer, an open-source software, for text analysis.
  • Processed textual data from YouTube interviews related to ChatGPT.
  • Developed a workflow for preparing text datasets as input for VOSviewer.

Main Results:

  • Successfully applied VOSviewer to analyze text-based data from social media transcripts.
  • Generated distinct visualization network maps from textual data, differing from traditional bibliometric outputs.
  • Confirmed VOSviewer's effectiveness in mapping text networks.

Conclusions:

  • VOSviewer is a powerful and versatile tool for data visualization and network mapping of textual data.
  • The software offers a scalable and user-friendly solution for researchers analyzing text networks.
  • VOSviewer has significant potential for text analysis across various fields beyond bibliometrics.