Keyword Extraction for Trend Analysis

Project Overview:

Objective

The “Keyword Extraction for Trend Analysis” project aims to create a dataset for training machine learning models to automatically extract and classify relevant keywords from textual data, enabling trend analysis and insights generation across various domains.

Scope

This project involves collecting text data from different sources, including news articles, social media posts, blogs, and research papers, and annotating them with relevant keywords that represent the topics and trends discussed in the text.

Keyword Extraction for Trend Analysis
Keyword Extraction for Trend Analysis
Keyword Extraction for Trend Analysis
Keyword Extraction for Trend Analysis

Sources

  • News Websites: Gather news articles from reputable news websites covering a wide range of topics.
  • Social Media: Access publicly available social media posts from platforms like Twitter, Facebook, and Instagram.
  • Blogs and Forums: Extract text data from blogs, forums, and online communities discussing various subjects.
  • Research Databases: Partner with research institutions to obtain research papers and academic articles.
Keyword Extraction for Trend Analysis
Keyword Extraction for Trend Analysis

Data Collection Metrics

  • Total Textual Data: 50,000 documents
  • News Websites: 20,000
  • Social Media: 15,000
  • Blogs and Forums: 10,000
  • Research Databases: 5,000

Annotation Process

Stages

  1. Keyword Extraction: Annotate each text document with relevant keywords that best represent the key topics and trends discussed within the text.
  2. Metadata Logging: Log metadata, including the source of the text, publication date, and any contextual information.

Annotation Metrics

  • Text Documents with Keywords: 50,000
  • Metadata Logging: 50,000
Keyword Extraction for Trend Analysis
Keyword Extraction for Trend Analysis
Keyword Extraction for Trend Analysis
Keyword Extraction for Trend Analysis

Quality Assurance

Stages

Annotation Verification: Implement a validation process involving domain experts to review and verify the accuracy of keyword extractions.
Data Quality Control: Ensure the removal of duplicate documents and irrelevant text data from the dataset.
Data Security: Protect sensitive information and maintain the confidentiality of copyrighted text materials.

QA Metrics

  • Annotation Validation Cases: 5,000 (10% of total)
  • Data Cleansing: Remove duplicate documents and irrelevant text data

Conclusion

The “Keyword Extraction for Trend Analysis” dataset is a powerful resource for trend analysis, market research, and insights generation across diverse domains. With a vast collection of text data, accurate keyword annotations, and robust privacy and security measures, this dataset empowers analysts, researchers, and businesses to stay ahead of emerging trends and gain deeper insights into various subjects. It serves as a foundation for developing advanced trend analysis and text mining solutions that can inform decision-making and strategy development in an ever-evolving landscape of information and trends.

quality dataset

Quality Data Creation

Guaranteed TAT​

Guaranteed TAT

ISO 9001:2015, ISO/IEC 27001:2013 Certified​

ISO 9001:2015, ISO/IEC 27001:2013 Certified

HIPAA Compliance​

HIPAA Compliance

GDPR Compliance​

GDPR Compliance

Compliance and Security​

Compliance and Security

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