How kr-yan/analysis-of-covid-19-false-news-using-deep-learning works
This repository is a notebook-based analysis of Covid-19 myth discussions. Its documented workflow explores topic distributions, applies LDA and deep-learning text summarization, then compares findings through visualizations. The README describes the dataset and analysis capabilities, but no notebook source was available to verify implementation details or internal call structure; the graph therefore represents only documented relationships. The listed PDF is not connected because the README does not establish how it relates to the notebook.
Main entry points: data_350_covid_19_myths_lab.ipynb Topic Exploration
Components 11
Data Exploration
- Topic Exploration
data_350_covid_19_myths_lab.ipynb - Truth Heatmap
data_350_covid_19_myths_lab.ipynb - Waffle Chart
data_350_covid_19_myths_lab.ipynb
Topic Analysis
- LDA Topics
data_350_covid_19_myths_lab.ipynb - Text Summarization
data_350_covid_19_myths_lab.ipynb - Method Comparison
data_350_covid_19_myths_lab.ipynb
Results Views
- Analysis Visualizations
data_350_covid_19_myths_lab.ipynb - Topic Findings
data_350_covid_19_myths_lab.ipynb
Other components
- Analyst
- Covid Discussions
- Analysis Notebook
data_350_covid_19_myths_lab.ipynb
Connections 11
- Analyst → Analysis Notebook: runs
- Covid Discussions → Topic Exploration: analyzed by
- Covid Discussions → LDA Topics: modeled by
- Covid Discussions → Text Summarization: summarized by
- Topic Exploration → Truth Heatmap: compares labels
- Topic Exploration → Waffle Chart: categorizes topics
- LDA Topics → Method Comparison: compared with
- Text Summarization → Method Comparison: compared with
- LDA Topics → Analysis Visualizations: visualized by
- Text Summarization → Analysis Visualizations: visualized by
- Method Comparison → Topic Findings: informs