Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/codewithmayank-py/cybertruck-sentiment-analysis
Sentiment Analysis of Tesla Cybertruck YouTube Comments
https://github.com/codewithmayank-py/cybertruck-sentiment-analysis
Last synced: about 2 months ago
JSON representation
Sentiment Analysis of Tesla Cybertruck YouTube Comments
- Host: GitHub
- URL: https://github.com/codewithmayank-py/cybertruck-sentiment-analysis
- Owner: CodeWithMayank-Py
- Created: 2024-03-30T13:27:56.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2024-03-30T14:24:04.000Z (9 months ago)
- Last Synced: 2024-03-31T14:37:31.377Z (9 months ago)
- Language: Jupyter Notebook
- Size: 492 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Sentiment Analysis of Tesla Cybertruck YouTube Comments
## 1. Introduction
This report analyzes public sentiment towards the Tesla Cybertruck as expressed in YouTube comments. A dataset of 32969 comments, spanning from 2023-12-01 to 2024-03-24, was used for this analysis.## 2. Key Findings
- Overall Sentiment Distribution
Sentiment towards the Cybertruck was found to be predominantly positive, with 47.5% of comments expressing positive sentiment, 25.6% negative, and 26.9% neutral.![Overall Sentiment Distribution](https://github.com/CodeWithMayank-Py/cybertruck-sentiment-analysis/blob/main/Images/sentiment_pie_chart.png)
- Sentiment Trends Over Time
Sentiment initially spiked positively around the Cybertruck's unveiling event but trended slightly downwards in the following months.![Sentiment Trends Over Time](https://github.com/CodeWithMayank-Py/cybertruck-sentiment-analysis/blob/main/Images/sentiment_trend_over_time.png)
- Sentiment and Engagement
Positive comments received significantly more likes than negative or neutral comments. The average number of likes for positive comments was [average likes], compared to [average likes] for negative comments.## 3. Notable Observations
- The word "look" featured prominently in both positive and negative word clouds, highlighting that the truck's design was a major driver of sentiment.
- A small group of active commenters were disproportionately negative, potentially skewing the overall sentiment slightly.## 4. Limitations
- The dataset may not fully capture sentiment from all segments of the population interested in the Cybertruck.
- VADER, while a useful tool, may not accurately interpret all sarcasm or nuances of car-enthusiast slang.## 5. Conclusion
The Tesla Cybertruck has generated strong public interest. While the design is polarizing, initial reactions were largely positive. Monitoring sentiment as the truck nears release could provide valuable insights into market reception.
## Data Sources
- Dataset : [Kaggle](https://www.kaggle.com/datasets/newbda/tesla-cybertruck-review-youtube-comments)
- YouTube Video : [Driving Tesla Cybertruck: Everything You Need to Know!](https://youtu.be/XxOh12Uhg08?si=Jaw4e4nNPpqAAmW3)