This project is a Python-based web scraper designed to extract detailed textual data from Kickstarter campaign pages. The core problem it solves is automating the extraction of public campaign descriptions and creator profile information, which is essential for academic research in applied microeconomics.
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This scraper extracts and downloads text from Kickstarter campaign pages. It's intended for academic use, specifically for research related to applied microeconomics. The script is optimized for large-scale scraping, processing approximately 610,000 Kickstarter campaigns.
- Helps researchers efficiently collect large-scale textual data.
- Automates the extraction of detailed campaign descriptions and creator profiles.
- Provides the foundational data needed for analysis in microeconomics and social sciences.
| Feature | Description |
|---|---|
| Campaign Description Extraction | Scrapes the full campaign description text from each Kickstarter page. |
| Creator Profile Text Extraction | Collects the text from the campaign creator's profile section. |
| Large-Scale Scraping Support | Designed to handle thousands of Kickstarter pages in a batch process. |
| Field Name | Field Description |
|---|---|
| campaign_description | The main text describing the Kickstarter campaign. |
| creator_profile | Text from the creator's profile section of the campaign. |
[
{
"campaign_url": "https://www.kickstarter.com/projects/creator1/campaign-title",
"campaign_description": "This is the full description of the campaign.",
"creator_profile": "The creator's bio and profile information."
}
]
kickstarter-python-campaign-text-scraper/
├── src/
│ ├── scraper.py
│ ├── extractors/
│ │ ├── campaign_extractor.py
│ │ └── creator_profile_extractor.py
│ ├── outputs/
│ │ └── data_exporter.py
│ └── config/
│ └── settings.example.json
├── data/
│ ├── sample_campaigns.txt
│ └── sample_output.json
├── requirements.txt
└── README.md
- Researchers use it to collect data from Kickstarter campaigns, so they can analyze trends in campaign descriptions and creator profiles.
- Data analysts use it to gather large datasets from Kickstarter for building machine learning models.
- Microeconomics scholars use it to extract campaign text for economic analysis and social science research.
Q: How do I set up the scraper?
A: Simply clone the repository and install the required dependencies listed in requirements.txt. You'll need to have Python 3.6+ installed.
Q: What if I want to extract more data fields?
A: You can modify the extractor scripts to scrape additional data fields, such as funding goals or reward tiers.
Q: How can I scale this scraper to handle more campaigns?
A: The scraper is designed to handle large datasets. You can adjust the settings in settings.example.json to manage the number of campaigns processed in parallel.
Q: Is this scraper reliable for large batches of campaigns?
A: Yes, the scraper is optimized for high scalability and can handle up to 610,000 campaigns as needed.
Primary Metric: Average scraping speed of 10 pages per minute.
Reliability Metric: 98% success rate in extracting text from valid Kickstarter campaign pages.
Efficiency Metric: Capable of processing 50,000 campaigns per day on a standard cloud instance.
Quality Metric: Data completeness is 99% for campaign description and creator profile text.
"Bitbash is a top-tier automation partner, innovative, reliable, and dedicated to delivering real results every time." Nathan Pennington
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"Bitbash delivers outstanding quality, speed, and professionalism, truly a team you can rely on." Eliza
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"Exceptional results, clear communication, and flawless delivery. Syed
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