Discover the power of the Twitter/X Comment Scraper—your ultimate tool for extracting and analyzing Twitter/X replies and comments effortlessly. Designed for speed and precision, it lets you quickly collect and analyze tweet replies to gain insights for social media research, sentiment tracking, and trend monitoring.
Created by Bitbash, built to showcase our approach to Scraping and Automation!
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The Twitter/X Comment Scraper enables you to scrape Twitter/X comments and replies with advanced sentiment and tone analysis. It's perfect for social media researchers, businesses tracking feedback, or anyone looking to monitor trends and sentiments in real-time.
- Sentiment and Tone Analysis: Detects the sentiment (positive, negative, neutral) and tone (humorous, sarcastic, informative) of each reply.
- Fast Extraction: Scrape up to 100 replies per second, with flexible sorting options like relevancy, latest, or likes.
- Customizable Filters: Use filters to tailor your data extraction based on tweet relevance, popularity, and other criteria.
- Real-time Monitoring: Supports real-time tweet and username change monitoring for continuous trend tracking.
| Feature | Description |
|---|---|
| Sentiment Analysis | Provides sentiment (positive, negative, neutral) and tone (humorous, sarcastic, etc.) analysis. |
| Fast Scraping | Scrapes up to 100 replies per second for rapid data collection. |
| Sorting Options | Sorts replies by relevancy, latest, or likes to suit your analysis needs. |
| Real-Time Monitoring | Supports real-time monitoring of tweets, usernames, and activity changes. |
| Field Name | Field Description |
|---|---|
| commentId | Unique identifier for each comment or reply. |
| userId | Twitter/X user ID of the person posting the comment. |
| isBlueVerified | Indicates whether the user is verified (true/false). |
| twitterName | Display name of the user. |
| twitterUsername | Username of the Twitter/X account posting the comment. |
| viewCount | The number of views for the reply or comment. |
| replyContent | The text content of the reply or comment. |
| likeCount | The number of likes the comment received. |
| replyCount | The number of replies to the comment. |
| retweetCount | The number of retweets the comment received. |
| quoteCount | The number of times the comment has been quoted. |
| bookmarkCount | The number of bookmarks for the comment. |
| createdAt | The timestamp when the reply was posted. |
[
{
"commentId": "1844873984250138716",
"userId": "1355721251180961792",
"isBlueVerified": true,
"twitterName": "Gunther Eagleman™",
"twitterUsername": "GuntherEagleman",
"viewCount": "250756",
"replyContent": "@realDonaldTrump If you support President Trump, we are family! Vote for law and order!",
"likeCount": 6808,
"replyCount": 395,
"retweetCount": 486,
"quoteCount": 12,
"bookmarkCount": 20,
"createdAt": "Fri Oct 11 22:53:28 +0000 2024"
}
]
twitter-x-comment-scraper/
├── src/
│ ├── runner.py
│ ├── extractors/
│ │ ├── twitter_parser.py
│ │ └── utils_time.py
│ ├── outputs/
│ │ └── exporters.py
│ └── config/
│ └── settings.example.json
├── data/
│ ├── inputs.sample.txt
│ └── sample.json
├── requirements.txt
└── README.md
- Researchers use this scraper to analyze sentiment and track trends on social media, so they can gain insights into public opinion.
- Marketing teams use it to track customer feedback on product launches or campaigns, so they can adjust strategies accordingly.
- Media analysts use it to track political conversations and identify major influencers, so they can stay ahead of public discourse.
Q: Do I need a Twitter API key or developer account to use this? A: No, the scraper works without the Twitter API. It uses web automation to extract data directly from public Twitter/X pages.
Q: Can I scrape replies from any public tweet? A: Yes, as long as the tweet is public and replies have not been limited by the original poster, the scraper can access them.
Q: Does this tool work on X (formerly Twitter)? A: Yes, the tool seamlessly supports both Twitter and X platforms, regardless of branding or display changes.
Primary Metric: Scrapes up to 100 replies per second. Reliability Metric: 98% success rate for accessing and extracting replies. Efficiency Metric: Handles large tweet threads with ease, processing thousands of replies in real time. Quality Metric: Provides detailed and accurate sentiment and tone analysis for each reply, with minimal misclassification.
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