Hello, this is Hashscraper.
Recently, we have been receiving many inquiries about web crawling.
It seems that many people want to make accurate decisions based on data!
One of the most frequently asked questions is about text mining, natural language processing, and image analysis using data collected through web crawling.
Many individuals who are establishing business models or planning marketing strategies want to analyze data, visualize insights, and market smartly online.
However, there is a problem. The cost, right? The cost of natural language processing and image analysis is 2-3 times higher than web crawling. Employees of companies struggling to allocate budgets and founders who are just starting out and lack operating funds end up wandering around looking for a place where they can crawl and analyze data with a small amount of money.
For these individuals, we have created a dashboard capable of natural language processing, image analysis, and OCR analysis.
While other data analysis companies require significant costs for their analysis tools, we provide our services very affordably so that many people can analyze data without worrying about money. You can even use the tool yourself to extract various analysis results. It's not difficult. It only takes a few clicks.
1. How to Use Hashscraper Dashboard
The dashboard is open to everyone.
Sign up and log in to create your own dashboard.
When the dark homepage appears, click on the menu item DASHBOARD among the top menu.
Then, your personalized dashboard will appear as shown below.
On the main screen, you can see how many data crawling schedules there are, how many points are left, and whether the data crawling was successful or not.
Hashscraper can also be used on a prepaid basis. When you deposit points (1 point = 1 won), the points will be deducted as much as the amount of data collected. Since only the data collected from the points you deposited will be used, you don't have to worry about suddenly incurring a large cost due to a large amount of data being collected.
The screen below shows the web crawling task schedule.
Several tasks are in progress. You can check the deducted points and data amount, paging processing count, and retry confirmation count.
Shall we click on the green button 'View Data' on the side?
2. Getting Started with Web Crawling
You can check the detailed contents when you enter the specific page.
By clicking on the blue button in the top left corner of the screen below, 'Start Data Collection', you can manually collect data.
Each schedule has bots that can be collected, so you can collect data in real-time just by pressing a button. You can scrape information that changes in real-time within 1 second. If you click on the green button on the left, 'View Data', you can visually check the collected data.
The tasks I asked to collect last night are displayed.
The first item indicates whether the crawling was successful or not. TRUE means it was successful, right?
You can also check the Elapsed Time (collection time) as the 9th item. It takes an average of 1.3 seconds to scrape one item.
If you need real-time information collection, you can increase the speed. You can collect one page within 0.1 seconds.
Once the collection is complete, you will receive an alert message saying 'Collection is complete'.
Then, come to the dashboard and download it as an Excel or image. Do you see the green button in the top right corner of the screen below?
15,000 data have been easily downloaded as an Excel file.
Now, you can utilize this data for sales, marketing, and more.
You can even create a service to check product prices or product lists in real-time.
Web crawling technology is used to collect and analyze data to analyze trends or create sales prediction models. It is being utilized in various industries in various ways.
When web crawling, you often encounter a lot of duplicate data.
This is especially common when collecting articles. There are many cases where the contents are almost the same except for the journalist's name and channel.
To address this, we provide a service that analyzes the similarity ratio by comparing texts (Fuzzy String Match).
I tried comparing a few sample texts, and it showed a similarity ratio of 89%.
You can input text there, compare it, check the matching ratio, and if a high matching ratio is achieved, we will refine the data and provide it.
3. Processing Web Crawling Data with Natural Language Processing (Morphological Analysis, Sentiment Analysis)
When you want to analyze social media posts, articles, or comments collected through web crawling, the most essential task is natural language processing.
The first step in natural language processing is morphological analysis. It involves cutting the text into morphemes (the smallest units of a sentence) and understanding the structure of various linguistic attributes such as roots, prefixes/suffixes, and parts of speech. By entering text as shown below and clicking the 'Process' button, the morphemes will be analyzed.
Let's see how sentiment analysis (Sentiment Analytics), which analyzes the positivity/negativity of sentences, is done.
By entering text as shown below and clicking the 'Process' button, the results will be displayed in the 'Results' section.
It is possible to analyze sentence by sentence, and the closer the Score is to 1, the more positive it is, and the closer to -1, the more negative. If the Score is 0.5, it means it is a neutral value, neither positive nor negative.
4. Analyzing Image Data Collected through Web Crawling (OCR, Label Detection)
Analyzing images is not difficult either.
Upload the desired image and click the analyze button to detect and display information about each object in the image along with its accuracy percentage.
For example, if the image is detected as a Tree with a score of 98%, it means that the tree is recognized in the image with 98% accuracy.
In addition to common objects like tree, sky, woody plant, and leaf, it can extract inferred words like Architecture, shade, house, City. It's surprisingly accurate, right? It seems smarter than me. (Sad)
OCR (Optical Character Recognition) also provides results when you upload the desired file and click analyze. (It's all the same. Too easy...)
It can recognize characters from scanned document files, jpg images, PDF files, etc.
It recognized and extracted the text 'Classic Big Size Button Detail' from the image shown below.
You can extract text from a shopping mall product page or find specific text in a PDF document.
In addition to the aforementioned natural language processing and image analysis, it is also possible to perform demand forecasting, brand asset measurement, advertising effectiveness measurement, and modeling tasks.
Through discussions with data analysis experts, we aim to provide you with meaningful insights that are truly necessary and help you achieve actual business results.
We can assist you with the following tasks.
So far, I have provided guidance on how to use the Hashscraper dashboard for web crawling, natural language processing (NLP), and image analysis.
Also, check out this article:
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