With arXiv—part of the world’s leading academic preprint platform—booming, are you wasting countless hours manually collecting paper-related data such as titles, author info, abstracts, publication dates, subject categories, citation counts, and keywords? Faced with its massive repository of academic works, spanning millions of preprints, paginated results and multi-dimensional subject classifications, efficiently acquiring structured paper data to track field progress for researchers or mine research hotspots for scholars has become a common challenge for scientists, university teachers and students, academic editors, and industry researchers. Say goodbye to tedious manual copy-and-paste and page-by-page recording of academic info. BrowserAct will revolutionize the way you access arXiv’s academic paper data.

What is BrowserAct Arxiv Scraper ?

BrowserAct is a powerful automated data extraction tool that lets you easily scrape required data from any web page without programming knowledge. It can efficiently capture key arXiv academic paper data, including titles, author info, abstracts, publication dates, subject categories, citation counts, and keywords. What can it do for you?

• arXiv Academic Paper Scraping: Our arXiv crawler intelligently extracts core academic data. This includes paper titles (e.g., “Machine Learning for Medical Image Analysis,” “Quantum Computing Breakthroughs”), authors (e.g., “Jane Doe, John Smith”), abstracts, publication dates, subject categories (e.g., “Computer Science (cs.AI),” “Physics (hep-th)”), and citation counts (e.g., 200+, 500+). It covers all critical info to track academic research dynamics.
• AI-Powered Field Suggestions: Using AI to identify arXiv page structures (paper listing pages, preprint detail pages), it quickly suggests key fields like "paper title, author, abstract, publication date, subject category". No manual positioning—direct structured data for analysis.
• Ideal Users: Suitable for scientists, university teachers and students, academic editors, and industry researchers. It provides structured arXiv data to drive decisions—like tracking field progress and mining research hotspots—or meet needs such as literature reviews, collaboration matching and academic trend analysis.

Features and Workflow Capabilities

• Input Parameters for Effective Conecte Imóvel Scraping. Detailed explanation of required input parameters, presented in a table for clarity:

How to Use BrowserAct as a CoinMarketCap Scraper

Step 1: Create Workflow and Set Input Parameters

• Click the "Workflow" button in the left sidebar, then "Create" to name your workflow (e.g., "Financial Data Automation").
• Define customizable inputs for flexibility:

arXiv_Link
Keyword

Step 2: Add Navigation and Search Actions 📍

• Click the "+" icon to add actions. Start with "Visit Page" and enter "Visit /url" to direct the workflow to the specified URL, such as https://arxiv.org/search/. BrowserAct's AI will automatically understand the page structure, powering your Forbes web scraper without hassle.

Step 3: Add "Extract Data" Action 📊

• Click "+" and select "Extract Data." In the description box, specify what to extract and set limits, such as:

Extract name/title and add it to "Name" - add Authors to "Authors" - add Abstract to "Abstract" - Add link to the item to "URL"

• The AI will interpret your request and precisely scrape Rightmove houses list—no CSS selectors, no XPath, no coding required. This makes BrowserAct a seamless job scraper for scraping jobs from the internet.

Step 4: Add Output, Publish, and Run 📈

• Click "+" and select "Finish: Output Data." Choose CSV as the output format and enable "Output as a file" for easy downloading.

• Click "Publish" to save and finalize your Forbes scraper.

• Navigate to the "Run" section. Adjust parameters if Forbes (or use defaults), then click "Start" to execute the scrape.

Step 5: Download the Results

• Before downloading, you can preview the scraped results to see if they meet your expectations.