Scrape ResearchGate All Authors, Researchers in Python

Intro

Currently, we don't have an API that supports extracting data from the ResearchGate Search page.

This blog post is to show you how you can do it yourself with the provided DIY solution below while we're working on releasing our proper API.

The solution can be used for personal use as it doesn't include the Legal US Shield that we offer for our paid production and above plans and has its limitations such as the need to bypass blocks, for example, CAPTCHA.

You can check our public roadmap to track the progress for this API:

🗺️

[New API] ResearchGate Search: Publications, Authors, Questions

What will be scraped

📌Note: For now, we don't have an API that supports extracting ResearchGate data.

This blog post is to show you how you can do it yourself. Let us know if you want to have this API made by us.

Prerequisites

Basic knowledge scraping with CSS selectors

If you haven't scraped with CSS selectors, there's a dedicated blog post of mine about how to use CSS selectors when web-scraping that covers what it is, pros and cons, and why they matter from a web-scraping perspective and show the most common approaches of using CSS selectors when web scraping.

Separate virtual environment

If you haven't worked with a virtual environment before, have a look at the dedicated Python virtual environments tutorial using Virtualenv and Poetry blog post of mine to get familiar.

Reduce the chance of being blocked

There's a chance that a request might be blocked. Have a look at how to reduce the chance of being blocked while web-scraping, there are eleven methods to bypass blocks from most websites.

📌Note: If you'll be using this code snippet without proxies, the requests will be blocked in a short period of time. Scraping with proxies large amount of data is a way to go.

Install libraries:

pip install parsel playwright

Full Code

from parsel import Selector
from playwright.sync_api import sync_playwright
import json


def scrape_researchgate_profile(query: str):
    with sync_playwright() as p:

        browser = p.chromium.launch(headless=True, slow_mo=50)
        page = browser.new_page(user_agent="Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/101.0.4951.64 Safari/537.36")

        authors = []
        page_num = 1

        while True:
            page.goto(f"https://www.researchgate.net/search/researcher?q={query}&page={page_num}")
            selector = Selector(text=page.content())

            for author in selector.css(".nova-legacy-c-card__body--spacing-inherit"):
                name = author.css(".nova-legacy-v-person-item__title a::text").get()
                thumbnail = author.css(".nova-legacy-v-person-item__image img::attr(src)").get()
                profile_page = f'https://www.researchgate.net/{author.css("a.nova-legacy-c-button::attr(href)").get()}'
                institution = author.css(".nova-legacy-v-person-item__stack-item:nth-child(3) span::text").get()
                department = author.css(".nova-legacy-v-person-item__stack-item:nth-child(4) span").xpath("normalize-space()").get()
                skills = author.css(".nova-legacy-v-person-item__stack-item:nth-child(5) span").xpath("normalize-space()").getall()
                last_publication = author.css(".nova-legacy-v-person-item__info-section-list-item .nova-legacy-e-link--theme-bare::text").get()
                last_publication_link = f'https://www.researchgate.net{author.css(".nova-legacy-v-person-item__info-section-list-item .nova-legacy-e-link--theme-bare::attr(href)").get()}'

                authors.append({
                    "name": name,
                    "profile_page": profile_page,
                    "institution": institution,
                    "department": department,
                    "thumbnail": thumbnail,
                    "last_publication": {
                        "title": last_publication,
                        "link": last_publication_link
                    },
                    "skills": skills,
                })
            
            print(f"Extracting Page: {page_num}")

            # checks if next page arrow key is greyed out `attr(rel)` (inactive) -> breaks out of the loop
            if selector.css(".nova-legacy-c-button-group__item:nth-child(9) a::attr(rel)").get():
                break
            else:
                # paginate to the next page
                page_num += 1


        print(json.dumps(authors, indent=2, ensure_ascii=False))

        browser.close()
        
    
scrape_researchgate_profile(query="coffee")

Code explanation

Import libraries:

from parsel import Selector
from playwright.sync_api import sync_playwright
import json

Code	Explanation
`parsel`	to parse HTML/XML documents. Supports XPath.
`playwright`	to render the page with a browser instance.
`json`	to convert Python dictionary to JSON string.

Define a function and open a playwright with a context manager::

def scrape_researchgate_profile(query: str):
    with sync_playwright() as p:
        # ...

Code	Explanation
`query: str`	to tell Python that `query` should be an `str`.

Launch a browser instance, open new_page with passed user-agent:

browser = p.chromium.launch(headless=True, slow_mo=50)
page = browser.new_page(user_agent="Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/101.0.4951.64 Safari/537.36")

Code	Explanation
`p.chromium.launch()`	to launch Chromium browser instance.
`headless`	to explicitly tell `playwright` to run in headless mode even though it's a defaut value.
`slow_mo`	to tell `playwright` to slow down execution.
`browser.new_page()`	to open new page. `user_agent` is used to act a real user makes a request from the browser. If not used, it will default to `playwright` value which is `None`. Check what's your user-agent.

Add a temporary list, set up a while loop, and open a new URL:

authors = []

while True:
    page.goto(f"https://www.researchgate.net/search/researcher?q={query}&page={page_num}")
    selector = Selector(text=page.content())
    # ...

Code	Explanation
`goto()`	to make a request to specific URL with passed query and page parameters.
`Selector()`	to pass returned HTML data with `page.content()` and process it.

Iterate over author results on each page, extract the data and append to a temporary list:

for author in selector.css(".nova-legacy-c-card__body--spacing-inherit"):
    name = author.css(".nova-legacy-v-person-item__title a::text").get()
    thumbnail = author.css(".nova-legacy-v-person-item__image img::attr(src)").get()
    profile_page = f'https://www.researchgate.net/{author.css("a.nova-legacy-c-button::attr(href)").get()}'
    institution = author.css(".nova-legacy-v-person-item__stack-item:nth-child(3) span::text").get()
    department = author.css(".nova-legacy-v-person-item__stack-item:nth-child(4) span").xpath("normalize-space()").get()
    skills = author.css(".nova-legacy-v-person-item__stack-item:nth-child(5) span").xpath("normalize-space()").getall()
    last_publication = author.css(".nova-legacy-v-person-item__info-section-list-item .nova-legacy-e-link--theme-bare::text").get()
    last_publication_link = f'https://www.researchgate.net{author.css(".nova-legacy-v-person-item__info-section-list-item .nova-legacy-e-link--theme-bare::attr(href)").get()}'

    authors.append({
        "name": name,
        "profile_page": profile_page,
        "institution": institution,
        "department": department,
        "thumbnail": thumbnail,
        "last_publication": {
            "title": last_publication,
            "link": last_publication_link
        },
        "skills": skills,
    })

Code	Explanation
`css()`	to parse data from the passed CSS selector(s). Every CSS query traslates to XPath using `csselect` package under the hood.
`::text`/`::attr(attribute)`	to extract textual or attribute data from the node.
`get()`/`getall()`	to get actual data from a matched node, or to get a `list` of matched data from nodes.
`xpath("normalize-space()")`	to parse blank text node as well. By default, blank text node is be skipped by XPath.

Check if the next page is present and paginate:

# checks if the next page arrow key is greyed out `attr(rel)` (inactive) -> breaks out of the loop
if selector.css(".nova-legacy-c-button-group__item:nth-child(9) a::attr(rel)").get():
    break
else:
    page_num += 1

Print extracted data, and close browser instance:

print(json.dumps(authors, indent=2, ensure_ascii=False))

browser.close()

# call the function
scrape_researchgate_profile(query="coffee")

Part of the JSON output:

[
  {
    "name": "Marina Ramón-Gonçalves", # first profile
    "profile_page": "https://www.researchgate.net/profile/Marina-Ramon-Goncalves?_sg=VbWMth8Ia1hDG-6tFnNUWm4c8t6xlBHy2Ac-2PdZeBK6CS3nym5PM5OeoSzha90f2B6hpuoyBMwm24U",
    "institution": "Centro Nacional de Investigaciones Metalúrgicas (CENIM)",
    "department": "Reciclado de materiales",
    "thumbnail": "https://i1.rgstatic.net/ii/profile.image/845010970898442-1578477723875_Q64/Marina-Ramon-Goncalves.jpg",
    "last_publication": {
      "title": "Extraction of polyphenols and synthesis of new activated carbon from spent coffe...",
      "link": "https://www.researchgate.netpublication/337577823_Extraction_of_polyphenols_and_synthesis_of_new_activated_carbon_from_spent_coffee_grounds?_sg=2y4OuZz32W46AWcUGmwYbW05QFj3zkS1QR_MVxvKwqJG-abFPLF6cIuaJAO_Mn5juJZWkfEgdBwnA5Q"
    },
    "skills": [
      "Polyphenols",
      "Coffee",
      "Extraction",
      "Antioxidant Activity",
      "Chromatography"
    ]
  }, ... other profiles
  {
    "name": "Kingsten Okka", # last profile
    "profile_page": "https://www.researchgate.net/profile/Kingsten-Okka?_sg=l1w_rzLrAUCRFtoo3Nh2-ZDAaG2t0NX5IHiSV5TF2eOsDdlP8oSuHnGglAm5tU6OFME9wgfyAd-Rnhs",
    "institution": "University of Southern Queensland ",
    "department": "School of Agricultural, Computational and Environmental Sciences",
    "thumbnail": "https://i1.rgstatic.net/ii/profile.image/584138105032704-1516280785714_Q64/Kingsten-Okka.jpg",
    "last_publication": {
      "title": null,
      "link": "https://www.researchgate.netNone"
    },
    "skills": [
      "Agricultural Entomology",
      "Coffee"
    ]
  }
]

Intro

What will be scraped

Prerequisites

Full Code

Code explanation

Links