How to Download ESG News from All S&P 500 Companies Using API

Hello,
I am looking for a way to download ESG news for all S&P 500 companies using the Refinitiv Data Platform (RDP) API or the Eikon API. My goal is to retrieve articles, headlines, and any relevant information related to sustainability, governance, and ESG criteria for the companies in the index.
Specific Questions:
- Which RDP API endpoints or functions can I use to extract ESG news for multiple companies?
- Is it possible to obtain the data in a structured format (e.g., JSON, CSV) that includes date, source, and ESG scorefor each news article?
- Is there a way to filter news by specific ESG topics (e.g., "climate change," "corporate governance")?
- Are there any limitations on the number of companies or articles that can be retrieved per request?
Usage Context:
- I have access to Refinitiv RDP with permissions for ESG data and news.
- I am working with Python and the
refinitiv.data
library.
Answers
-
Thank you for reaching out to us.
I would like to suggest that you should use the new LSEG Data Library for Python.
The news example are on GitHub.
It uses the news query to filter news headlines. For example:
- "Topic:CLC AND R:0#.SPX". This query gets news headlines that relate to Climate Change and 0#.SPX
- "Topic:ESG and R:0#.SPX". This query gets news headlines that relate to ESG and 0#.SPX
Each request can return at most 100 news headlines.
You can also contact the helpdesk team via MyAccount for the news query or use the news monitor app to generate news queries.
1 -
Hello @jose.guillamon.19
You can use the Content Layer of
. The Content layer has News cand ESG classes that can give you News and ESG data.News Example:
import lseg.data as ld
from lseg.data.content import news
ric = 'TSLA.O'
q = f'R:{ric} AND Topic:ESG'
print(q)
response = news.headlines.Definition(
query= q,
count= 5
).get_data()Then you can get a response data in Dataframe (response.data.df) or in a raw JSON format (response.data.raw).
ESG Examples:
import lseg.data as ld
from lseg.data.content import esg
response = esg.full_scores.Definition(
universe= ric,
start=0,
end=-5
).get_data()
response.data.dfYou can find the full examples here:
1
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