I am looking for Consumer complaint/review description data which is not generated from automatic logs but manually entered by the end-user/customer-support.

The objective is to run the Stanford NLP-NER tool on the user description for determining the Location, Organization, Faulty Device, etc related to the complaint. I have been struggling for 2-3 days to explore and have found some Telco data, but all of the Data is STRUCTURED. See my answer on this question.

The key elements of the data I need are -

  1. UNSTRUCTURED description by the end-user or by customer-support.
  2. Data can be in the form of either of 'complete sentences' or phrases(say comma separated/semi-colon separated data). A hypothetical example (just for the sake of clarity and not restricted to the following format) of tow of the concerned columns among the rest of the user/caller info -

Fault Description - "I am calling from New York; staying at Hotel Marriot Marquis; Please help asap - my phone not working."

Fault Resolution - "System connection established in New York; Hotel Marriot Marquis; Issue resolved by on-site visit - problem in region multiplexer..bla bla."

I believe this problem would make for an interesting application in the Telecom domain.

1 Answer 1


I'm also looking for similar. Did you check reddit forums? Reddit has a decent API for scraping. Also many telcos have their own customer complaint forums.

Also structured, but I came across the fact that MeaningCloud provides some pre-trained categorization models for Telco vertical https://www.meaningcloud.com/developer/documentation/predefined/deep-categorization-models/voc-telco

Let me know if you found anything else!

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Not the answer you're looking for? Browse other questions tagged or ask your own question.