945,000 Real-World Customer Support Conversations from Twitter

945,000 English tweets provide a large corpus of real-world conversations between consumers and support agents on Twitter. The dataset, created by Prady06 and last updated in March 2026, is designed to drive innovation in Natural Language Processing by matching contemporary support language.

Use Cases

• Fine-tuning language models for customer support responses based on real Twitter conversations.
• Training classifiers to identify customer intent or sentiment based on the conversational text.
• Developing dialogue systems that mimic real agent-consumer interactions based on the dataset's context.
• Analyzing linguistic patterns in modern, informal customer service exchanges.

Strengths

• Large scale of 945,000 real-world conversations.
• Focus on contemporary language used in a major social media platform (Twitter).
• Explicitly designed for NLP innovation, as stated in the description.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is the only known size metric; file formats and other specifics are unknown.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Twitter, via Hugging Face user Prady06.

Collection Method

Likely gathered via Twitter API, as indicated by platform tags.

Time Range

null

Freshness

Last updated 2026-03-28 06:42:59.

Geography

Region tag suggests a US focus, but coverage is not explicitly defined.