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Customer Support on Twitter

Customer Support on Twitter

Stefan
Open Dataset
Creators: Axelbrooke, Stuart
Publication Date: 2017
Creators: Axelbrooke, Stuart

The Customer Support on Twitter dataset is a large, modern corpus of tweets and replies to aid innovation in natural language understanding and conversational models, and for study of modern customer support practices and impact. It is intended to facilitate advancements in natural language understanding and the development of conversational models. Compiled by Stuart Axelbrooke in 2017, this dataset encompasses tweets and replies from prominent companies such as Apple, Amazon, Uber, Delta, and Spotify. It provides valuable insights into contemporary customer support practices and their impact, making it an essential resource for researchers interested in automated response generation, sentiment analysis, and conversational flow modeling. The dataset is approximately 516.53 MB in size. It is designed for the analysis of conversation dynamics and contains several key attributes. Each tweet entry has a unique, anonymized tweet ID (tweet_id), an anonymized user ID (author_id), a timestamp (created_at), and the tweet text (text), where sensitive information such as phone numbers and email addresses has been masked to ensure privacy. It differentiates between inbound tweets (inbound), which are directed at companies by customers, and outbound tweets, which are responses from the companies. Additionally, in_response_to_tweet_id and response_tweet_id fields allow for the reconstruction of entire conversation threads by linking tweets to their respective responses.

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