A Twitter dataset sample of over 1000 posts. Dataset was extracted using the Bright Data API.
id
: The unique identifier for the postuser_posted
: The username of the post ownername
: The name of the post ownerdescription
: The text description of the postdate_posted
: The date when the post was publishedphotos
: URLs of any photos attached to the postvideos
: URLs of any videos attached to the posturl
: The URL link to the postquoted_post
: Details of the quoted post within the main posttagged_users
: A list of profiles tagged in the postreplies
: The total number of replies the post has receivedreposts
: The total number of reposts the post has receivedlikes
: The total number of likes the post has receivedviews
: The total number of views the post has receivedexternal_url
: The external URL included in the posthashtags
: The hashtags included in the postfollowers
: The number of followers the profile hasbiography
: The bio of the post ownerposts_count
: The total number of posts the profile has madeprofile_image_link
: The URL to the profile imagefollowing
: The number of profiles the user followsis_verified
: Indicates whether the user is verified (True/False)quotes
: The total number of times the post has been quotedbookmarks
: The total number of times the post has been bookmarkedparent_post_details
: Details of the parent post, if applicable
And a lot more.
This is a sample subset which is derived from the "Twitter Posts (public data)" dataset which includes more than 1,000,000 posts.
Available dataset file formats: JSON, NDJSON, JSON Lines, CSV, or Parquet. Optionally, files can be compressed to .gz.
Dataset delivery type options: Email, API download, Webhook, Amazon S3, Google Cloud storage, Google Cloud PubSub, Microsoft Azure, Snowflake, SFTP.
Update frequency: Once, Daily, Weekly, Monthly, Quarterly, or Custom basis.
Data enrichment available as an addition to the data points extracted: Based on request.
Uncover emerging trends and opportunities by tracking public conversations on Twitter. Monitor retweets, likes, replies, and mentions to identify key topics and shifts in user sentiment. Use the Twitter dataset to gain valuable insights into customer opinions and evolving market trends. Understand public sentiment about your brand, product, or service by analyzing Twitter data. Track changes in popularity through likes, comments, shares, hashtags, and mentions to stay ahead of trends. Gain a competitive edge by assessing the social media activity of rival brands. Review hashtags, posts, and user engagement on Twitter to refine your strategy and outperform competitors.The Bright Initiative offers access to Bright Data's Web Scraper APIs and ready-to-use datasets to leading academic faculties and researchers, NGOs and NPOs promoting various environmental and social causes. You can submit an application here.