Published 2016
| Version v2
Open dataset
Open
Twitter US Airline Sentiment
Description
Description
A sentiment analysis job about the problems of each major U.S. airline. Twitter data was scraped from February of 2015 and contributors were asked to first classify positive, negative, and neutral tweets, followed by categorizing negative reasons (such as "late flight" or "rude service").
Files
Tweets.csv__100lines.csv
Files
(23.3 kB)
| Name | Size | Download all |
|---|---|---|
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md5:678dd3dd90603235cd33d591b0515811
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Details
| Resource type | Open dataset |
| Title | Twitter US Airline Sentiment |
| Creators |
|
| Publisher | Kaggle |
| Year of publication | 2016 |
| Dates of collection | February 1, 2015 |
| External resource | https://www.kaggle.com/crowdflower/twitter-airline-sentiment |
| Size | 0.008 GB |
| Formats | Comma-separated values (CSV) (.csv) SQLite database |
Variables
| Name | Description |
|---|---|
| tweet_id | tweet_id |
| airline_sentiment | Airline sentiment, either positive / neutral / negative |
| airline_sentiment_confidence | airline_sentiment_confidence |
| negativereason | negativereason |
| negativereason_confidence | negativereason_confidence |
| airline | airline |
| airline_sentiment_gold | airline_sentiment_gold |
| name | name |
| negativereason_gold | negativereason_gold |
| retweet_count | retweet_count |