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)
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md5:678dd3dd90603235cd33d591b0515811
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23.3 kB | Preview Download |
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 |
Details
| Resource type | Open dataset |
| Title | Twitter US Airline Sentiment |
| Creators |
|
| Publisher | Kaggle |
| Year of publication | 2016 |
| Dates of collection | February 1, 2015 |
| Research fields | Business Administration Economics Psychology Sociology Political Science Economic & Social History Communication Sciences Educational Research Other |
| Industries | Airlines |
| Countries | United States |
| Size | 0.008 GB |
| Formats | Comma-separated values (CSV) (.csv) SQLite database |
| External resource | https://www.kaggle.com/crowdflower/twitter-airline-sentiment |