Data
Airlines-Tweets-Sentiments

Airlines-Tweets-Sentiments

active ARFF CC0: Public Domain Visibility: public Uploaded 23-03-2022 by Dustin Carrion
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  • Computer Systems Machine Learning
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Context A dataset I used to classify tweets about my company. I took tweets and I classified them manually as positive, negative or neutral. Content There are 4 columns : Id : the tweed id, unique. tweettext : the tweet tweetlang : always EN, all tweets are in english tweetsentiment_value : 0 for negative, 1 for neutral, 2 for positive Acknowledgements Do what you want with it. Inspiration The aim of this dataset is to be able to determine if a tweet is positive or negative about an airline company.

4 features

_idstring1097 unique values
0 missing
tweet_textstring1090 unique values
0 missing
tweet_langstring1 unique values
0 missing
tweet_sentiment_valuenumeric3 unique values
0 missing

19 properties

1097
Number of instances (rows) of the dataset.
4
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
1
Number of numeric attributes.
0
Number of nominal attributes.
0
Number of attributes divided by the number of instances.
25
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
Average class difference between consecutive instances.
0
Percentage of missing values.

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