Analyzing Natural Disaster related Tweets with AI and NLP based Services

Citation Author(s):
Fahim
Sufi
Federal Government
Submitted by:
Fahim Sufi
Last updated:
Sun, 12/26/2021 - 06:24
DOI:
10.21227/p0ed-cb23
Data Format:
*.csv
License:
Creative Commons Attribution
833 Views
Categories:
Artificial Intelligence
Machine Learning
Climate Change/Environmental
Keywords:
artificial intelligence; machine learning; natural language processing; sentiment analysis; named entity recognition;
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Abstract 

Tweets related to 10 different types of disasters were monitored from 28 September 2021 till 6 October 2021. 67528 rows containing 16 fields were extracted using Artificial Intelligence and Natural Language Processing Services of Microsoft.

Instructions: 

Excel file contains 67528 rows containing the following 16 fields:

 

1              TweetID               Text

2              EntityType          Text

3              Entity    Text

4              EntityConfidence             Decimal

5              TweetDate         DateTime

6              Sentiment           Text

7              SentimentPositive           Decimal

8              SentimentNegative         Decimal

9              SentimentNeutral            Decimal

10           Favourite             Numeric

11           Retweet              Numeric

12           TweetType         Text

13           Category              Text

14           Language             Text

15           CategoryConfidence       Decimal

16           Source  Text

Dataset Files

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