CCUS Sentiment Analysis - Tweets Dataset

The present dataset contains Tweets in any language supported by Twitter obtained during the months January to March 2023, with any mention to the topic CCS/CCUS. The scraping process were done in Python, using the official Twitter API. All tweets were manually annotated after being machine translated into English.

- Structure 
Every row contains: 
1st cell (A): Language 
2nd cell (B): Tweet-text 
3rd cell (Cc: Benefit 
4th cell (D): Concern 
5th cell (E): Perception – Fight climate change 
6th cell (F): Perception – Climate-friendly technology 
7th cell (G): Perception – Extensive R&D needed 
8th cell (H): Perception – Better options than CCS 
9th cell (I): Sentiment 
10th cell (J): Relatedness 
11th cell (K): Comments 

- Annotations 
Benefit 
Preventing c. change 
Reducing c. change risks 
Safeguarding jobs 
Creating new jobs 
Fossil energy production envir. friendly 
Products envir. friendly 
Reducing envir. impact 
Other 
None 
Concern 
Accidents 
Leakages 
Environmental 
Earthquake-related 
Increased local traffic 
Investment 
Greenwashing 
Lock-in effects for fossil energy 
Increase cost 
Other 
None 
Perception (Yes / No / None) 
Fight climate change 
Climate-friendly technology 
Extensive R&D needed 
Better options than CCS 
Sentiment 
Positive 
Negative 
Neutral