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