Tweets on carbon dioxide removal

<div> <h1><span>Growing online attention and positive sentiments towards</span><br><span>carbon dioxide removal</span></h1> <p>Tim Repke, Finn M&uuml;ller-Hansen, Emily Cox, Jan Minx</p> <p><em><span>(unpublished)</span></em></p> <p><span>Scaling up CO2 removal is crucial to achieve net-zero targets and limit global warming.&nbsp;</span><span>Understanding public perception of large-scale carbon dioxide removal (CDR) is vital to </span><span>avoid opposition that could slow down development, investments, and deployment.&nbsp;<br></span><span>Using Twitter data from 2010 to 2022, we analysed attention and sentiments towards ten </span><span>CDR methods. Our study provides up-to-date time series evidence complementing survey </span><span>studies, capturing the opinions of users with knowledge or awareness of emerging CDR </span><span>methods. </span><span>Attention towards CDR has grown exponentially, particularly in recent years.&nbsp;<br></span><span>Overall,&nbsp;</span><span>the discourse on CDR has become more positive, except for BECCS. Conventional CDR </span><span>methods are the most discussed and receive more positive sentiments. We examined three </span><span>user types, each with varying levels of involvement in the discourse.</span> <span>Infrequent users (as</span><span>sumed less familiar) pay more&nbsp; attention to methods with biological sinks, while frequent </span><span>users (assumed more familiar) focus more on novel CDR methods.</span></p> <h3><span>Dataset description</span></h3> <p><strong><span>export.csv<br></span></strong><span>This dataset contains all Twitter IDs of tweets retrieved for this study. We also include all technology annotations, which technology-specific subquery this relates to, sentiment classification, and user type. Note, that this dataset contains more tweets than used in the study.</span></p> <p><strong>UserPanels.csv<br></strong>This is an overview of all users, their categorisation, and the number of positive/negative/neutral tweets. This could also be derived from the export.csv.</p> </div> <div> <div>&nbsp;</div> <div>&nbsp;</div> </div>