Despite differences in extent of engagement of users, original tweets and retweets to scientific publications are considered as equal events. Current research investigates quantifiable differences between tweets and retweets from an altmetric point of view. Twitter users, text, and media content of two datasets, one containing 742 randomly selected tweets and retweets (371 each) and another with 5898 tweets and retweets (about 3000 each), all linking to scientific articles published on PLoS ONE, were manually categorized. Results from analyzing the proportions of tweets and retweets indicated that academic and individual accounts produce majority of original tweets (34% and 55%, respectively) and posted significantly larger proportion of retweets (41.5 and 81%). Bot accounts, on the other hand, had posted significantly more original tweets (20%) than retweets (2%). Natural communication sentences prevailed in retweets and tweets (63% vs. 45%) as well as images (41.5% vs. 23%), both showing a significant rise in usage overtime. Overall, the findings suggest that the attention scientific articles receive on Twitter may have more to do with human interaction and inclusion of visual content in the tweets, than the significance of or genuine interest towards the research results.
https://doi.org/10.1007/s11192-024-05127-8
| Artificial Intelligence |
| Research Data Curation and Management Works |
| Digital Curation and Digital Preservation Works |
| Open Access Works |
| Digital Scholarship |
