Abstract
Modern metrics like Altmetrics help researchers and scientists to gauge the impact of their research findings through social media discussions. Twitter holds more scholarly and scientific discussions than other social media platforms and is extensively used to discuss and share research articles by domain experts as well as by the general public. In this study, we have analyzed the motivations of people using Twitter as a medium to propagate the research works. Tweets and the publication details from the field of medicine are collected from altmetric.com for journals with high impact factors and a Support Vector Machine classifier is developed with 85.2% accuracy to categorize the tweets into one of the six motivation classes. The model is then extended to observe the pattern of user motivations in chemistry and environmental science. Medicine and environmental science were found to have similar patterns in user motivations as they directly impact the general public. Chemistry, on the other hand, showed a peculiar pattern with a high percentage of self-citation and promotion. From this study, the domain is also found to play a vital role in measuring research impacts when alternate metrics are used.
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Kumar, M.S., Gupta, S., Baskaran, S., Na, JC. (2019). User Motivation Classification and Comparison of Tweets Mentioning Research Articles in the Fields of Medicine, Chemistry and Environmental Science. In: Jatowt, A., Maeda, A., Syn, S. (eds) Digital Libraries at the Crossroads of Digital Information for the Future. ICADL 2019. Lecture Notes in Computer Science(), vol 11853. Springer, Cham. https://doi.org/10.1007/978-3-030-34058-2_5
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