Who says what about the most-discussed articles of Altmetric?

In Altmetrics, tweets are considered as important potential indicators of immediate social impact of scholarly articles. However, it is still unclear to what extent Twitter captures the actual scholarly impact. Therefore, it is necessary to investigate the people who cite the articles and the content of the tweets with attitude towards the articles comprehensively. In this paper, we combine different indicators to identify opinion leaders in the spread of the articles, and use sentimental analysis to quantify the sentimental polarity of tweets. Altmetrics should highlight the positive role of scientific research results to the public, which is more valuable than simple numbers

Do you cite what you tweet? Investigating the relationship between tweeting and citing research articles

The last decade of altmetrics research has demonstrated that altmetrics have a low to moderate correlation with citations, depending on the platform and the discipline, among other factors. Most past studies used academic works as their unit of analysis to determine whether the attention they received on Twitter was a good predictor of academic engagement. Our work revisits the relationship between tweets and citations where the tweet itself is the unit of analysis, and the question is to determine if, at the individual level, the act of tweeting an academic work can shed light on the likelihood of the act of citing that same work. We model this relationship by considering the research activity of the tweeter and its relationship to the tweeted work. Results show that tweeters are more likely to cite works affiliated with their same institution, works published in journals in which they also have published, and works in which they hold authorship. It finds that the older the academic age of a tweeter the less likely they are to cite what they tweet, though there is a positive relationship between citations and the number of works they have published and references they have accumulated over time

An extensive analysis of the presence of altmetric data for Web of Science publications across subject fields and research topics

Sufficient data presence is one of the key preconditions for applying metrics in practice. Based on both Altmetric.com data and Mendeley data collected up to 2019, this paper presents a state-of-the-art analysis of the presence of 12 kinds of altmetric events for nearly 12.3 million Web of Science publications published between 2012 and 2018. Results show that even though an upward trend of data presence can be observed over time, except for Mendeley readers and Twitter mentions, the overall presence of most altmetric data is still low. The majority of altmetric events go to publications in the fields of Biomedical and Health Sciences, Social Sciences and Humanities, and Life and Earth Sciences. As to research topics, the level of attention received by research topics varies across altmetric data, and specific altmetric data show different preferences for research topics, on the basis of which a framework for identifying hot research topics is proposed and applied to detect research topics with higher levels of attention garnered on certain altmetric data source. Twitter mentions and policy document citations were selected as two examples to identify hot research topics of interest of Twitter users and policy-makers, respectively, shedding light on the potential of altmetric data in monitoring research trends of specific social attention

Highly tweeted science articles: who tweets them? An analysis of Twitter user profile descriptions

In this study we examined who tweeted academic articles that had at least one Finnish author or co-author affiliation and that had high altmetric counts on Twitter. In this investigation of national level altmetrics we chose the most tweeted scientific articles from four broad areas of science (Agricultural, Engineering and Technological Sciences; Medical and Health Sciences; Natural Sciences; Social Sciences and Humanities). By utilizing both quantitative and qualitative methods of analysis, we studied the data using research techniques such as keyword categorization, co-word analysis and content analysis of user profile descriptions. Our results show that contrary to a random sample of Twitter users, users who tweet academic articles describe themselves more factually and by emphasizing their occupational expertise rather than personal interests. The more field-specific the articles were, the more research-related descriptions dominated in Twitter profile descriptions. We also found that scientific articles were tweeted to promote ideological views especially in instances where the article represented a topic that divides general opinion.</p