Tweets vs. Mendeley readers: How do these two social media metrics differ?

A set of 1.4 million biomedical papers was analyzed with regards to how often articles are mentioned on Twitter or saved by users on Mendeley. While Twitter is a microblogging platform used by a general audience to distribute information, Mendeley is a reference manager targeted at an academic user group to organize scholarly literature. Both platforms are used as sources for so-called “altmetrics” to measure a new kind of research impact. This analysis shows in how far they differ and compare to traditional citation impact metrics based on a large set of PubMed papers.

Hyperlinks as inter-university collaboration indicators

Collaboration is essential for some types of research, and some agencies include collaboration among the requirements for funding research projects. This makes it important to analyse collaborative research ties. Traditional methods to indicate the extent of collaboration between organizations use co-authorship data in citation databases. Publication data from these databases are not publicly available and can be expensive to access and so hyperlink data has been proposed as an alternative. This paper investigates whether using machine learning methods to filter page types can improve the extent to which hyperlink data can be used to indicate the extent of collaboration between universities. Structured information about research projects extracted from UK and EU funding agency websites, co-authored publications and academic links between universities were analysed to identify if there is any association between the number of hyperlinks connecting two universities, with and without machine learning filtering, and the number of publications they co-authored. An increased correlation was found between the number of inlinks to a university’s website and the extent to which it collaborates with other universities when machine learning techniques were used to filter out apparently irrelevant inlinks.

A community of curious souls: an analysis of commenting behavior on TED talks videos

The TED (Technology, Entertainment, Design) Talks website hosts video recordings of various experts, celebrities, academics, and others who discuss their topics of expertise. Funded by advertising and members but provided free online, TED Talks have been viewed over a billion times and are a science communication phenomenon. Although the organization has been derided for its populist slant and emphasis on entertainment value, no previous research has assessed audience reactions in order to determine the degree to which presenter characteristics and platform affect the reception of a video. This article addresses this issue via a content analysis of comments left on both the TED website and the YouTube platform (on which TED Talks videos are also posted). It was found that commenters were more likely to discuss the characteristics of a presenter on YouTube, whereas commenters tended to engage with the talk content on the TED website. In addition, people tended to be more emotional when the speaker was a woman (by leaving comments that were either positive or negative). The results can inform future efforts to popularize science amongst the public, as well as to provide insights for those looking to disseminate information via Internet videos.