Scientific discourse on YouTube: Motivations for citing research in comments

Authors : Sören Striewski, Olga Zagovora, Isabella Peters

YouTube is a valuable source of user-generated content on a wide range of topics, and it encourages user participation through the use of a comment system. Video content is increasingly addressing scientific topics, and there is evidence that both academics and consumers use video descriptions and video comments to refer to academic research and scientific publications.

Because commenting is a discursive behavior, this study will provide insights on why individuals post links to research publications in comments. For this, a qualitative content analysis and iterative coding approach were applied. Furthermore, the reasons for mentioning academic publications in comments were contrasted with the reasons for citing in scholarly works and with reasons for commenting on YouTube.

We discovered that the primary motives for sharing research links were (1) providing more insights into the topic and (2) challenging information offered by other commentators.

Arxiv : https://arxiv.org/abs/2405.12798

‘I Updated the ‘: The Evolution of References in the English Wikipedia and the Implications for Altmetrics

Authors : Olga Zagovora, Roberto Ulloa, Katrin Weller, Fabian Flöck

With this work, we present a publicly available dataset of the history of all the references (more than 55 million) ever used in the English Wikipedia until June 2019. We have applied a new method for identifying and monitoring references in Wikipedia, so that for each reference we can provide data about associated actions: creation, modifications, deletions, and reinsertions.

The high accuracy of this method and the resulting dataset was confirmed via a comprehensive crowdworker labelling campaign. We use the dataset to study the temporal evolution of Wikipedia references as well as users’ editing behaviour.

We find evidence of a mostly productive and continuous effort to improve the quality of references: (1) there is a persistent increase of reference and document identifiers (DOI, PubMedID, PMC, ISBN, ISSN, ArXiv ID), and (2) most of the reference curation work is done by registered humans (not bots or anonymous editors).

We conclude that the evolution of Wikipedia references, including the dynamics of the community processes that tend to them should be leveraged in the design of relevance indexes for altmetrics, and our dataset can be pivotal for such effort.

URL : https://arxiv.org/abs/2010.03083

What increases (social) media attention: Research impact, author prominence or title attractiveness?

Authors : Olga Zagovora, Katrin Weller, Milan Janosov, Claudia Wagner, Isabella Peters

Do only major scientific breakthroughs hit the news and social media, or does a ‘catchy’ title help to attract public attention? How strong is the connection between the importance of a scientific paper and the (social) media attention it receives?

In this study we investigate these questions by analysing the relationship between the observed attention and certain characteristics of scientific papers from two major multidisciplinary journals: Nature Communication (NC) and Proceedings of the National Academy of Sciences (PNAS).

We describe papers by features based on the linguistic properties of their titles and centrality measures of their authors in their co-authorship network.

We identify linguistic features and collaboration patterns that might be indicators for future attention, and are characteristic to different journals, research disciplines, and media sources.

URL : https://arxiv.org/abs/1809.06299