| Literature DB >> 29134093 |
Manu E Saunders1, Meghan A Duffy2, Stephen B Heard3, Margaret Kosmala4, Simon R Leather5, Terrence P McGlynn6,7, Jeff Ollerton8, Amy L Parachnowitsch9.
Abstract
The popularity of science blogging has increased in recent years, but the number of academic scientists who maintain regular blogs is limited. The role and impact of science communication blogs aimed at general audiences is often discussed, but the value of science community blogs aimed at the academic community has largely been overlooked. Here, we focus on our own experiences as bloggers to argue that science community blogs are valuable to the academic community. We use data from our own blogs (n = 7) to illustrate some of the factors influencing reach and impact of science community blogs. We then discuss the value of blogs as a standalone medium, where rapid communication of scholarly ideas, opinions and short observational notes can enhance scientific discourse, and discussion of personal experiences can provide indirect mentorship for junior researchers and scientists from underrepresented groups. Finally, we argue that science community blogs can be treated as a primary source and provide some key points to consider when citing blogs in peer-reviewed literature.Entities:
Keywords: blogging; communication; impact; science community
Year: 2017 PMID: 29134093 PMCID: PMC5666276 DOI: 10.1098/rsos.170957
Source DB: PubMed Journal: R Soc Open Sci ISSN: 2054-5703 Impact factor: 2.963
Details of the authors' blogs, including abbreviations used elsewhere in this article.
| Blog title | abbreviation | Author(s) |
|---|---|---|
| Dynamic Ecology | DE | Duffya |
| Small Pond Science | SPS | McGlynn, Parachnowitscha |
| Scientist Sees Squirrel | SSS | Heard |
| Ecology Bits | EB | Kosmala |
| Jeff Ollerton's Biodiversity Blog | JOBB | Ollerton |
| Don't Forget the Roundabouts | DFR | Leather |
| Ecology is Not a Dirty Word | ENDW | Saunders |
aThese blogs have additional contributors who did not co-author this paper. DE: Jeremy Fox, Brian McGill; SPS: Catherine Scott.
Summary data for each blog. See table 1 for blog abbreviations and electronic supplementary material for raw data.
| blog | start date | average posts/ month | total followers | total comments | total visitors | total views | top views by country of origin (%) | top views by referrer (%) |
|---|---|---|---|---|---|---|---|---|
| DE | June 2012 | 21 | 9248 | 21 265 | 1 178 092 | 2 587 900 | USA (50%) | search engines (24%) |
| SPS | Feb 2013 | 11 | 2160 | 4354 | 572 243 | 1 000 766 | USA (60%) | search engines (29%) |
| SSS | Jan 2015 | 7 | 2873 | 2336 | 124 858 | 215 148 | USA (41%) | Twitter (21%) |
| EB | Jan 2016 | 3 | 54 | 261 | 46 115 | 59 632 | USA (56%) | Facebook (27%) |
| JOBB | Mar 2012 | 5 | 550 | 2074 | 79 052 | 123 936 | UK (41%) | Facebook (24%) |
| DFR | Jan 2013 | 3 | 259 | 865 | 68 072 | 119 038 | UK (37%) | search engines (48%) |
| ENDW | Oct 2009 | 2 | 473 | 859 | 28 290 | 53 479 | Australia (31%) | search engines (20%) |
Figure 1.Median monthly blog views for the entire sample period for each of the seven blogs represented in this analysis. See table 1 for blog codes.
Figure 2.Relationship between monthly views and number of posts published per month for (a) group author blogs and (b) single-author blogs. Asterisks next to correlation coefficients indicate p < 0.001. One extreme outlier was removed from EB to improve readability. See table 1 for blog abbreviations and electronic supplementary material for raw data.
Figure 3.Word cloud created from the topics of all top 10 posts from our sample blogs (n = 70). Larger words indicate higher frequency of occurrence. Posts were assigned to general categories based on the content and opinions expressed in the post. ‘Academia’, broader academic issues and experiences relevant across multiple disciplines; ‘PeerReview’, posts about reviewing papers or the peer review system; ‘Research’, methods or issues relating to research practice; ‘Teaching’, posts directly relevant to teaching undergraduate students; ‘NaturalHistory’, posts on natural history or ecology of a species; ‘Scicomm’, posts focused on fact-checking media coverage or communicating a topical scientific issue to non-specialist audiences; ‘Analysis’, posts providing analysis of published research; ‘Statistics’, posts about statistical issues or components; ‘Politics’, posts focused on topical political issues; ‘Humanities’, posts comparing humanities and science disciplines. See the electronic supplementary material for data.