The Wardle Test for a #socialmedia #selfie effect in science


‘And I am immortal’ (through social media).
Connor MacLeod (The Highlander).

A recent paper in the journal Ideas in Ecology and Evolution inspired me to rethink/temper my optimism in social media as a panacea for effective scientific communication. The running title of the paper, how to tweet your way to honour and glory, by David Wardle captures several primary concerns with altmetrics as a tool to estimate merit, value, or even global reach. We are discussing these ideas at NCEAS today, and as a heuristic, I prepared the following deckumentary (commentary + slide deck). The strengths and limitations of social media as a tool to communicate science are explored.  Several basic solutions are proposed. However, there is an incredible opportunity here to more throughly examine how we handle social media as a tool and evaluate its capacity for effective outreach.

One of the highlights proposed in the article that I really enjoyed but want to emphasize more directly here is the test of a particular potential limitation – non-independence of outreach from the social media stream of the producer.  I propose we should entitle the test developed The Wardle Test for a social-media selfie effect in science.

The social-media selfie effect workflow

  1. Select a set of products with different authors but from a similar outlet (i.e. a journal).
  2. Structure sampling of products to ensure reproducibility (i.e. regular, random, or random-stratified sampling from the outlet), and ensure author-identities are unique in each instance.
  3. Record altmetric scores reported for each product.
  4. Capture twitter-stream for each product.
  5. Assign tweets to product producer (rule: personal twitter account matches first author or organization such as lab) or other (potentially independent twitter account).
  6. Contrast altmetric scores between products tweeted by producers relative to others.

Fantastic idea as a proxy for the positive and negative ‘echo-chamber’ effect discussed widely online. We need an r-script to scrape a larger set of products and associated accounts!

Then, can can calculate not only this social-media selfie effect but also explore some of the contemporary analytical solutions produced online by many ‘influence’ indices including diversifying the signal analysis, weighting (often by audience), and normalization.

The ‘quickening’ of social media amplification is perhaps not immortal, but it is a challenge and thus opportunity for scientific communicators and critical citizens to better validate and use this effect appropriately.



A common sense review of @swcarpentry workshop by @RemiDaigle @juliesquid @ben_d_best @ecodatasci from @brenucsb @nceas

This Fall, I am teaching graduate-level biostatistics. I have not had the good fortune of teaching many graduate-level offerings, and I am really excited to do so. A team of top-notch big data scientists are hosted at NCEAS. They have recently formed a really exciting collaborative-learning collective entitled ecodatascience. I was also aware of the mission of software carpentry but had not reviewed the materials. The ecodatascience collective recently hosted a carpentry workshop, and I attended. I am a parent and use common sense media as a tool to decide on appropriate content. As a tribute to that tool and the efforts of the ecodatascience instructors, here is a brief common sense review.


ecodatascience software carpentry workshop
spring 2016





sw carpentry review

You need to know that the materials, approach, and teaching provided through software carpentry are a perfect example of contemporary, pragmatic, practice-what-you-teach instruction. Basic coding skills, common tools, workflows, and the culture of open science were clearly communicated throughout the two days of instruction and discussion, and this is a clear 5/5 rating. Contemporary ecology should be collaborative, transparent, and reproducible. It is not always easy to embody this. The use of GitHub and RStudio facilitated a very clear signal of collaboration and documented workflows.

All instructors were positive role models, and both men and women participated in direct instruction and facilitation on both days.  This is also a perfect rating. Contemporary ecology is not about fixed scientific products nor an elite, limited-diversity set of participants within the scientific process. This workshop was a refreshing look at how teaching and collaboration have changed. There were also no slide decks. Instructors worked directly from RStudio, GitHub Desktop app, the web, and gh-pages pushed to the browser. It worked perfectly. I think this would be an ideal approach to teaching biostatistics.

Statistics are not the same as data wrangling or coding. However, data science (wrangling & manipulation, workflows, meta-data, open data, & collaborative analysis tools) should be clearly explained and differentiated from statistical analyses in every statistics course and at least primer level instruction provided in data science. I have witnessed significant confusion from established, senior scientists on the difference between data science/management and statistics, and it is thus critical that we communicate to students the importance and relationship between both now if we want to promote data literacy within society.

There was no sex, drinking, or violence during the course :). Language was an appropriate mix of technical and colloquial so I gave it a positive rating, i.e. I view 1 star as positive as you want some colloquial but not too much in teaching precise data science or statistics. Finally, I rated consumerism at 3/5, and I view this an excellent rating. The instructors did not overstate the value of these open science tools – but they could have and I wanted them to! It would be fantastic to encourage everyone to adopt these tools, but I recognize the challenges to making them work in all contexts including teaching at the undergraduate or even graduate level in some scientific domains.

Bottom line for me – no slide decks for biostats course, I will use GitHub and push content out, and I will share repo with students. We will spend one third of the course on data science and how this connects to statistics, one third on connecting data to basic analyses and documented workflows, and the final component will include several advanced statistical analyses that the graduate students identify as critical to their respective thesis research projects.

I would strongly recommend that you attend a workshop model similar to the work of software carpentry and the ecodatascience collective. I think the best learning happens in these contexts. The more closely that advanced, smaller courses emulate the workshop model, the more likely that students will engage in active research similarly. I am also keen to start one of these collectives within my department, but I suspect that it is better lead by more junior scientists.

Net rating of workshop is 5 stars.
Age at 14+ (kind of a joke), but it is a proxy for competency needed. This workshop model is best pitched to those that can follow and read instructions well and are comfortable with a little drift in being lead through steps without a simplified slide deck.


Running discoveries from systematic reviews and meta-analyses

No pun on words intended. I agreed to give a talk this week on the science of running at a pub. Seemed like a good idea at the time for many reasons. I love to run. I recognize that practice in speaking is invaluable. I also like to reach a different audience once in a while in promoting evidence-based decisions and science in general. Running is just another example wherein evidence can facilitate informed decisions. There are over 100,000 primary research articles on the physiology of running alone. Eye of the tiger.


I have been running (and not getting anywhere) for 30 years. Helps me think, and it also benefits others by ‘somewhat’ reducing my twitchiness. Here were my personal discoveries in engaging and processing some of the research literature on this topic. I read none of this prior to this talk preparation, ever, in deciding whether to continue running as a personal choice.

1. Systematic reviews and meta-analyses continue to be the most rapid, effective tools in getting up to speed on the research for a given topic.
2. The risk of injury from running is low unless you run at really high intensities or run really long long distances. Intriguing pattern.
3. Running definitely increases heart health. Many other health outcomes consistently improve with running, but the heart is a big winner.
4. Less is more in terms of footwear unless you have form issues.
5. The benefits from recreational running and light running in sports exceed those of swimming.

Posted in fun

A #scicomm resource guide to video abstracts

I just discovered video abstracts last week thanks to a scientific communication seminar by SciFund founder Jai Ranganathan. Lacking shame, I decided to try one because I just had a paper come out that week. Here was my first attempt at the process.

Of course, I had really no idea what I was doing but did some solid scientific-communication learning.

Personal Discoveries
1. Eyes. Look directly at the camera.
2. Plan. Do not script but think about what you want to say in advance.
3. Do not read. Having the abstract available to read is useful, but watching someone else read it is not that fun and quite distracting (mid-way through you can see me reading it).
4. Personal motivation. Describe your personal reason for doing the paper not listed in the actual abstract.
5. Audience effect. Going public and posting it feels much different than recording and watching on your machine.

A relatively empty niche for ecologists
Excluding kittens, we have an opportunity here. Doing the research now, I checked my two fav ecoblogs (The Oikos Blog and The Journal of Ecology Blog) that are directly associated with journals. I did not see any video content. Loads of great pictures, but no other media.  I also checked the blog provided by Ecography too. Similarly, I could not locate any videos. I then checked the facebook pages for these journals to no avail.  Using the youtube search bar directly, I did find some excellent videos by The Journal of Animal Ecology and Functional Ecology. However, these offerings were not quite the video abstract format I was expecting – author describing a recent paper in brief. If there are loads of them out there for ecology, they are not that easy to find. Consequently, I propose we have an opportunity to do some potentially compelling or at least more personal scientific communication about our research. There are numerous resources for scientists associated directly with video abstracts.

Video abstract resources
1. The scientist videographer blog has a post on how to make a video abstract for your next journal article.  Good introduction.

2. The guidelines provided by the New Journal of Physics for video abstracts are fantastic.

3. Cell also has specific guidelines that are more technical in nature, but the sample videos on the side bar are amazing.

4. To round out your education on the topic, check the out the video abstracts for the Journal of Number Theory.

5. Finally, the simple rules for good oral presentations still apply.

I propose ecologists fire up those webcams built right into the laptops (but use an external mic). We have audience (at least we can share with each other, i.e. ecolog-L has over 10,000 members) and outcomes could include better recognition of one another and appreciation of the inspirations and motivations that drive us to study natural systems.

In a nutshell, plan, be brief (< 4 mins), check audio, minimize distractions, be personable, and view as a mini-story (somewhere between elevator pitch & actual abstract).


#fieldwork takes practice: lost quadrat and #zenmind

Fieldwork takes practice.
I love this pic because the landscape is so spectacular (Cuyama Valley, here is the post on the work our team is doing there), and it ‘looks’ like I am working. A new research associate has joined the team. Chase and I were out in the Cuyama Valley and Carrizo National Monument.  I was hoping to share with him some wisdom, hang out, survey some plots, and check on everything. The best thing about this pic however is that I am missing my quadrat (and my wisdom). I am looking back to Chase for about the tenth time hoping he picked up mine in addition to his own.


I never had to pick up his quadrat.
I also managed to lead us down the wrong dirt road once (only 12 miles), and in another instance, I was positive that this particular slope was the correct one and we ended up on a very pretty but extended detour.

zen mind, beginner’s mind