Here I am in bed finally with a Hulu trial and happily starting to binge watch the last season of The Mindy Project. I have been watching this show since day one, and even though I’m sad that it’s ending, I feel good knowing it’s not the end to come from Mindy Kaling. Plus, this season takes on a lot of great references from today’s events!
Girlfriend, that glass of wine is totally worth it, but now let’s add a show to it. It’s time to take a few hours off to yourself with a show! Here I am 3 episodes in, fully committed, and happy to know that this is the only thing my mind can deal with. I’m not thinking about tomorrow’s workload, or what I’m going to have for lunch — that’s a thing.
Your mind deserves a time-out away from solving algorithms — the world, throwing boss meetings and feeding your neighbor’s cat. Laughter is medicine, and so is TV. I like to indulge in romantic comedies, with a strong female role! Love is real, but I love myself first so I binge-watch.
Alright, let’s wrap up this post before the last advertisement ends #noshame. Now find yourself a show to unwind with for the next 30 mins or 3 hours! Bake yourself a cake like I did, eat half of it without a guilt, and unwind /!
What’s in your queue? I’d love to hear your picks!
This came up in a recent comment thread, and I decided it was interesting enough to post on. What’s the demographic profile of our commenters? How diverse are they, compared to our readership? And do the demographics of people who comment about our posts on Twitter differ from the demographics of the people who comment here? If so, is there any sign that that’s because some groups of people (students? women? people who disagree with our posts?) are more comfortable commenting on Twitter than in our comment threads?
Attention conservation notice: navel-gazing post, probably of greatest interest to other bloggers.
Last month, I went back through the most recent 200 non-trackback comments by someone other than Meghan, Brian, or me, and compiled the following data: commenter gender (m/f; evaluated by name, and photo if available; a gender binary is not ideal but the best I can do), employment (grad student, postdoc, prof, other; ID’d by googling), country (ID’d by geolocating IP addresses), and total number of comments ever made (all time, not just within the most recent 200 comments). Then, because those 200 comments didn’t cover any posts by Meghan, or any posts on gender and equity issues, I also went back and compiled the same data for all the commenters on Meghan’s 10 most recent posts, and for 5 recent-ish posts on gender and equity issues. Two of those 5 were by Meghan and were among her 10 recent posts; 2 were by me and 1 was by guest poster Gina Baucom. Finally, earlier this month, I went through our Twitter notifications and did some searches (to look for subtweets), and compiled data on the gender and employment of the most recent 51 people to discuss our posts on Twitter. I didn’t count anyone who merely rephrased the post title or main conclusion along with tweeting a link to the post, but I did count all other comments even if they were quite brief (brief for tweets, I mean). Those 51 people’s tweets about our posts were made from Dec. 8, 2017 – Jan. 9, 2018, so overlapped a lot in time with the most recent 200 comment data.
For reference, here’s a demographic profile of our regular readers, from a reader survey we did last year that got almost 400 responses:
- 32% grad students, 26% postdocs, 26% faculty, 16% other.
- 58% men, 42% women, <1% non-binary or not disclosed.
- 50% from the US, 10% Canada, 7% UK, rest from elsewhere. That matches where our pageviews come from, so our survey respondents were geographically representative of all readers.
Demographics of the commenters who made 200 recent comments:
- 54 commenters
- 67% of those 54 were men, 26% women, remainder unknown gender
- 17% grad students, 13% postdocs, 37% profs (the majority of them senior profs), 19% other or unknown. Aside: from context, I suspect several of the unknowns are grad students.
- 44% US, 15% Canada, 9% UK, remainder from elsewhere
- Most of these 54 commenters have only ever commented once. The 7 all-time most active commenters among these 54 are all men, 6/7 are profs, and 2/7 have their own blogs.
Demographics of the commenters on 10 recent posts by Meghan:
- 47 commenters, most of whom commented on only 1 of the 10 posts
- 57% men, 32% women, 11% unknown
- 11% grad students, 13% postdocs, 42% profs, the remainder other or unidentified
- 60% US, 15% Canada, remainder from elsewhere
Demographics of the commenters on 5 recent posts on gender and equity issues:
- 60 commenters
- 45% women, 42% men, remainder unknown
- 12% grad students, 8% postdocs, 23% profs, remainder unidentified or other
- 72% US, 8% Australia, 7% Canada, remainder from elsewhere
Demographics of people who’ve recently discussed our posts on Twitter:
- 51 people or organizations
- 61% men, 35% women, 4% organizations
- 9% grad students, 27% postdocs, 45% profs, 14% other or unknown employment, 4% organizations
Summary and comments:
- The overall picture is that the demography of our commenters skews a bit more male than our readership (which itself skews a bit male), and substantially more senior than our readership.
- Commenter demography changes when there’s a strong correlation between interest in the post topic and some dimension of commenter demography. Posts on gender and equity issues draw a more gender-balanced and US-skewed mix of commenters compared to posts on other topics (not mostly women, though, contrary to some speculation in the comment thread linked to at the beginning of this post). As another (anecdotal) example, it looks like our recent series of guest posts on doing ecology in developing countries had an unusually high proportion of commenters from developing countries.
- That posts on gender and equity issues draw a very US-skewed commentariat is the only surprise in this dataset for me. Curious to hear thoughts on this, especially from non-US readers, and from folks who participate in or follow online discussions of gender and equity issues in other venues.
- The identity of the post author doesn’t affect the demographic mix of our commenters. It’s post topic that matters, not who wrote the post. This lines up with our anecdotal experience and survey data. Meghan, Brian, and I all have had the experience of being complimented for a post someone else wrote; some readers don’t notice who writes which post. And from survey data, we know that very few of our readers have favorite post authors, as opposed to favorite topics.
- Most commenters only ever comment once or twice. If you weighted commenters by the number of comments they leave, you’d increase the skew towards male profs a bit, because our most active repeat commenters are mostly male profs. But this additional skew wouldn’t be huge, because no one commenter makes more than a few percent of all our comments.
- Twitter commenters are not more diverse on the dimensions considered than people who comment here, contrary to a (plausible!) hypothesis proposed by some commenters in that old comment thread linked to at the start of the post. Indeed, if anything it looks like Twitter commenters might skew even a bit more senior than commenters here. I didn’t quantify geographic diversity of our Twitter commenters, but offhand it looked roughly similar to that of our commenters here.
- I didn’t quantify this, but just anecdotally the vast majority of Twitter comments about our posts were positive–expressing agreement with the post, and/or adding additional thoughts. The majority of the small number of people disagreeing with our posts on Twitter were male profs. This is a very small sample of disagreement, obviously, so I wouldn’t make much of it. But for what little it’s worth, I don’t see any hint that Twitter commenters are more likely than our commenters to disagree with our posts (which as an aside is slightly contrary to what I’d have expected). And I don’t see any hint that Twitter commenters who disagree with our posts differ demographically from all Twitter commenters on our posts, or from our commenters here.
- I have no idea about the demography of people who share and/or discuss our posts on Facebook.
- The demographics of people who retweet and/or like us on Twitter, without commenting, might well differ from those of our Twitter commenters. Or not; I don’t know.
- The data on our Twitter commenters didn’t cover a time period in which we posted about gender and equity issues. I suspect that if it had, we’d have found less male skew, or maybe even gender balance or a skew towards women.
- The sample sizes here are modest, so keep that in mind. But I don’t see any reason to think that these samples are massively unrepresentative.
- We love our commenters, they’re fantastic, we enjoy their comments and learn a lot from them. We wish we had even more and more diverse commenters, but I’m not sure there’s much we can do to encourage that beyond what we already do (moderating comments, treating commenters respectfully, blocking the IP address of anyone who makes really inappropriate comments, etc.). There’s no evidence that we’d increase the diversity of our commenters by switching all discussion of our posts to Twitter (and no one’s suggested we should). Further, we know from reader surveys, and from anecdotal evidence, that people’s reasons for not commenting are mostly beyond our control. Many readers don’t feel they have anything to add. Many have a policy never to write anything on the internet. Some find it a pain to type on their phones. Some prefer Twitter to blog comment threads, for various reasons. Etc. Probably the only thing we could do to attract a different mix of commenters is post on a different mix of topics. But we’re not perfect, and so we welcome suggestions on how we can encourage a large and diverse commentariat.
- The demographic mix of our blog commenters, and the very similar demographic mix of people who comment on our posts on Twitter, might well not match the demographic mix of people with whom any particular Twitter user exchanges tweets most often. “People who comment on Dynamic Ecology posts on Twitter” probably comprise a non-random subset of all Twitter users, and of all Twitter users with whom any given Twitter user exchanges tweets regularly.
- I don’t know if these results generalize to other blogs.
- Let me conclude by thanking the many folks who participated in the excellent comment thread linked to at the start of this post for raising some important and interesting questions and inspiring me to compile some data addressing them.