Frances Bell

home at last – for all the mes


Acknowledging and Making Women More Visible on Social Media Platforms – It’s Complicated

Two Women Hugging – Photo by Matthew Henry on Unsplash

In recent days, there has been a trend (not sure if it’s a meme) going around where a tweeter names 10 women to thank and asks others to pass it on, for example

Maren was delighted to see #femedtech people being celebrated, as was I

It’s such a beautiful thing that people acknowledge women’s work, and help make them and their work more visible when so often it is ignored and even erased.  I was really touched by people including me in their lists.  Social media is excellent for networking and connecting people and the human aspect of this meme is lovely.

Can you sense a but coming?


Women’s work is being celebrated by men and women on the Twitter platform that enables the meme to spread within networks and enables people to make new connections as they click on the profiles of those women they encounter. As the meme spreads, those connected to it experience effects that stem largely from Twitter’s algorithms and from the defaults that it has chosen to apply.  The format of the meme Tweet includes at least 11 Twitter ids, and if anyone interacts (replying or liking) all of those will receive notifications.

*But* does it need to be like this? When using email, we have the choice of reply or reply all to a group email. On Twitter threads like these, we have to individually de-select each of the 10 plus recipients if we just want to reply to the person who was kind enough to include us in their meme tweet. If we like the post (as basic gratitude), all mentioned will receive a notification, and we have no option to exclude the other 9 people from the like notification.

And what could be different?

Twitter could default to replying only to the person who posted the meme tweet (or any tweet mentioning it). And like notifications could default to poster only.

I started by liking posts that I was mentioned in, then stopped as I saw the effect of others doing this. My notifications were flooded. I began to think about why this was so and what could be different?

I re-read a really interesting paper where Funes and Mackness(2018) explore how efforts to include can also exclude.  Funes and Mackness answered their own hypothetical question

“Are you saying that just because an aspiration to include sometimes excludes we should not be inclusive?

We have argued for no more than awareness that the actions we take to include have an exclusionary element when enacted on the internet because of the nature of the medium.”(Funes and Mackness 2018)

What I am arguing for here is an increased awareness of not only the impacts of human actions, but also the impacts of algorithms and default settings, in an exploration of how things could be different.

Highlighting the work done by women can work well, for example on #femedtech and by @femedtech (that in itself includes by having rotating curators) where specific examples of women’s work is shared, usually including woman’s Twitter id on an individual basis. The form that drives the meme socially across the network, when combined with the choice of algorithms and defaults by Twitter make for a different experience from individual sharing.

Algorithms are generally opaque but it’s interesting to think about why Twitter makes the algorithmic and default setting decisions it does, or indeed how memes emerge. For me, this meme has something in common with the #FF Follow Friday meme. I have written elsewhere about Snowball threads that also have similarities to the meme discussed here.

So how might Twitter benefit from this recent meme? In 2018, Twitter earned 86% of its revenue from advertising, and 14% from data licensing and other sources. Twitter sells subscriptions to public data beyond its public API to other companies and developers who can then “access, search and analyze historical and real-time data” on the platform, How Does Twitter Make Money?

Without knowing the detail of Twitter’s selling of advertising/data subscription services, I am thinking that increased traffic will be one of the quantitative measures that helps sell those services. And this meme may generate data that can identify/verify the gender of the sets of ‘10 women’ appearing in meme occurrences.

It is complicated but also can be annoying for those mentioned in the increased traffic 🙂


Funes, M. and Mackness, J. (2018) ‘When Inclusion Excludes: a counter narrative of open online education’, Learning, Media & Technology, 43(2), pp. 119–138. Available at: .


francesbell • November 13, 2019

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  1. Kevin Hodgson November 13, 2019 - 9:35 pm Reply

    This, what you wrote, is important and worth surfacing: “What I am arguing for here is an increased awareness of not only the impacts of human actions, but also the impacts of algorithms and default settings, in an exploration of how things could be different.”
    The complicated nature of being on a platform being monetized by a profit company is always an uncomfortable fit, I think, and then to realize that at times, you have little agency or control over your own identity and presence in that space (inadvertent or not) causes one to pause, step back and re-evaluate.
    You focused on the reply format (valid points) but I was thinking of visibility.
    Thank you, Frances, for your post and for Wendy, for guiding me here to it. (Perhaps this is the reverse effect — the powerful positives of having something found, passed along and read with an impact).
    Your friend across networks and time,

  2. Frances Bell November 13, 2019 - 10:26 pm Reply

    And you too, Kevin are my friend across networks and time 🙂 I watch what I see of what you do with interest and I often think of your comments about Facebook and the like at Rhizo14. That’s an interesting point you make about me mentioning the reply format and I agree about your concerns about visibility. I agree – I just wasn’t addressing the visibility in the stream issues in this post 🙂 Though, we did address the issue of (in)visibility within algorithmic streams in this paper “In Rhizo14, groups of learners who only participated on
    one platform could become invisible to other groups participating in different
    platforms and within Facebook itself posts that were not engaged with by the most
    active participants disappeared to the bottom of the stream supported by the
    Facebook algorithm.”
    Thanks for calling in and enriching the post.

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