A few days ago I took a look at my LinkedIn data, and realised while writing it that I exported my Facebook data in the fall of 2017 when I first strongly reduced and then later closed and deleted my original October 2006 account (I do keep a new account with limited interaction and much fewer contacts). The Facebook data also has a list of contacts with the date they became a contact.

From that export I therefore created the same data I did for LinkedIn: the number of added contacts per year and its gender balance, and the cumulative number of contacts and its gender balance. This in response to Rick Klau’s description of his ‘do-it-yourself contact management‘ Between 1 October 2006 and 30 October 2017 I added some 650 people on FB, of which 161 women (25%)
Those numbers are even more out of balance than with LinkedIn, although in recent years it improved in much the same way per year as on LinkedIn, though it comes out slightly below LinkedIn for the total. I suspect for Facebook a social aspect is in play more than on LinkedIn: for a larger social distance I suspect it is socially more likely I’d add a male contact. To test that I would need to arrange the contacts by my perceived social distance, which is an interesting experiment for another moment.


cummulative per year


new contacts added per year

I’ve held for a long time that whenever someone says “we’d like to hire women but we don’t know any” or “we really want women as speakers on our event but we don’t know any and if we do they say no”, it is really down to the lack of quality and balance in their network of contacts. When I organised international conferences myself, with our team we made sure to invite speakers while conscious of the lopsidedness of our own networks, overcompensating in our invitations to get a result closer to a 50/50 balance. Now that my company is hiring new people every now and then, that too is an opportunity to counteract such imbalance.

Last week I wrote about ‘homebrew CRM‘, in which I mentioned Rick Klau’s post on his contact management routines. One element that jumped out when I was reading his post was that he had taken a look at his contact lists to see how the men/women ratio was in his network. There’s nothing in LinkedIn that let’s you explore your contact list as a single data set. It’s only a rolodex still, no way to visualise the data in that list in any way (e.g. geographic or sectoral distribution, or other cross sections of the list). Rick mentioned he had downloaded all his LinkedIn data and all his Twitter data, and then used that data export to work on. I requested the same data from LinkedIn and Twitter.

It turns out that LinkedIn’s export contains a list of contact names (but not the link to their profiles, as that isn’t ‘your data’), and a key piece of information they normally don’t show you: the date you connected. (Interestingly LinkedIn offers you nothing to record the context and reason you connected. The Xing-platform, heavily used in Germany, does do that, and I find it very useful)

Having names and dates, I manually indicated someone’s gender, and then used the dates for basic insights into how my recorded network developed over time. (Typing this I realise I still have the export from Facebook when I deleted my original account 2 years ago, and I could do the same there)

For now I looked at two measures: the balance between women and men in contacts I added each year, and the balance between women and men in the total number of contacts each year. Currently I have some 2150 contacts, of which some 600 are women, for a percentage of 27%. That is significantly lower than I had intuited. I think such overestimation is a known effect.

Looked at per year for the contacts added that year, the balance over time has improved from 10% in 2003, to between a third and 40% in the last handful of years. That last number is in line with the overall percentage I had intuited, so apparently I am using my perception of recent years as the estimate for the entire period. That low 2003 starting percentage has a lot to do I think with the general imbalance of the early adopter crowd that came into LinkedIn when they launched in May 2003 (I joined in June ’03) and the low number of people I connected to those first months on the platform (11 in 6 months).

Getting closer to a 50/50 balance on LinkedIn isn’t completely within my control I realise (unlike in my feed reading), as it also depends on who I actually meet in my work, and each working environment has its own existing gender distribution. It is also not completely outside my control. There is agency in new situations and contexts, such as whom I seek out for conversation when participating in an event. Yet, getting to a 50/50 balance for the total would mean connecting only to women for a few years, adding about a 1000 new contacts that way. History does keep one back clearly.

cummulative per year

new contacts added per year

Through a posting of Roel I came across Rick Klau again, someone who like me was blogging about knowledge management in the early ’00s. These days his writing is on Medium it seems.

Browsing through his latest posts, I came across this one about homebrew contact management.

Contact management is one area where until now I mostly stayed away from automating anything.
First and foremost because of the by definition poor initial data quality that you use to set it up (I still have 11 yr old contact info on my phone because it is hard to delete, and then gets put back due to some odd feedback loop in syncing).
Second, because of the risk of instrumentalising the relationships to others, instead of interacting for its own sake.
Third, because most systems I encountered depend on letting all your mail etc flow through it, which is a type of centralisation / single point of failure I want to avoid.

There’s much in Rick’s post to like (even though I doubt I’d want to shell out $1k/yr to do the same), and there are things in there I definitely think useful. He’s right when he says that being able to have a better overview of your network in terms of gender, location, diversity, background etc. is valuable. Not just in terms of contacts, but in terms of information filtering when you follow your contacts in several platforms etc.

Bookmarked to come up with an experiment. Timely also because I just decided to create a simple tool for my company as well, to start mapping stakeholders we encounter. In Copenhagen last September I noticed someone using a 4 question page on her phone to quickly capture she met me, the context and my organisation. When I asked she said it was to have an overview of the types of organisations and roles of people she encountered in her work, building a map as it were of the ecosystem. Definitely something I see the use of.

HandShakeHandshakes and conversations is what I’m interested in, not marketing instruments. Image Handshake by Elisha Project, license CC BY SA

Today, my ‘on this day in …’ widget tells me it is 16 years ago that I triggered what turned out to be the most pivotal discussion my blog generated, the Making Actionable Sense conversation. It became a key building block of Lilia‘s PhD, and the subject of network visualisation research. It shaped my own thinking about the funnel of information input, through processing, to getting to action, and how being deliberately and consciously networked feeds into agency.

Attended a very good conversation with Audrey Tang (唐凤), Taiwan’s digital minister.

20191120_121824

There are many nuggets still to mine from the notes. On the SDG’s and radical transparency for instance.

One thing, because I could find it in full online, is the poem as job description, the minister recited early on in the conversation:

When we see “internet of things”, let’s make it an internet of beings.
When we see “virtual reality”, let’s make it a shared reality.
When we see “machine learning”, let’s make it collaborative learning.
When we see “user experience”, let’s make it about human experience.
When we hear “the singularity is near”, let us remember: the Plurality is here.

There’s much to like in those lines. It almost reads like a concise version of the tech pledge.