clique – Pertinent Observations

When I’m visiting someone’s house and they have an accessible bookshelf, one of the things I do is to go check out the books they have. There is no particular motivation, but it’s just become a habit. Sometimes it serves as conversation starters (or digressors). Sometimes it helps me understand them better. Most of the time it’s just entertaining.

So at a friend’s party last night, I found this book on Graph Theory. I just asked my hosts whose book it was, got the answer and put it back.

As many of you know, whenever we host a party, we use graph theory to prepare the guest list. My learning from last night’s party, though, is that you should not only use graph theory to decide WHO to invite, but also to adjust the times you tell people so that the party has the best outcome possible for most people.

With the full benefit of hindsight, the social network at last night’s party looked approximately like this. Rather, this is my interpretation of the social network based on my knowledge of people’s affiliation networks.

This is approximate, and I’ve collapsed each family to one dot. Basically it was one very large clique, and two or three other families (I told you this was approximate) who were largely only known to the hosts. We were one of the families that were not part of the large clique.

This was not the first such party I was attending, btw. I remember this other party from 2018 or so which was almost identical in terms of the social network – one very large clique, and then a handful of families only known to the hosts. In fact, as it happens, the large clique from the 2018 party and from yesterday’s party were from the same affiliation network, but that is only a coincidence.

Thinking about it, we ended up rather enjoying ourselves at last night’s party. I remember getting comfortable fairly quickly, and that mood carrying on through the evening. Conversations were mostly fun, and I found myself connecting adequately with most other guests. There was no need to get drunk. As we drove back peacefully in the night, my wife and daughter echoed my sentiments about the party – they had enjoyed themselves as well.

This was in marked contrast with the 2018 party with the largely similar social network structure (and dominant affiliation network). There we had found ourselves rather disconnected, unable to make conversation with anyone. Again, all three of us had felt similarly. So what was different yesterday compared to the 2018 party?

I think it had to do with the order of arrival. Yesterday, we were the second family to arrive at the party, and from a strict affiliation group perspective, the family that had preceded us at the party wasn’t part of the large clique affiliation network (though they knew most of the clique from beforehand). In that sense, we started the party on an equal footing – us, the hosts and this other family, with no subgroup dominating.

The conversation had already started flowing among the adults (the kids were in a separate room) when the next set of guests (some of them from the large clique arrived), and the assimilation was seamless. Soon everyone else arrived as well.

The point I’m trying to make here is that because the non-large-clique guests had arrived first, they had had a chance to settle into the party before the clique came in. This meant that they (non-clique) had had a chance to settle down without letting the party get too cliquey. That worked out brilliantly.

In contrast, in the 2018 party, we had ended up going rather late which meant that the clique was already in action, and a lot of the conversation had been clique-specific. This meant that we had struggled to fit in and never really settled, and just went through the motions and returned.

I’m reminded of another party WE had hosted back in 2012, where there was a large clique and a small clique. The small clique had arrived first, and by the theory in this post, should have assimilated well into the party. However, as the large clique came in, the small clique had sort of ended up withdrawing into itself, and I remember having had to make an effort to balance the conversation between all guests, and it not being particularly stress-free for me.

The difference there was that there were TWO cliques with me as cut-vertex. Yesterday, if you took out the hosts (cut-vertex), you would largely have one large clique and a few isolated nodes. And the isolated nodes coming in first meant they assimilated both with one another and with the party overall, and the party went well!

And now that I’ve figured out this principle, I might break my head further at the next party I host – in terms of what time I tell to different guests!

Last evening we hosted a party at home. Like all parties we host, we used Graph Theory to plan this one. This time, however, we used graph theory in a very different way to how we normally use it – our intent was to avoid large cliques. And, looking back, I think it worked.

First, some back story. For some 3-4 months now we’ve been planning to have a party at home. There has been no real occasion accompanying it – we’ve just wanted to have a party for the heck of it, and to meet a few people.

The moment we started planning, my wife declared “you are the relatively more extrovert among the two of us, so organising this is your responsibility”. I duly put NED. She even wrote a newsletter about it.

The gamechanger was this podcast episode I listened to last month.

The episode, like a lot of podcast episodes, is related to this book that the guest has written. Something went off in my head as I listened to this episode on my way to work one day.

The biggest “bingo” moment was that this was going to be a strictly 2-hour party (well, we did 2.5 hours last night). In other words, “limited liability”!!

One of my biggest issues about having parties at my house is that sometimes guests tend to linger on, and there is no “defined end time”. For someone with limited social skills, this can be far more important than you think.

The next bingo was that this would be a “cocktail” party (meaning, no main course food). Again that massively brought down the cost of hosting – no planning menus, no messy food that would make the floor dirty, no hassles of cleaning up, and (most importantly) you could stick to your 2 / 2.5 hour limit without any “blockers”.

Listen to the whole episode. There are other tips and tricks, some of which I had internalised ahead of yesterday’s party. And then came the matter of the guest list.

I’ve always used graph theory (coincidentally my favourite subject from my undergrad) while planning parties. Typical use cases have been to ensure that the graph is connected (everyone knows at least one other person) and that there are no “cut vertices” (you don’t want the graph to get disconnected if one person doesn’t turn up).

This time we used it in another way – we wanted the graph to be connected but not too connected! The idea was that if there are small groups of guests who know each other too well, then they will spend the entirety of the party hanging out with each other, and not add value to the rest of the group.

Related to this was the fact that we had pre-decided that this party is not going to be a one-off, and we will host regularly. This made it easier to leave out people – we could always invite them the next time. Again, it is important that the party was “occasion-less” – if it is a birthday party or graduation party or wedding party or some such, people might feel offended that you left them out. Here, because we know we are going to do this regularly, we know “everyone’s number will come sometime”.

I remember the day we make the guest list. “If we invite X and Y, we cannot invite Z since she knows both X and Y too well”. “OK let’s leave out Z then”. “Take this guy’s name off the list, else there will be too many people from this hostel”. “I’ve met these two together several times, so we can call exactly one of them”. And so on.

With the benefit of hindsight, it went well. Everyone who said they will turn up turned up. There were fourteen adults (including us), which meant that there were at least three groups of conversation at any point in time – the “anti two pizza rule” I’ve written about. So a lot of people spoke to a lot of other people, and it was easy to move across groups.

I had promised to serve wine and kODbaLe, and kept it – kODbaLe is a fantastic party food in that it is large enough that you don’t eat too many in the course of an evening, and it doesn’t mess up your fingers. So no need of plates, and very little use of tissues. The wine was served in paper cups.

I wasn’t very good at keeping up timelines – maybe I drank too much wine. The party was supposed to end at 7:30, but it was 7:45 when I banged a spoon on a plate to get everyone’s attention and inform them that the party was over. In another ten minutes, everyone had left.