Networking events and positions of strength

This replicates some of the stuff I wrote in a recent blog post, but I put this on LinkedIn and wanted a copy here for posterity 

Having moved my consulting business to London earlier this year, I’ve had a problem with marketing. The basic problem is that while my network and brand is fairly strong in India, I’ve had to start from scratch in the UK.

The lack of branding has meant that I have often had to talk or negotiate from a position of weakness (check out my recent blog post on branding as creating a position of strength). The lack of network has meant that I try to go to networking events where I can meet people and try to improve my network. Except that the lack of branding means that I have to network from a position of weakness and hence not make an impact.

A few months back I came across this set of tweets by AngelList founder Naval Ravikant, in which he talked about productivity hacks.

One that caught my eye, which I try to practice but have not always been able to practice, is on not going to conferences if you are not speaking. However, now that I think about it from the point of view of branding and positions of strength, what he says makes total sense.

In conferences and networking events, there is usually a sort of unspoken hierarchy, where speakers are generally “superior” to those in the audience. This flows from the assumption that the audience has come to gather pearls of wisdom from the speakers. And this has an impact on the networking around the event – if you are speaking, people will start with the prior of your being a superior being, compared to you going as an audience member (especially if it is a paid event).

This is not a strict rule – when there are other people at the event who you know, it is possible that their introductions can elevate you even if you are not speaking. However, if you are at an event where you don’t know anyone else, you surely start on higher ground (no pun intended) in case you are speaking.

There is another advantage that speaking offers – you can use your speech itself to build your brand, which will be fresh in your counterparties’s minds in the networking immediately afterward. Audience members have no such brand-building ability, apart from the possibility of tarnishing their own brands through inappropriate or rambling questions.

So unless you see value in what the speaker(s) say, don’t go to conferences. Putting it another way, don’t go to conferences for networking alone, unless you are speaking. Extending this, don’t go to networking events unless you either know some of the other people who are coming there (whose links you can then tap) or if there is an opportunity for you to elevate your brand at the event (by speaking, for example).

PS: Some of Naval’s other points such as having “meeting days” and scheduling meetings for later in the day are pertinent as well, and I’ve found them to be incredibly useful.

Taking sides on twitter

Garry Kasparov versus Nassim Nicholas Taleb
Joe Weisenthal versus Balaji Srinivasan

These are two twitter battles that have raged (ok the latter is muted in comparison) on my timeline during the last few days. I’ve been witness to these battles because I follow all of these worthies, who are each interesting for their own reason. But I don’t like these battles, and fights, and I find that apart from quickly scrolling through my timeline, there is no way for me to ignore these battles.

I find all four of these people independently interesting, and so don’t want to unfollow any of them just for the sake of avoiding being witness to these fights. But in due course of time, if any of them were to focus excessively on these fights (which is unlikely to happen) at the cost of other interesting tweets, I’m likely to unfollow.

These episodes, however, have given me an insight into why there is some sort of a political division in twitter following – that people who follow a set of argumentative people with one set of beliefs are unlikely to follow members from another set with the opposite kind of beliefs. This is because if you follow argumentative people from both sides, you end up getting caught in their argument which can contaminate your timeline.

You tolerate it for a while, but then over time you start losing patience. And you realise that the only way of avoiding following these arguments is by unfollowing, or even muting, people from one side of the argument. It is more likely that you unfollow the people whose beliefs agree with less. And you do this a sufficient number of times, and you’ll end up only following people whose beliefs you fully agree with.

And then they say social media is an echo chamber!

Anyway, the moral of the story for me is that I shouldn’t engage in protracted flamewars on twitter, for each time I do, I run the risk of losing followers who might also be following my counterparty in such flame wars.

Why Twitter is like Times Now

One reason I stopped watching news television about a decade back is because of its evolution into a “one issue channel”. On each day, a channel basically picks a “topic of the day”, and most discussion on that day is regarding that particular topic.

In that sense, these “news channels” hardly provide news (unless you bother to follow the tickers at the bottom) – they only provide more and more discussion about the topic du jour (ok I’m feeling all pseud about using French on my blog!). If you’re interested in that topic, and willing to consume endless content about it, great for you. If not, you better look for your news elsewhere (like the <whatever> o’clock news on the government-owned channel which at least makes a pretence of covering all relevant stuff).

One thing that made Twitter attractive soon after I joined it in 2008 was the diversity of discussions. Maybe it was the nature of the early users, but the people I followed provoked thought and provided content on a wide array of topics, at least some of which I would find interesting. And that made spending time on twitter worthwhile.

It’s still true on a lot of days nowadays, but I find that Twitter is increasingly becoming like a modern news channel such as Times Now. When there are certain events, especially of a political nature, it effectively becomes a one-topic channel, with most of the timeline getting filled with news and opinion about the event. And if it is either an event you don’t care about, or if you’ve moved on from the event, Twitter effectively becomes unusable on such days.

In fact, a few of my twitter breaks in the last 2-3 years have followed such periods when Twitter has turned into a “one issue channel”. And on each of these occasions, when I’ve joined back, I’ve responded by unfollowing many of these “one-issue tweeters” (like this guy who I don’t follow any more because he has a compulsive need to livetweet any game that Arsenal is playing).

That Twitter becomes a one-topic channel occasionally is not surprising. Basically it goes like this – there are people who are deeply passionate or involved in the topic, and they show their passion by putting out lots of tweets on the topic. And when the topic is a current event, it means that several people on your timeline might feel passionately about it.

People not interested in the topic will continue to tweet at their “usual rate”, but that gets effectively drowned out in the din of the passionate tweeters. And when you look at your linear timeline, you only see the passion, and not the diverse content that you use Twitter for.

Some people might suggest a curated algorithmic feed (rather than a linear feed) as a solution for this – where a smart algorithm learns that you’re not interested in the topic people are so passionate about and shows you less of that stuff. I have a simpler solution.

Basically the reason I’m loathe to unfollow these passionate tweeters is that outside of their temporary passions, they are terrific people and tweet about interesting stuff (else I wouldn’t follow them in the first place). The cost of this, however, is that I have to endure their passions, which I frequently have no interest in.

The simple solution is that you should be able to “temporarily unfollow” people (Twitter itself doesn’t need to allow this option – a third party client that you use can offer this at a higher layer). This is like WhatsApp where you can mute groups for just a day, or a week. So you can unfollow these passionate people for a day, by which time their passion will subside, and you can see their interesting selves tomorrow!

Of course it’s possible to manually implement this, but I know that if I unfollow them today I might forget to follow them back tomorrow. And there are countless examples of people in that category – who I unfollowed when they were passionate and have thus missed out on their awesomeness.


The Birthday Party Problem

Next Tuesday is my happy birthday. As of now, I’m not planning to have a party. And based on some deep graph theoretic analysis that the wife and I just did over the last hour, it’s unlikely I will – for forming a coherent set of people to invite is an NP-hard problem, it seems like.

So five birthdays back we had a party, organised by the wife and meant as a surprise to me. On all counts it seemed like a great party. Except that the guests decided to divide themselves into one large clique and one smaller clique (of 2 people), leaving me as the cut vertex trying to bridge these cliques. That meant the onus was on me to make sure the tiny clique felt included in the party, and it wasn’t a lot of fun.

The problem is this – how do you invite a subset of friends for a party so that intervention by the host to keep guests entertained is minimised?

Let’s try and model this. Assume your friends network can be represented by an unweighted undirected graph, with a pair of friends being connected by an edge if they know (and get along with) each other already. Also assume you have full information about this graph (not always necessary).

The problem lies in selecting a subgraph of this graph such that you can be confident that it won’t break into smaller pieces (since that will mean you bonding with each such sub-group), and no guest feels left out (since the onus of making them comfortable will fall on you).


Firstly, the subgraph needs to be connected. Then, we can safely eliminate all guests who have degree of either zero or one (former is obvious, latter since they’ll be too needy on their only friend). In fact, we can impose a condition that each guest should have a minimum degree of two even in the subgraph.

Then we need to impose conditions on a group in the party breaking away. We can assume that for a group of people to break away, they need to be a clique (it is not a robust requirement, since you and someone you find at a party can suddenly decide to find a room, but reasonable enough).

We can also assume that for a group to break away, the strength of their mutual connections should outweigh the strength of their connections to the rest of the group. Since we’re using unweighted graphs here, we can simply assume that a group can break away if the number of edges between this group and the rest of the network is less than the size of the group.

So if there is a group of three who, put together, have two connections to the rest of the group, the group can break away. Similarly, a clique of four will break away from the main group if they have three or less edges going over. And let’s assume that the host is not a part of this subgroup of guests.

Given these constraints, and constraints on party size (minimum and maximum number of guests to invite), how can we identify an appropriate subset of friends to invite for the party? And I’m assuming this problem is NP-Hard (without thinking too much about it) – so can we think of a good heuristic to solve this problem

Do let me know the answer before next Tuesday, else I may not be able to have a party this time as well!

Evaluating WhatsApp groups

Over time I’ve come to become a member of several WhatsApp groups. Some of them are temporary, designed to simply coordinate on a particular one-off event. Others are more permanent, existing over a long term, but with no particular agenda.

Over this time I’ve also exited several WhatsApp groups, especially those that have gotten a bit annoying. I remember this day last year when I stepped in and out of a meeting, and I found a hundred messages on a family WhatsApp group, most of them being random forwards, and a few of them being over a page long. I quickly exited that group.

Not everyone quickly exits groups they don’t like, though. There is social pressure to remain, since anyone’s exit gets publicly broadcast in the group. Being a member of a WhatsApp group is the latest measure of conformity, and irrespective of how annoying some groups are, one is forced to endure.

Not all WhatsApp groups are annoying, though. Some groups I’m a member of are an absolute joy. There are times when I explicitly choose to initiate a conversation within the group, than bilaterally, so that others in the group can pitch in. And this taking of the conversation to the group is usually not minded by the intended counterparty as well.

Thinking about good and bad WhatsApp groups, I was wondering if there is a good and clean metric to determine how “good” or “useful” a WhatsApp group might be. Based on my experience, I have one idea. Do let me know if you know a better way to characterise whether a WhatsApp group is going to be good or bad.

When you have a WhatsApp group with N people, you are essentially bringing together N * (N-1)/2 pairs of people. Now, some of these pairs might get along fantastically well. Other pairs might loath each other. And yet others are indifferent to each other.

My hypothesis is that the more the number of pairs in a group that like to talk to each other, the better the group functions (yes it’s a rather simple metric).

Now, this hypothesis is rather simplistic – for example, you can have threesomes of people whose mutual relationship is very different from that of any pair taken together. So this ignores a higher order correlation term, but improves simplicity. It’s like that benzene ring, where six carbon atoms bond together in a way no two of them as a pair can (forget the scientific term for such bonding)!

Yet, what we have here is a good measure of cohesion within the group. It also explains why sometimes the addition of a single member can lead to the destruction of the group – for it can increase the proportion of people who don’t like to talk to each other!

The model is incomplete, though. For now, it doesn’t differentiate between “don’t care conditions” (people in the group who are indifferent to each other) and “don’t get alongs”. If we can incorporate that without making the formula more complex, I think we might be up to something.

Maybe we should form a WhatsApp group to discuss what a good formula might look like!

InMails and the LinkedIn backfire

A few months back I cleaned up my connections list on LinkedIn. Basically I removed people who I don’t “know”. I defined “know” as knowing someone well enough to connect them to someone else on my network (the trigger for a cleanup was when someone asked me to connect them to someone else on my network who I hardly knew).

The interesting thing about the cleanup was that a lot of the spurious connections I had on LinkedIn were headhunters. Thinking back at how they got in touch with me, in most cases it was with respect to a specific opportunity for which they were finding candidates. Once the specific opportunity had been discussed there was no value of us being connected on LinkedIn, and were effectively deadweight on each other’s networks.

Over the last couple of days, ever since I wrote this piece for Mint on valuation of startup ratchets, I’ve got several connection requests, all from people I don’t know. Normally I wouldn’t accept these invitations, but what is different is that most requests have come with non-standard messages attached. Most have mentioned that they liked my Mint piece and so want to either connect or discuss it.

When you want to simply exchange messages with someone, there is no need to really add them as a “friend”. Except that LinkedIn’s pricing policy makes this kind of behaviour rational.

LinkedIn offers a small number of “InMails” which you can send to people who you aren’t directly connected to. Beyond this number, each InMail costs you money. So if you want to have a discussion with someone you’re not connected with, there’s an element on friction.

There’s a loophole, however. You can send messages for free as long as they go along with a connection request. And if that request is accepted, then you can have a “free” conversation with that person.

So given the current price structure, if you want to have a conversation with someone, you simply send your initial message as part of a friend request. If the person wants to continue the conversation, the request will get accepted. If not you haven’t lost anything!

Then again, there are mitigating features – an InMail won’t get charged unless there is a reply, and LinkedIn’s UI is so bad that it takes effort to read messages attached to connection requests. So this method is not foolproof.

Still, it appears that LinkedIn’s pricing practice (of charging for InMails) is destroying the quality of the network by including spurious links. I guess they’ve done a cost-benefit analysis and believe that the cost of spurious connections is far lower than the revenue they make from InMails!


Social Reading

Feedly, the RSS Reader I’ve been using ever since Google Reader shut down, has announced a feature called “Shared Collections“. This is something like the Google Reader shared items (much loved by its loyal users including me, but something that apparently wasn’t good enough for Google to retain), except that it is available only for premium users.


While this is in theory a great move by Feedly to start shared collections, recognising the unfulfilled demand for social reading post Google Reader, their implementation leaves a lot to be desired. And I’m writing this without having used the feature, for, in an extremely daft move, it is available only for pro users. My problem is with the pricing model, which charges content creators (or curators or aggregators, if you like to call them that) for sharing content!

There are so many things wrong with this that I don’t know where to start. Firstly, if you charge people for creating content, that significantly increases the barrier to creating content. If there is an article I like and want to share with my (currently non-existent) followers, the fact that I have to create a premium account to do so means that the barrier to doing so is too high.

Secondly, if I’m going to be a consumer of shared collections from other people, I’ll need a certain critical mass of friends before I start using the feature. I won’t start using a feature only because one or two friends are curating content on it. The critical mass is much higher. And by putting barriers to entry to people who want to share, it makes this critical mass even more difficult to obtain.

Thirdly, Feedly doesn’t have a social network of itself so far (though I’m not aware what permissions they’ve taken from my when I used my Google account to log in to the service). And without having a ready social network for discovery (Google Reader leveraged the Google Talk network), how do they expect people to discover each other’s collections, once created? Are they relying on external networks such as Facebook or Twitter?

It is not easy to build a social network of curation. Google Reader had managed it quite well back in the day by first allowing people to share items without comment, then add external content, and then to add comments. It was an extremely powerful way for people to share blogs and other content, and discussion on that was rather active. I even remember quite a few people adding me on Google Talk for the sole reason of wanting to follow my Shared Items.

In recent times we’ve seen the news aggregator app Flipboard starting its personal collections feature. I have a collection, but don’t remember the last time I put something into it – for without any interaction on that, there’s absolutely no motivation. Flipboard, by the way, has access to your Facebook and Twitter graphs, and so has access to some sort of a social network. Yet, despite keeping the feature free, they haven’t been able to generate sufficient activity on it.

Feedly has got just about everything wrong with its Shared Collections feature. There is disincentive for content creators. There is no incentive for content consumers. They don’t have a ready social network. And there doesn’t seem to be any interaction.

If only Google were to bring back Google Reader and Shared Items, now that they’ve decided to dismantle Google+.