Vinayak Hegde

Jodhpur is a trading town right in the heart of Rajasthan. The famous Mehrangarh fort stands on a hill rising majestically and towering over the city. The other places worth seeing in the city are Jaswant Thada – The cenotaph of Maharaja Jaswant Singh II and Umaid Bhawan Palace – which has been converted now into a luxury hotel.

This photo is of a kid who was dancing and singing near the gates of the Mehrangarh fort. It was hot and dry in the afternoon when I took this photo and the kid did not want to dance. His mom pushed him to dance though, which made him angry. I managed to capture his candid mood in this photograph. More technical details about the photo at my photoblog (click on Image Info).

In my last blog entry I talked about graphing the informal office social network. Using the social hack I could find out how the news propagated in the grapevine network. We can draw similar kind of graphs using public chat rooms such as IRC channels. We can use this to derive relationships between people. I was looking for doing something similar to my last experiment using IRC channels.

But to graph the relationships between people on IRC channels you need to write a bot which does this. IRC protocol is very simple and easy to implement. There are quite a few opensource bots out there which could be modified to fit. Luckily I found a IRC bot called PieSky which was written in java which does exactly this. It can infer relationships between people using the IRC conversations. Piesky has some nifty features which makes it really good for this purpose such as:

1. It draws an internal graph depending on who is talking to whom on IRC.
2. It has built in visualization tool for graphing these relationships (which is customizable)
3. It has some heuristics for temporal decay.

I registered the nick social-bot using nickserv on irc.freenode.net. After that I choose 3 channels to monitor for this experiment – #gentoo – A linux distribution channel, #python and #perl – both open source programming languages, ##linux-india – an IRC channel where linux enthusiasts hang out. I ran Piesky for about 12 hours on these channels. Piesky generates graphs for every dialogue between participants of an IRC channel. So make sure that you run this on a reasonably powerful machine if you are going to try this on a very active channel. Piesky has built-in temporal decay for relationships, so that relationships fade out when people stop talking – just as in real life. Running piesky on IRC channels threw up some interesting results. Those who have been using IRC for sometime like me will identify with this.

What the graphs represent :
1. The nodes represent the participants of IRC channels and lines represent the relationships between them.
2. The thickness and darker hues of the lines indicates the strength of a relationship.

##linux-india
Lap_64 was yakking away and seemed to talking to everyone and hence he is well connected with everyone. But he seems to be mostly talking a lot to binand. Similar lut4rp has been busy chatting away but he seems to have his own set of friends and though there is some overlap between them. Obviously Lap_64 and lut4rp seem to be hanging around for sometime and know quite a few people on ##linux-india or are particularly chatty during nightime (when this test was run and graph was generated). binand and binand_ indicate that binand had got disconnected but did not bother to ghost his IRC nick. ##linux india has been around for a long time and does not have many people logged onto it. This channel is active during the evening and late at night so the graph indicates that (with two almost disjoint set of nodes). This is typical of country-specific channel where activity rises and diminishes depending on time of day.

#perl and #python
Perl and Python are well known open source languages which attaract loyal followers from around the world. Such channels also have a long discussions on code and features of languages. The two social graphs indicate that. If you run piesky you are likely to see well-interconnected graphs such as this which means there is great amount of cross discussions and hence more dense relationships than country-specific or distro-specifc channels.

#gentoo
Linux distros such as gentoo also attract followers from around the world. But much of the discussion on features and code happens on the developer or maintainers mailing list and not so much on public IRC channels. So many of the participants in the #gentoo or #fedora ask a few questions and then leave. This is reflected in the disconnected graphs which piesky draws for distribution channels.

There are two major glowworm caves in New Zealand. Waitomo caves on the North Island and Te Anau caves on the South Island. Te Anau is the gateway to the Milford Sound and Doubtful Sound, both famous fiords in the south-western coastal part of New Zealand called as Fiordland. Knowing that we would not be able to make it to Waitomo caves due to lack of time, we went to the Te Anau glowworm caves.

This photo is of the wharf on the shores on Te Anau in the Murchison Mountains. It was taken during twilight. More technical details about the photo at my photoblog (click on Image Info).

Introduction
Social networks are all the rage nowadays, with every other me-too startup targeting some kind of relationship and helping people interact online. Social networks give interesting insights into the minds of people which were hitherto unavailable (atleast on a large scale) till a few years back. This post describes an experiment my colleague and I did on a group of people informally. We were a small group of people of 30 people in the team spanning various departments from sales and marketing to engineering and finance.

The Experiment
My friend and I wanted to trace the informal grapevine network from which we used to get the interesting news in the office. Soon the opportunity came in an unexpected manner. The office picnic was being planned and Engineering (4 engineers strong) was given the task of planning and executing it. We came up with a strategy for planning that. We kept the location secret so that everyone would keep guessing it and create a buzz. Other than creating hype, we had an ulterior motive (Ha Ha – They were the guinea pigs !!).

The Actors
We knew there were 3-4 people who would generally speak with people within their department (called Propagators). It was 24×5 office so not everyone worked at the same time. That was one of the reason for some isolation between different departments. Also there were a bunch of people (about 3-4) who were comfortable speaking to almost everyone in the company (called Intersections).

The Plan
So we started a buzz about the secret location. Propagator A was told that we were going to Kabini (nice), Propagator B was told Bannerghatta (moderately good), Propagator C was told some resort on the road to Mysore. Also there was purposeful variance between the location. Kabini was great but slightly far so it would have necessitated overnight stay which some people would be unhappy about. Bannerghatta resort was close to the office but not as great as Kabini. The resort near Mysore was moderately far but any more details were not given. The variance in the locations meant that people will talk about it more. More pros and cons means more gossip. Exactly what we wanted. PA, PB and PC were chosen so that they would talk amongst their group mostly. Soon after we told P[ABC] the information, we started getting queries from people about the possible location. Most people heard from one person the first day. Slowly as the news spread, Intersections (I) came to know about it. They became active, more people started querying us with different locations including those who rarely spoke with us. Soon everyone was confused and the reticent people who wouldn’t talk with people much started getting the news and talking to us. We were at an advantage because we used because our work timings would overlap with all the 3 shifts by some factor so we were always accessible for queries (more datapoints . So we were silently chugging way writing in our little notebook figuring who spoke to whom. Also we were noting who spoke to whom first (the comfort level indicates a stronger bond – makes sense ?). Eventually we announced the secret location (Bannerghatta) a couple of days before the event. Finally, I drew the following graph (obfuscated to department level – Thicker lines indicate stronger bonds -based on comfort level and interaction) based on our little notebook.

Map of the Grapevine

The Conclusion
We can see that Marketing talked most with Sales. The unusually strong bonds between HR and other departments were because we were ramping up during that time. I doubt if such a experiment would work with a bigger setup. Oh Yes, we did see chinese whisper phenomenon at work during the experiment as well.

The town of Mount Abu is the only hill station in the state of Rajasthan. Since it is close to the state of Gujarat, it is a popular vacation spot for tourists from that state. The two main attractions of the town are the Dilwara Temples and the Nakki Lake. The carvings in the Dilwara Temples is exquisite. It is so fine that you are afraid to touch thinking that it might crumble to pieces. Alas they wouldn’t let you take any pictures.

The above photo is of a restuarant on the shores of the Nakki lake. It’s not a floating restaurant but looks like one from the vantage point it was taken from. More technical information (click on Image Info) about this photo at my Photoblog Lens.