What Community Soccer tells us about Social Media for Business

My wife always tells me that I have a horse shoe in my ass. For some reason I have this knack for walking into a space with no preparation and coming out on top. Case in point: I volunteered to coach community soccer this year. Every week I do pretty much the same simple drills before each game – starting out with a cheer and one simple task – can you touch the ball over and over again while looking at me (not the ball). Now the goal for community soccer is not that you win all the games, but instead that everyone scores at least once by the end of the season. It’s not even half-season, and we are well on our way towards that goal. Horse shoes – I do almost nothing and success falls in my lap.

Now for the other side of the coin. I was asked to do a presentation on social media – something I have done over and over again with varying degrees of success. I prepared my way to no end, asking for help from various mentors, reading everything I knew and didn’t know about social media. Brought the stats. Found the right images. Followed every piece of advice. Fifteen minutes in, it became obvious that I prepped wrongly. Somehow I assumed the wrong things about my audience, remembered the wrong facts and worst of all, appeared to have lost touch with a subject I used to love so much.

The aftermath of this experience was a series of negative “never again” messages to people who asked me how it went. My attitude was “social media is old enough now that people already have their opinions. I am not going to change their minds. Social media now is more about tea parties and social justice warriors trying to use attention to influence policies. Or click bait journalism and cat photos. If you want a social media success story in this world, you will have to invest in Facebook or Twitter ads while ensuring a minimum presence to protect your brand. After that, there’s nothing else.” As one person in the presentation suggested, (referencing the book) “social media is bullshit.”

Two people brought me back to (actual) reality. The first was Bruce Walsh from the University of Regina Press. (PS. The Education of Augie Merasty is an excellent book that I intend on reviewing sometime in the next week also, Ken Coates kindly added a recommendation to me in his book about #idlenomore also published by the press) who somehow managed to get me out of this negative funk with his always positive personality. The second was Giles Crouch who is always a go-to for any ideas I have about the future of digital. They both reminded me of things I already knew. Social media is only part of the story. Like a computer has a monitor to show its outputs, our world has social media to show us a big world going on around us. Social media is not the story – our crazy world is the story and social media reflects it back to us.

So if you are a business wondering about a social media strategy now that social media is now both obvious and dull, I have to go back to my soccer success story. I wasn’t successful because I had horseshoes up my backside. I was successful because I didn’t overthink it. The only thing a U8 soccer player with minimal skills needs to beat other similar u8 soccer players is an awareness of the field. You need to see your players, your opponents and the goal. That means taking the focus off the ball and putting it on where you want the ball to go and when.

I am not going to spend any more time blogging to business people about strategy, planning and branding. There are far better people to discuss those things than me. The bottom line is that the story of social media for business is one that sends us back to fundamentals. I’ll lay them out for you.

  • Customer service. Your front-line staff need to know that bad experiences carry fast, sometimes through social media but also through email, mailing lists and word-of-mouth. Yesterday my wife had a poor customer experience at a government service that nearly had us changing major life plans just to avoid dealing with them again. Good experiences will carry too. You can’t please everyone, but you can try. The example I always offer was one time when I had every possible security inconvenience at the Denver Airport and somehow still felt like it was the greatest thing ever. That’s customer service.
  • Basic supervision. If you are a manager or supervisor, you need to know how your people are doing. Just the basics will get you there. Have short one on ones, ask people how their interactions have gone, what has been working, what hasn’t and give both positive and constructive feedback.
  • Look-up. In online terms, I think this means going to page 10 of your Google search results. Don’t focus on what’s captured everyone’s attention. Focus on what is important to you and your business.

I am no business owner, but I have looked into the deep heart of social media and found both lots of bullshit (usually 40% of all messages on a topic are just that) but also lots of really thoughtful dialogue and sincere discussions about what does and does not make us happy. Hopefully this little tidbit helps make you happy too (if it doesn’t make you rich)!

Chantal Hébert and Social Media

Last night (April 15th, 2015 for those future people not paying attention to the blog date) I attended the Tansley lecture hosted by my school the Johnson-Shoyama Graduate School of Public Policy with the guest presenter, Chantal Hébert‘s discussion the role of social media in changing politics.

I have to say that I’ve often considered Chantal to be the best no-shit political commentator in Canada today and to have her present at what is for me one of the most important policy-related meetings annually was very gratifying. She was definitely her very brightest with just enough aloofness to make sure you knew she was giving you the honest goods. A good amount of her talk relied on her experience as a political journalist and she openly admitted that she would not have everything tied up in a nice box for the audience. She couldn’t possibly.

She began by describing political campaign reporting in the past as high-jacked by political actors. Media relied on the telephone to find out information and ask important questions. To keep media in the dark, you just had to keep them away from a telephone. According to Hébert, you’d think that 24 hour access to information online would mean a more informed society that is more connected to the issues.

But not so. Instead, she argued, politicians have come to understand that in a world of constant information, the only time a journalist will call is when they have some controversy to get a reaction to. That means that the person who takes the call is no longer the person who actually knows what’s going on, but instead someone who is used to communicating in a crisis.

Hébert sees this as a serious problem (as do I). Social media to her mind means that the chattering classes and government are increasingly disconnected from the voters, who, more often than not, are too busy working their 3 jobs to get excited about the latest Gawker report on some offensive thing a comedian said on Facebook.

I will be presenting on something similar in Arizona in May for the Digital Government conference. Although a lot of it will be a bit too technical for a blog post, one thing I will note comes from the protests on Elsipogtog First Nations against some hydraulic fracturing tests occurring near their lands. The eventual government response went in their favor – a moratorium was called on all fracturing in the province. While the anti-fracturing protests were all over social media, there was almost no mention of support for the government’s decision. Not even an “it’s about time.”

This theme of public interest in drama, but disinterest in solutions is something that bears scrutiny in our society. Hébert cites the example of young Quebec anti-austerity protestors who could not name the Premier who called for those measures. Too much of the social movements we see are caught up in ideas about social problems and less involved in the institutions they expect to do something about those problems. I don’t know if this is too new, but it’s a lost opportunity that all this political action has little to no connection to the people with the legitimate authority to act on the citizens behalf.

My dissertation will be looking at this problem with the hopes that the research I provide can suggest some recommendations around what could be done to connect those engaged in social movements to the legitimate political power. Given big issues like climate change, economic disparity, depleting resources, lack of productivity, a growing yet marginalized First Nations population etc., it is essential that we get as many bodies interested in developing policy solutions as we can.

How social media makes things worse.

A little ways back, I decided that I would try my best to fight misinformation on the Internet. I just found too many people who I respected just off-handedly sharing one piece of information or the other with a tag line “so true” when in fact, it had very little truth about it.

Often, it puts me in a very difficult position. Let me provide an example. Consider this article by Matthew Yglesias from vox.com. In it, he decries “white on white” violence as a retort to Joe Klein’s assertion in Time that “Blacks represent 13% of the population but commit 50% of the murders; 90% of black victims are murdered by other blacks.” Looking at the same statistics Yglesias found that 80% of white victims are murdered by other whites, and felt that this was an ideal time to point out how biased we are when we look at crime statistics.

Racial bias is an empirical fact, as is racism. But unfortunately, Yglesias’s claim that “white on white crime” is a problem is not a fact.

When you look at a statistic and want to decide whether it’s a problem or not, you need to compare that statistic to what you would reasonably expect given the context. For example, if you wanted to see if a coin was biased towards “heads,” you might flip the coin 10,000 times and see what happens. You would expect a 50-50 outcome over time. If the coin showed 80% heads, that’s strong evidence that the coin is unfair.

The mistake Yglesias makes is in assuming an expected value of 50%, which is not the case for race in the United States. If a group of future murderers (any race) were tracked, we would expect the proportion of white victims would be close to the proportion of white people in the population. For the United States, that expected value would be about 72%. I won’t go into whether an 80% result is statistically significant or not. In general, a good amount of social behavior is homophilous, meaning that like tends to want to hang around with like. While it is not a problem if people marry inter-racially, it turns out that, in general, people marry someone of their own race. Given that many murders happen at home, we would expect some level of homophily in the result. This could be because of racism, preferences or both, (likely both), but in the end this white-on-white crime scenario is not so far from the expected value that it represents a serious social problem.

On the other hand, given that the population of black people in the US is 13% and black on black crime is 90%, this is very strong evidence that black people are disproportionately killing other black people. If we were to assume that the white-on-white crime scenario was caused by generic homophily, then this suggests an extreme case that might have other causes beyond simple homophily.

The problem, of course, is that a radical right-wing racist interpretation of these statistics could be that Black people are inherently dangerous because they are black. It is possible, even by pointing out the faulty statistical interpretation by the vox article that I could be tacitly supporting these racists.

It is not as if others like Tim Wise haven’t already covered these interpretations in great detail all ready. On the other hand, it would be naive to think that anyone reading the Internet is going to go through the data, or even bother to read the entirety of Wise’s take-down of the extreme right-wing view.

On the other hand, the 90% black on black violent crime is about as solid evidence as you can get that institutions in the United States are heavily stacked against black people. It’s not just that, but also that rather than face the reality of this dire inequality, we’d rather share stupid, half-factual memes than work to resolve the problem. It is a difficult and controversial question to decide whether the benefits of sharing the statistics because it could result in judiciously increased support for African Americans would be outweighed by the use of such a statistic by racists to support their racist ideas. We also would have to consider the impact of sharing the statistic on the level of trust African Americans would have for their political institutions.

But, when we share something with a “so true” what is it that we actually mean by this? Well, I think it has something to do with what is symbolically true, rather than empirically true. For example, if you ask someone “do you believe in equality?” They’ll probably say “yes, absolutely!” But then you can ask them: “great – then how should be divide this pie that i baked?”

Deborah Stone covers this topic in detail in her amazing book Policy Paradox – The Art of Political Decision Making. Under highly politicized circumstances, dividing a pie is no easy task. You could say “all equal” but that fails to take into account that someone paid for all the ingredients and did all the work to make the pie. If they made the pie, maybe they should be able to decide how it gets divided. What if someone is gluten intolerant and can’t eat the pie? Do they get none, or should they be given the right to sell the pie to others in order to buy some cake, but the others have nothing but pie to offer. So maybe our pie maker should forget about making the pie and just give the ingredient supplies to the others. But there’s no guarantee that the others have the skills and abilities to make pie and cake on their own…

There is, of course, no correct answer here, and at the end of the day, someone is going to be upset. The best we can do, is provide reliable and trustworthy information to the group to show that we’ve done our best to try and be as fair as possible given all other alternatives currently available to us. But there is power inherent in what “problems” we decide to focus on and how they are framed (eg. maybe this is a pie productivity issue rather than an equality issue).

But to not frame the problems would create even worse outcomes. Left to our own devices, we are more likely to find ourselves in the clutches of tyrants, not less.

But there is one outcome worse than doing nothing: that is spreading incomplete or untrustworthy information. If we continue down the road of “gotcha” talking points, the end result will be polarisation and conflict. The only thing worse than an unequal distribution of pie is a mass war over the pie – that will only result in people getting hurt and the pie likely being destroyed.

In short, it behooves us to think closely about the information we share and how we present it. Some will say “but then you just have tone policing.” Well, no. If you only have a symbolic argument and you state it in ways that denigrate others, I think it’s quite justified to ask the person to calm it down. If the tone of an argument is a barrier to understanding, in particular because it gets in the ways of understanding the intricacies of the issue, then yes tones should be policed. Although perhaps time and place are considerations. There is a reason I have left this topic until well after the Ferguson protests, for instance.

The #TeamHarpy Affair – My Comments a Bit Too Late

The #teamharpy result ended exactly as I feared, but also as I hoped, but then again as I feared it would.

I feared that the people accused of libel could not prove their statements are true. I feared that they based their claims on hearsay and innuendo, but, egged on by people who should have had IANAL pasted on their foreheads with super glue, would continue to make the claims because they appeared true, or ought to be true, or had a vague air of truthiness to them. I feared that they treated the justice system in spiritual or normative terms when all of my knowledge and experience reminded me that the justice system is not a spiritual system, but a cold, hard materialist system. “Ought to be true” does not stand up in court.

I hoped that the plaintiff would understand just how stupid the world has gotten with communities and friends and followers. I hoped he would use that knowledge to compromise and negotiate with the defendants. I am not particularly fond of people who think that complete annihilation of their opponent is a virtue. It appears that the plaintiff has gone in that direction, and for that he’s gained a good amount of my respect. I learned from restorative processes that when harm is done, the person harmed most wants to be believed.  I don’t know him personally, but his (still alleged) choice to look for an apology instead of a big cash reward is magnanimous — empirically magnanimous. Everyone is not an angel, but occasionally people show flashes of moral brilliance. This seems like one of those cases. It’s better than I hoped.

Before I get to the final fear I had, I kept holding Don Quixote in my head as a mantra. Don Quixote. Don Quixote. Don Quixote. But the reality is that this was not like Don Quixote. Don Quixote had a Sancho Panza who tried to tell him to look ahead and see what was real. The defendants in this case, were spurred on by an army of Don Quixotes – all “fighting” symbolic ideas of … well, no need to go into that. Anyone who has read a really great book understands that sometimes symbols have a truth of their own. Don Quixote is a likeable character, probably because he has read too many books about chivalry and knighthood. The only problem he had was that he became so lost in the symbolic battle (there are plenty of abstract giants to overcome in our world) that he broke his lance. In fact, he was lucky that he didn’t all break the windmill, otherwise he may find a miller coming after him for restitution.

In short, the #teamharpy fiasco reminded me of this wrestling moment (be sure to start from 7 minutes):

I wonder what people really meant when they said “I support #teamharpy.” Was it real support or was it using the defendants’ reputations and livelihoods as a means to support their own foolish self-interest? Then again, what *is* real support? We all find ourselves throwing a little bit of money towards causes that inspire us, assuming that it actually helps.

This leads me to my last fear. The librarians I thought I knew claimed that their role was, at least in part, a way of improving information literacy. A big part of that was promoting critical thinking, evaluation of sources and better understanding of materials. This year it seemed that these ideas were all thrown out the window by some. The concept of professional librarianship took a big hit this past year.

I can hear a small band of Twitterites making the irrelevant claim that we should believe women, because harassment is a real issue and it needs to be addressed. And moreover that the only reason I am speaking out now is because I am a cis-gendered white male who is invested in this patriarchial system that oppresses men.

My reply rhymes with “duck shoes,” not because it is an absolutely false claim (the idea is so general, that is has to be at least partially true) but because it assumes that I do not have real life experiences that can inform the experience of the defendants here. I have had my own Don Quixote moments, and I am extremely thankful to the kind and supportive _female_ librarians who reminded me to pay attention to what is really important, and think hard about what hills are really the sort to die on. I got through my Don Quixote situations, not because I am special or heroic, but because people cared about me and helped me tell the difference between a crusade that was truly principled and one that was a sham.

I’ll also say that a good number of the #teamharpy Andy Kaufmans on my feed were white cis-gendered men. Consider King Lear, but reverse the genders. Those who disagree are not necessarily your enemies, and those who agree are not necessarily your friends.

My last fear was that we now live in a society that finds it nearly impossible to learn from the experience of others, and where diversity somehow became a “fight” instead of a set of values that lead us to make the world just a little bit better. And when we speak of a “fight” we usually mean one where other people pay the physical costs while the rest of us sit at home clicking stupid stuff, perhaps forgoing the occasional Starbucks so we can pretend we are changing the world.

This fear is in parallel with the loss of the principle that ideas should be judged on their merits rather than from their source.

It also suggests that the values of library 2.0 that i held in such high regard not too long ago, may have made our society worse off than better.

And as I watch people using the #teamharpy tag to continue to bully people from stupid anti and pro camps, largely to support their own ideological beliefs rather than the actual people involved, I cannot say that my last fear has not come true.

My Peer Review of Your Paper (A Parody)

Dear author(s):

I am going to start out with a summary of your paper and a few complimentary remarks. Unfortunately for you, I am a PhD student who just went ABD and is now in the process of writing a dissertation chapter that encompasses everything tangentially related to your topic. It will eventually be thrown away for something more sane, but I digress.

While this appears to be a peer review, it is in fact a game of Battleship. I will make a series of remarks A-2, B-12 etc. in the hopes that i can somehow sink the battleships which are your critical review, theoretical framework, sampling decisions, methodology, analysis and conclusions. In anticipation of this sinking, I will be a little bit nice this time in hopes that karma will extend this favor to me at some time in this process. For this reason, I recommend that your paper be returned with a request for major revisions.

Unfortunately, your theoretical framework does not encompass all aspects of the ever-changing and oft-debated discipline. Worse, it does not include some of my very favorite authors. You should include many more authors and especially my favorites in order to make your contributions to a fairly narrow, but relevant aspect of the field much less clear. The world is complex, my friend, therefore all straight-forward positivistic experiments much include at least one paragraph on postmodern social theory.

Your critical review of the literature is even worse than your theoretical framework. There are at least twenty authors who have said the exact opposite of “this thing that you referenced in your paper” and you need to deal with each in turn, even though they come from popularly tweeted blog posts of something some famous academics wrote one night when they were obviously either bored or very drunk. I also have written a few drunken posts on the topic that I will not mention here, but they are popular enough that if you google the appropriate terms you will find them pretty quickly. Unfortunately, I do not have any published works you can refer to, but that’s only because they are all in revisions themselves.

I don’t really understand how you came to select the cases you did. Please insert a few lines of bullshit that justify why people become interested in a research topic to the point that they wish to write about it. I kind of want to know why myself.

You elected to use some methodology that i do not completely understand myself. Good for you! If I don’t understand it, it must be pretty cutting edge. But, I am pretty sure that if I did the same thing with my own cutting edge methodologies, I would come up with fairly different results. This likely has nothing to do with your analysis, but instead with the way I treat research like a Yahtzee game. You see, whenever I get some great data, I shake it up a few times until I get a Yahtzee! Once I see that Yahtzee, I come up with a great research question. Like this: How many dice are showing the exact same number? Hypothesis 0: not 5. Hypothesis 1: 5. Result: Yahtzee! (otherwise, I wouldn’t bother to write up the results.) Either way, choose a different methodology that is closer to the way I like to study problems.

I am not sure that your analysis follows from your theoretical framework. This makes sense because if you were going to use the theoretical framework in the way it was intended, it would just be duplicating the rather mundane and old methods of people who have already got their first academic job and have received promotion and tenure — not to mention tons of grant money to now do all that research work properly. This will not do. Your first mistake was trying to be both cutting edge and working from the foundations of a discipline. If I can’t sink you on one side, I will definitely sink you on the other.

Your conclusions are adequate of course, because we all know that attacking a conclusion is petty. You are free to speculate away all you want so long as you are sure to include the need for further research. Of course, that need would be subsided if people actually began to accept my papers, but there I go again digressing on the issue.

I noticed a number of minor typing and grammar errors. Hopefully these will not matter as the primary goal here is that this paper never makes it to the final proof stage.

Also, I thought I’d include a little bit of speculation here at the end because I am kind of on a roll. In fact, if it weren’t a complete violation of the rules of peer review, I think I’d want to publish this myself. I think it could become Internet gold.

P.S. I may still be drunk.

P.P.S. In my opinion Rusty Nails go very well with revisions. If you have no Drambuie, just add lime juice and marachino cherries and make a Whiskey Sour instead.

1972 Canada-Russia Summit Series Hockey Game 8: A Social Network Analysis Part One (1st Period)

The 1972 Canada-Russia Summit Series to some is a defining moment in Canada’s history. At the height of the Cold War, 28 hockey players went into a tournament thinking they it was an exhibition series that no one would take seriously. By the end, the 28 were defenders of Canadian hockey against the surprising hockey prowess and political power of the Russian bear. The final game, number 8 in the series of 8 was particularly dramatic. After a closely-fought first period, the Canadians fell 5-3 in the second, but came back to tie it in the third until 19:26 of the third period when Paul Henderson … well if you don’t know the story, you probably aren’t Canadian and don’t care anyway. Well, here’s the game on YouTube if you want to see more.

Game 8 is a good case for social network analysis centrality at work. A hockey game is a network where people pass a puck to and from each other over the course of 60 minutes. Each time the puck passes from one player to another, we can create a directed tie. We may also be able to make some statements about the game. For instance, is it more important to give or receive a pass from a diverse group of players? Who passes to the biggest passers? Who receives passes from them? Rather than going through all this preamble how about I just get to it?

The Roster

Maybe later I will add the last names, but right now I’m going with the numbers.  You can use this roster as a key to find your favourite players.

Team Canada

  • 02: Gary Bergman
  • 03: Pat Stapleton
  • 05: Brad Park (if it weren’t for Bobby Orr, the greatest defenseman of his era)
  • 06: Ron Ellis
  • 07: Phil Esposito (big goal scorer and captain of the team)
  • 08: Rod Gilbert
  • 10: Dennis Hull (Brother to Bobby)
  • 12: Yvon Cournoyer (The Roadrunner)
  • 17: Bill White
  • 18: Jean Ratelle (One of the great Rangers, amazing goal scorer)
  • 19: Paul Henderson (A very good player, but the hero of the series)
  • 20: Pete Mahovlic (Overshadowed by his brother Frank, but actually very good)
  • 22: J.P Parise (Great player, but got thrown out early for threatening to slash the refs)
  • 23: Serge Savard (Eventually became captain of the Habs)
  • 25: Guy Lapointe
  • 27: Frank Mahovlich (Big “M” – hero of the Toronto Maple Leafs)
  • 28: Bobby Clarke (was chosen last for the team, but brought the Broad Street Bully element to the game.)
  • 29: Ken Dryden

Team Russia

  •  02: Alexandre Gusev
  •  03: Vladimir Lutchenko
  • 06: Valeri Vasilev
  • 07: Gennadey Tsyganov
  • 08: Vladimir Vikulov
  • 09: Yuriy Blinov
  • 10: Alexander Maltsev
  • 12: Yevgeni Mishakov
  • 13: Boris Mikalov
  • 15: Alexander Yakushev
  • 16: Vladimir Petrov
  • 17: Valeri Kharlamov
  • 19: Vladimir Shadrin
  • 22: Vyacheslav Anisin
  • 25: Yuri Liapkin
  • 30: Alexander Volchkov
  • 20: Vladimir Tretiak

Getting the Data Using R’s iGraph Library

The data were created using edge lists separated by spaces. Here is a sample of what it looks like:

Off16 Can07 
Can07 Can23 
Can23 Rus26 
Rus26 Rus22 
Rus22 Can29 
Can29 Rus22 
Rus22 Rus26

A few things that may be added in the future are the times of the pass, goals, steals (although this could be calculated on its own), power-play information and so on. But for now, I just have the edge lists. The first entry is the “from” player (Rus=”Russia”, Can=”Canada” and Off=”Official / Referee”) and the second is the “to” player.  You can enter the information in to an R graph object pretty easily using iGraph. You can assign descriptive values to the hockey players (vertices) by using V(df)$description.  In this case, I’ve used color to easily identify the Russians from the Canadians in the graph plots (igraph will automatically plot the colors if there is a descriptor available).

el <- read.csv("summitseries.txt", header=F, sep="") #sep="" means any whitespace
df <- graph.data.frame(el) # create a graph from the dataframe el

#Create a color vertex trait so that Russians are red; Canada is white and the Refs are black.
V(df)$color <- ifelse(substr(V(df)$name,1,3)=="Rus", 
               "red", ifelse(substr(V(df)$name,1,3)=="Can", "white", "black"))

Overall Degree

Degree refers to the number of different people a person passed/lost the puck to, or received/stole the puck from. It’s basically a count of the number of “sticks” for each ball.

The code to calculate the values is this:

V(df)$degree <- degree(df) 

Each player gets a value based on the total number of pucks received or sent.  To plot:

plot(df, vertex.size=V(df)$degree, layout=layout.kamada.kawaii)

This is what the graph looks like:

Screen Shot 2015-02-16 at 11.21.54 PM

This graph is not particularly meaningful, but it does offer a few insights. For instance, Phil Esposito (#7) was out a lot in this game and managed to both take passes away from the Russians as well as lose them. It kind of speaks to his garbage can approach to hockey – his play in this period, like most days was gritty and he found himself in the midst of almost every play. This also shows quite a bit of the classy Russian style of play with a lot of quick passes and fancy footwork. Almost every player on the Russian team had the puck quite a bit. Vladimir Shadrin (#19) is mostly ignored in the English world today, but he was amazing in this series, scoring more than even the Russian hero Valeri Kharlamov (#17) who barely shows up on the charts.

Out Degree

V(df)$outdegree <- degree(df, mode="out")

“Out” degree is the same measure, but only counting “outgoing” passes. These represent passes made or intercepted.

Screen Shot 2015-02-16 at 11.28.23 PM

Like I said earlier, Phil Esposito (#7) was finding himself giving the puck away quite a bit in this first period, but also making some pretty strong passes. Brad Park was also pretty busy. Both these guys happened to score goals in the period by the way. On the Russia side, Lutchenko (#3) and Yakushov (#15) are nothing particular special in the pass department even though they scored goals as well. That could be because the Russians were much more team players.

In Degree

V(df)$outdegree <- degree(df, mode="in")

Screen Shot 2015-02-16 at 11.51.10 PM

Not too much more to say about this one, except that it’s not too different from the outdegree measures. This is not that surprising given that if you have the puck either you are going to pass it or someone will steal it from you. I should also note that goalie Ken Dryden (#29) was pretty busy in this period. Not good for Canada.

Bonacich Power (Beta=0.5)

Now we can look at some eigenvector-like centrality measures. There are a variety of them, but I’ve decided to use Bonacich in this case. Bonacich uses a beta value that assigns a weight to the degree centrality of the neighbours. In the case of a positive value (cooperative networks), the more “passy” your neighbour, the more power you have. Unfortunately, this method produces both positive and negative values which is a little challenging for plotting.  So I have a little linear mapping function that I borrowed from here:

linMap <- function(x, from, to)
          (x - min(x)) / max(x - min(x)) * (to - from) + from

And then assign the values and plot.

V(df)$eigen <- bonpow(df, exp=0.5)
plot(df, vertex.size=linMap(V(df)$eigen, 0, 25)

Screen Shot 2015-02-17 at 12.16.15 AM

The picture is a little bit different in this case. Now we see the great New York Ranger, Jean Ratelle (#18) finding his way into the largest influencer position along with Bobby Clarke (#28). On the Russian side, Yakushev (#15), Karlamov (#17) & Mishakov (#12) find themselves in their rightful place as the elite members of their team. Phil Esposito, on the other hand shrinks to almost nothing.  Why? Well, he tends to find himself taking and losing the puck from defensive players more than picking up passes from his line-mates Yvon Cournoyer (#12) & Frank Mahovlich (#27).

Bonacich Power (Beta=-0.5)

V(df)$bonpow <- bonpow(df, exp=-0.5)
plot(df, vertex.size=linMap(V(df)$bonpow, 0, 25)

The picture is also quite different when looked at from a negative Bonacich power perspective. Usually negative bonacich power is used for networks that are competitive in nature, when it’s much better to have less powerful neighbours.Screen Shot 2015-02-17 at 12.17.12 AM

In this case, it’s pretty obvious that its the defensemen that have the least powerful as neighbours.  This makes sense because defensemen usually end up playing with a wider variety of forwards than other forwards do. Canada’s top defenseman, Brad Park, certainly found himself passing to and from the lesser lines in the first period, and likely stealing from Russia’s lesser lines as well!

Conclusion (for now)

This post goes to show that you can get a different answer from a social network analysis depending on how you decide to measure it. There are no mind-blowing revelations here (likely because the game was somewhat even at this stage) but still quite a bit of diversity among the different graphs that it gives pause. At the end of the day, this is why it is important to think clearly about your research question before you start looking at your data.  If you don’t, you’ll probably find yourself getting the answer you want just by rolling through different measures. I haven’t even gone through all the possibles – betweenness, closeness, clustering values and alpha centrality are all measures I’ve decided to leave out just for now (but may revisit later).

Another thing that might be interesting to look at is what the centrality values look like when I separate the Canadians from the Russians – from that perspective you could see how well the teams play with each other. Also, we could look at the edges where the puck changed hands from one team to another. In this case the negative bonacich power may be quite telling as per who was really coughing up the puck to the wrong people.

The data is not up in my git site yet, but I will share it eventually. I’ll keep the data open so that people can add or edit it as needs be. Certainly there may be problems with the way I coded everything. It was not always easy to see who was touching the puck. Sometimes I just had to guess based on position and the usual line-ups.