In the review of the book power of habit mentioned earlier we covered the findings by the author on what it is and why we do it. We now look at some of the applications discussed in the book. The author gives examples from successful organizations. He describes habits that are important as keystone habits. He gives the example of Alcoa - an aluminium manufacturing giant that had been dwindling and brought on a new  CEO O'Neill. O'Neill was a former government bureaucrat who wanted the employees to focus on safety and touting it as a habit of excellence. Further, he wanted to make it an indicator of progress throughout the institution.His comment was initially perceived as totally out of context and relevance to the situation the company was in but within a year to the date from his speech, ONeill grew Alcoa' market capitalization to $27 billion and created record profits.  The value of the stock had risen five times larger than what it was. The key to his success was that he attacked one habit and watched the changes ripple through the organization. O'Neill observed that some habits were more important than others. They had the power to start a chain reaction. These are called Keystone habits. Keystone habits say that success is dependent on a few key priorities and fashioning them into powerful levers. Organizational behavioral patterns are quite common. In fact researchers have found institutional habits in almost every organization or company they've scrutinized. What ONeill found was that the decision making was being ceded to a process that occurred without actual thinking. Consequently the workers were not nimble and the quality of the products was poor. When previous CEO had tried to mandate improvements, effigies of managers were burned. ONeill wanted something that everybody including unions would agree was important. By declaring safety as the priority with a metric as zero injuries, ONeill had brilliantly mandated that Alcoa be more streamlined. He used a simple cue : worker injury to institute an automatic routine where the unit president had to put in a place a plan to never let it happen again. And there was a reward, the only people who got promoted were those who embraced the system. The ripple that this created - unions embraced productivity measurements, workers were given more autonomy, faulty equipment were replaced, loss of raw material was reduced with upgrades etc.
The author says that studies have shown such chain reactions with habits even in family life. Families that eat dinner together seem to raise children with better homework skills, higher grades, greater emotional control and more confidence. Habits create a new structure that establish cultures where change becomes contagious.
Habits can be complex and old. Yet every habit is malleable. Its the power in remaking a habit that this book advocates.

The power of habit is a book by Charles Duhigg. The author explores why habits exist and how they can be changed. He includes anecdotes on companies and individuals who struggle to change and who seem to make the change overnight. The author argues that most of the choices we make today seem to be well considered decision making but are in fact just habits. By understanding how habits work, we can rebuild those patterns in whichever way we choose.
Researchers have found that an organ inside the brain is responsible for forming habits called basal ganglia  They studied rats running through a maze to form their opinions on how rats internalize the maze. Converting a sequence of actions into an automatic routine is called chunking. There are dozens if not hundreds of behavioral chunks and they happen because brain is trying to figure ways to save effort. The process is a three step loop involving a cue, a routine and a reward which when repeated becomes a habit. Some peoples habits are obnoxious. If we want to create new habits we should look at Claude C Hopkins who was in the advertising industry and had  a set of rules he coined to create new habits among consumers. Among his rules, he first created a craving to a power of habit. He illustrated this by making
America brush with pepsodent.  The cue he used was a tooth film which was universal and impossible to ignore. He was selling a sensation.To understand next how to change the habit, the author illustrates the golden rule with the example of Tony Dungy who as a coach wanted to change the behavior of the players. Dungy wanted to attack only the middle step in how habits form - the routine. The cue and the reward are kept the same but the routine is changed. When this rule is applied correctly, even habits can be reversed. 

Good to great is a book written Jim Collins. The following is a summary review of the book.  The title comes as a sequel to the author's earlier book called Built to Last which he attributed as greatness and hence the suggestion that many companies that are good don't get to the next stage of being great.  Here he focuses on why more companies don't do what worked for others or do it more often. He picked eleven companies Abbott, Fannie Mae, Kimberly Clark, Nucor, Pitney Bowes, Wells Fargo, Circuit City, Gillette, Kroger, Phillip Morris and Walgreens. These companies had to meet the criteria that they had 15 year cumulative stock returns that were at or below the general stock market, punctuated by a transition point, then cumulative returns with three times the market over the next fifteen. These companies were selected over their competitors because they either do not show such a leap or did not sustain it.  From these selections, the author describes patterns that emerged from this behavior.
The first topic was about leadership. Contrary to the belief that celebrities may have influenced the performance in the market with their charisma or influence, these companies had leaders who demonstrated Level 5 leadership. The term refers to those who unlike the celebrities had personal humility and intense professional will. Many such leaders often setup successors for success. Their humility came with a steely resolve and intolerance for mediocrity. Abbott Laboratories attacked nepotism in its company to make the leap. The levels from 1 to 5 are graded as follows: level 1 - comprises highly capable individuals who make productive contributions through talent, knowledge, skills and good work habit; level 2 comprises members who contribute at the team level and work with others; level 3 is a competent manager who organizes people and resources towards objectives; level 4 is a leader who draws commitment and pursuit to a clear vision; level 5 is those who establish the vision independent of themselves to make the company move to the next plane.
However, the author argues vision or strategy is not the primary prerequisite to make the leap, instead its the selection of people to get on the bus before deciding where to go. As an example, Wells Fargo continuously hired the best to prepare for changes in its industry. The book claims the following truths:
If we focus on who are with you rather than the mission, the changes is going to be easier.
If we have the right people, we spend less time on managing them.
If we have the wrong people, we cannot make the most of the right direction.
Essentially its about people who practice a culture where they don't worry about their positions.
It also implies not to hire too soon too fast and to put existing people not on the biggest problems but the biggest opportunities.
Another pattern that emerges from this company is the notion of disciplined thoughts. Self-assessment by companies is a pre-requisite to knowing what transition to make. Called brutal facts, these establish the weaknesses that are clear enough. The author highlights that some leaders were open enough to say "I don't know" and that is welcome. It simply argues for evaluations and positive feedback more often to keep refining it till it becomes clear. Clearer facts are easier to execute on, be measured and put in a cycle of improvements. Such facts could also be opened up to the public. To do this the book suggests the following:
- Lead with questions, not answers such that we often discover more and more than what we perceive.
- And engage in a dialogue not a debate, sermon, ridicule or worse coercion.
- Review past work but without blame and with a resolve to do better
- Keep metrics and thresholds so that they can translate to actionable alerts.
The book also introduces hedgehog concept which divides the world into two groups - the hedgehogs who translate the complex world into a single idea or a principle and the foxes who take the complex world for what it is and work on different levels often missing a unified direction. The hedgehogs win in a match with the foxes.
The use of the hedgehog concept is to illustrate that leaders with a simple mission can help drive the company from good to great. To find this mission, the concept talks about identifying the intersection of three dimensions : what we can be best at, what drives the economic engine, and what we are deeply passionate about.
Another pattern mentioned in this book is about  disciplined action. These involve building a culture around the idea of freedom and responsibility, within a framework. It also involves getting passionate people who will take their responsibilities forward. The degree of adherence to the discipline should be reasonable and more towards the hedgehog concept than religion.
Lastly, the book mentions a pattern to use technology to accelerate and encourages the use of right technologies as opposed to new technologies. In fact, it cautions against the zeal to use new technologies.
With the patterns mentioned, the book suggests that there is a flywheel effect that can result in good to great transformations. The opposite of the flywheel is the doom loop which can be seen in the cases where the patterns are not followed.
  

Having looked at the bottom up approaches to finding sub-networks in a graph, I will now read the top down approaches from the Hanneman online text.  The bottom up approaches help us understand the processes by which actors build networks. On the other hand, the top down approach helps us find holes, vulnerabilities, or weak spots that define lines of division in a larger group. These help to describe the levels of group selection and the constraints under which actors build networks.
We look at components first in this methodology. Components are subgraphs that have high cohesion and less adhesion.Components can have weak ties whether the direction of the ties don't matter and strong ties which are directed. If we have a metric that establishes connections between components as one where the actors participated in something common, then for a very high threshold, we may have few or no independent actors.  and for a lower threshold, we may group them into a component. This therefore is too strong a definition to find weak points.
Blocks and Cutpoints are alternative approaches to finding key weak spots in graphs. If a node is removed and the structure is divided into disjoint parts then that node is called a cutpoint and forms a broker among otherwise disconnected groups. These groups are called blocks. We can find the blocks by the cut points While component analysis looks at missing links, this bi-component analysis looks at vulnerable links.
Lambda sets and bridges is another alternative approach for the same. This ranks each of the relationships in the network in terms of the importance by evaluating how much of the flow goes through each link and when disconnected would greatly disrupt the flow between nodes.
Factions are ideal groupings where the members are closely tied to one another but not to anybody else. This concept helps us assess the degree of factionalization in the population.
With the bottom up and top down approaches, we find sub-networks in a graph. The groupings or cliques - their number, size and connections can tell us about the behavior of the network as a whole. 

A graph of knoke information shows strong symmetric ties. It also answers questions such as how separate are the sub-graph ? How large are the connected sub-graphs.Are there particular actors that appear to play network roles ?
We now look at ways to find sub-graphs.  One approach is the bottom up manner. A clique extends the dyads by adding members that are tied to all the members in a group.The strict definition can be relaxes to include nodes that are not quite so tied as we will see shortly with n-cliques, n-clans and k-plexes. The notion however is to build it outwards to construct the network. The whole network can then be put together by joining cliques and clique like groupings.
Formally, a clique is the maximum number of actors who have all possible ties among themselves. It can be considered to be  a maximal complete sub-graph. Cliques can be viewed in conjunction with the Knoke information matrix mentioned earlier. We might be interested in the extent to which these sub-structures overlap and which actors are more central or more isolated than cliques.
We can examine these by evaluating the actor by actor clique co-memberships.Then we can do hierarchical clustering of the overlap matrix which gives us an idea of the closeness of the cliques. Visually we can see the co-membership and the hierarchical clusterings as matrices formed from the actor and cliques and levels and cliques respectively.
 Two major approaches to relaxing the definition for cliques are the N-cliques and N-clan approaches.
In N = 2, cliques we say that an actor is a member of a clique if it is connected to every other member of the clique at a distance greater than one, and in this case we choose two. The path distance of two corresponds to the actor being a friend of a friend.
The cliques that we saw before have been made more inclusive by this relaxed definition of group membership. 
The N-clique approach tries to find long and string like groupings instead of the tight discrete ones by the original definitions. It is possible for actors to be connected through others who are themselves not part of the cliques.
To overcome this problem, some restriction is imposed additionally on the total span or path distance between any two members. This is the N-clan approach where all ties are forced to occur by means of others members of the n-clique.
If we are not comfortable with the idea of using a friend of the clique member as a member of the clique, we can use the K-plex approach. In this approach we say that a node is a member of a clique of size n if it has direct ties to n-k members of that clique. This tends to find a relatively large number of small groupings. This shifts focus to overlaps and centralization rather than solidarity and reach.
Courtesy: Hanneman notes

In this post, we will cover an interesting topic : cliques and sub-groups.
In graphs and networks, one of the common interests is the presence of "sub-structures" that may be present in a network. Neighborhoods and groups of nodes fall into this category. When small compact sub-networks are joined to form large networks in a bottom up manner, we form extended network known as cliques. In cliques there's generally more interaction between the members than with others.
A clique can be considered a closed elite.  We can also look for this substructure from the top down. The idea that some regions of graph may be less connected than the whole  may lead to insights into cleavage and division. Weaker parts in the social fabric also create opportunities for brokerage and less constrained action.Most computer algorithms for locating sub-structures operate on binary symmetric data. We can use Knoke information exchange data to illustrate these sub-networks with strong ties. Knoke information exchange can be viewed as a binary connectedness values on the adjacency matrix of a directed graph.

I'm taking a short break today as I'm taking my time on another task from work today.

The use of matrices to describe social relations is as follows:
Transform a block operation allows us to select a matrix to be blocked, a row and/or column partition and a method for calculating the entries in a resulting block. We first split the row and column partition. These are just data sets which we then group to form partitioned data sets.  This operation requires a method for summarizing the information within each block. The operation outputs two new matrices. The PreImage data set contains the original scores, but permuted. The reduced image data set contains a new block matrix containing the block densities.
The Transform collapse method allows us to combine rows and/or columns by specifying which elements are to be combined and how. Combinations can be maximum, minimum and sum. The result of the combinations is a new matrix with specified operation performed.
The Data -> Permute allows us to re-arrange the rows and/or columns and/or matrices.  This operation requires us to list the new orders method needed.
The Data->Sort re-arranges the  rows, columns or both of the matrix according to a criterion we select.
The Data-> Transpose re-arranges the data in a way that is very commonly used in matrix algebra and switches the columns with the rows.