This is a great example of Kohonen's Self-organizing Maps and the use of the U-Matrix. The authors were very thorough in explaining how it can be used.

Data Structure

This is the novel innovation approach to network analysis that I will be discussing in my article review presentation

I am familiar with SPSS, but I had not considered using it for my final project until now. I am a little confused about how I would have to code the data (adjacency matrix) so that it works well in SPSS, but I think I'm going to try it just to see if I can get the same results that I obtain from using R.

I am interested in learning more about the NetDraw software in UCINET. While I like statistics, nothing really says SNA like having clear visuals that display network ties

I need to more practice with creating cleaner graphs that show my network. So far, I've been sticking with the orange and blue colors but I plan to get a little more creative for the final project

My project deviated from the author's process because I actually obtained the dataset before identifying research questions. I am using a public dataset so I had to develop me project around what I had available

Throughout the semester, I have struggled with turning my research topic into a researchable question. I think I've come up with some decent questions, but I'm constantly rewording them.

I have a background in quantitative statistics. The use of a t-test assumes normality of data. I know that normality does not matter for SNA, but is this particular section referring to a nonparametric test that works like a t-test or is it actually referring to the use of a t-test and just ignoring the assumption of normality?

Ok... So now this is making a little more sense for my own data. In my case, I could analyze the countries geographic loaction as an attribute varibale that predicts the probability of certain industries having multiple companies in a given country. Does this make sense?

I really wish there was an explanation of how to construct/create/execute a p* model using R.

Ahhhh... This makes sense. I asked about this in the previous chapter.

Can ERGMs be used for nonreciprocal networks?

I am using ego-level networks for my final project, but how would I go about ensuring that the ego in question was chosen randomly?

Maybe I missed something in our previous readings/videos, but can someone explain to me what is meant by the term "artifacts"?

Would running such tests require a need for assessing latent variables that emerge from network analysis? I will keep reading, but from what I know of SNA, it seems like you are only analyzing observable variables and it would be difficult to obtain a correlation from such unique variables. Am I way off here?

I would actually be interested in conducting a factor analysis on my data. Though I am a bit confused about how such a test would be useful for SNA

For my current data set, this is true. However, it would be nice to be able to make generalizations to a larger population.

I have been dealing with this issue all semester. I am really struggling to determine which questions are appropriate and which can be answered using SNA techniques. Perhaps this is due to the type of data I am working with, but I am still working on developing sound research questions.

I am really looking forward to better understanding the concepts of SNA... beyond the explanation of just looking at relationships.

Given the nature of my data (Forbes top companies), I think it would be appropriate to look at specific countries as the Ego and the job categories as the alters. Am I correct in assuming that the local pattern of relations would be how my selected county (the ego) is connected to other countries through job category?

Since I am working with countries and job categories, I think it would be best for me to work with non directional neighborhoods. I would like to see some directed ego centric data though.

My research doesn't actually focus on individuals so this is interesting.

Nice definition

This reminds me of my middle school. Rather than each class period having different students, we had one classroom with the same students and we would just switch teachers each period. They all taught the same students. It's nice to have a personal example of structural equivalence

I'm interested to learn more about this.

From my understanding of this, structural holes differ from triads since triads generally indicate that all three actors are connected in some way. Is this correct?

I like the explanation of effective density. I think it will be useful for my own "potential" research

This is the software that was used by the authors of the article that I chose for our Week 3 assignment. Apparently, it's a fairly common choice for SNA research

Are we allowed to include nodes for John and Holly if they are identified by others, but without using their name? For example, we would refer to John as Anonymous 1 and Holly as Anonymous 2. Or would we have to exclude any data that involves them, regardless of anonymity?

While I know this is possible in some situations, I wonder how often it actually occurs.

This seems similar to conducting a program evaluation. I guess the only difference would be the application of network analysis.

Interesting. I am unfamiliar with this type of sampling. I have heard of it before, but I have not seen many studies that utilize this sampling approach.

I think this is a really good example of SNA research. It would take a lot of thinking to operationally define bullying as identified on facebook, but I bet the results would be interesting. I wonder if something of this nature has already been studied.

This is my first time learning about cultural capital. It makes sense so I am surprised that I have not come across it before.

Human Capital is a big deal in the field of Human Resource Development. Supporters of the human capital theory argue that humans are the best asset of any organization. It's nice to see the theory mentioned in literature outside of business and HR fields.

While I can make an educated guess as to what these terms mean, I am not very familiar with them.

Interesting

Here is a better explanation of the SNA terms Arcs and Edges. Arcs represent those relations that are directed from one student to another, meaning that the friendship nomination has not necessarily been reciprocated. Edges, on the other hand, are those lines that do not have arrowheads (since friendships are directed, there are no edges in Figure 3.1), which are appropriate when the relation is by definition reciprocated (e.g., “studies with”).

I am unfamiliar with the term "arc" in this context since I am unsure what is meant by "directed lines".

Applied quantitative SNA methodology

Great example of SNA at work.

I think this will occur a lot in SNA

This is a really great SNA term/phrase. Generating big ideas from small observations is a nice description of SNA. It reminds me of the grounded theory approach in qualitative research.