The internet has definitely helped us connect with many more people. Your example of the metoo movement is good because a lot of people on Facebook were posting about it. The movement was able to reach all over the Country, even in other countries because of our connections all over the world. By using those connections, the movement was able to spread and more people became aware of the movement. Another example is the Women's March that is taking place in January. Even though it is still months away, I have already seen some of my friends on Facebook say they are going or are interested in the March in D.C. There will be thousands of people who show up that day, and I think a large part of it is because of the use of social media and our connections and relationships with people. It shows that even while in person connections are important, that online ones can be just as important.

I agree with you. While I think less in person connections are made today than years ago, I don't think we are bowling alone. We are still making connections and forming relationships with people, just in a different way. Technology has evolved over the years, and will continue to do so. Even though our connections are more online, it doesn't make them any less important. I also think we are still bowling because we still have groups of people we connect with.

That is a great point. When we think about cyber bullying, I think this is especially true. I think when people use technology and hide behind a computer screen, they may think that what they are saying doesn't affect people and they don't think anything of it because they aren't in person. They might feel like what they are saying is acceptable because it isn't to someone's face. I think this is one way which social media isn't always a good thing. It does help us reach out to many people, but it also has some disadvantages. Cyber bullying and hiding behind social media could be one.

I would definitely say that the internet has altered social capital in a big way. Social capital refers to our relationships in our social networks. The internet has changed over the years and made personal relationships a lot different than they used to be. Even when I was younger, we didn't have Facebook and ways to reach out to many people with social networking sites. The internet has made our relationships less personal because now they are more based on technology. People usually don't have telephone calls anymore, because they text each other, or tweet, or use Facebook messenger.

When it comes to our political system, it seems like most people tend to agree with their own party. It isn't very often that different parties have the same ideas. I do agree with you when you say that homophily makes it difficult to cross party lines, the visual you included helps to show that. I am not sure that this will ever change. Do you think it will be possible for parties to cross lines or do you think this will continue to be a problem?

This is a great point. We definitely tend to become friends with people who are most like us. Whether this be similar likes and dislikes, the same thoughts about politics, etc. It is good in terms of compatibility with someone also. If people aren't compatible it doesn't usually work out between them.

Predictive analysis is important when it comes to many different fields. By using previous data, we are able to look at what future outcomes might look like. In some cases, it might not help, but in others it will. If I want to look at recidivism rates in the criminal justice field, I could look at previous data about what leads people to recidivism. I have looked at that before when writing a paper for another class. At the time I didn't realize I was using predictive analysis. This just shows that social network analysis is all over!

This shows that the foundations and the institutions are both included in the social network.

Social network theory is how people and organizations interact with each other. What do you think consequences could be when it comes to this social structure?

I remember learning about degree centrality a few weeks ago with all of the different kinds of centrality that relate to social network analysis.

That is a lot of nodes and possible connections.

How did they determine that 10 was a small network?

SNA can be useful to see where the "clusters" are in the network that have addictive behaviors. They are able to see where in the network those clusters are by looking at the graphs.

When those in a network are together, it is easy to see who is drinking or smoking. It is not clear who gambles.

Markov clustering-the flow of the graphs

Researchers found the data using a 6 point scale that respondents answered. I wonder if respondents lied when answering the questions. If they did not want researchers to find out how much they actually drink, they just would have needed to answer a lower number. Do you think there would have been a better way to get answers from respondents or do you think this was the best way?

They looked at the clusters within the network had addictive behaviors, which would make sense since a lot of the time people tend to hang out with people who are similar to them. If someone in a network has addictive behaviors, it might make sense that others in the network also have those addictive behaviors.

Do you think in this case, ego and alters would be similar to nodes and edges?

This is how they define social network analysis (SNA) for the purpose of this research.

I would like to look more into this finding and if see if there is more research to back this up. It would make sense.

Sample size that was used.

Clusters-Collection of individuals

I need to look more into what egocentric social network analysis is.

I selected this article because I wanted to look at the relationship of SNA with alcohol use