This is interesting in terms that I can totally relate to it. When we follow someone on Twitter, we do because we have shared interests, we like them,and we would like to be exposed to the information they might share. We often live in ideological echo chambers. We share information that conforms with our own ideologies. So, I understand the strong homophily in follower and retweet networks. However, within the echo chamber of social media, it only takes a few abusive messages to start a firestorm. When we mention someone, we are not necessarily following them or retweeting them. It can be to draw attention for present a different point of view than theirs. For example, if we go on any of Trump's tweets, first few replies with his mention are always contradicting his opinion. I think that makes sense.

Node attributes

I think this is a great practice when it comes to analyzing data that is associated with a specific tweet. Often, users have tendency to use the random hashtag that may not be relevant to their actual tweet but they use hashtags that may be trending to gather attention to their own. I have struggled with this in one my projects.

Wow. That must be a treasure cove of the data (Unfortunately also documented ways for radicals to find sources to join and get involved). It seems interesting.

Homophily

This is very relevant to our week's reading. SNA can be a really valuable tool to understand the network of criminals and online extremist groups. I came across a study for this week's blog, which suggests that SNA of crime networks can reveal links to people who are not necessarily criminals or directly associated with them. However, they have a high potential to get involved in criminal activities. Highly debated, but, such techniques are used to monitor those with high probability of getting involved and has often proved to be useful.

The best example of this is white supremacist rally in Charlottesville, VA. It started out so casually just like any other FB event. SImilarly, terrorist organisations have an increased opportunity to spread their ideological stance and to recruit new membership. They have seized upon technological advances in Internet media distribution and online anonymity.

As I mentioned earlier, the institutions with highest eigenvector centrality are those that are situated in triangle area. It would be interesting to see how their geographic location affects their position in the network.

It would be interesting to see the evolution of foundation's influence on education policy reform over the years. How they evolved from being an invisible force in the education policy reform to more publicly visible force as stated by Eikenberry.

This seems like a new term.

This is interesting. Specifically in this case of healthcare conversation, people are definitely more likely to take advice or consultation from the organization or people with most following. It could be because we are inherently likely to believe those that are followed by many others.

This is interesting. we can see that non-healthcare organizations, providers, and advocacy & engaged consumers have strong ties with average consumers.

Measuring the strength of ties

use of in-degree and out-degree centralities to measure understand the structure of network.

They used SNA packages NodeXL and UNICET for the visualization and measurement. I am not sure how NodeXL exactly works but from what I have read it feels like it is very similar to Gephi.

The way they categorized the tweets into different fields.

Data collection method to collect data/tweets from Twitter. They say that the data set has 125,907 unique tweets. I think they didn't include any re-tweets as well.

The goal of using SNA in this study.

The role on SNA in this study. The researchers utilize SNA to study the underlying themes in the health related conversation on Twitter. They try to identify the influential nodes in the network structure.

Node attributes and betweenness centrality.

Definition of Community of Practice by National Institute on Disability, Independent Living, and Rehabilitation Research.

Communities of practice are formed by people who engage in a process of collective learning in a shared domain of human endeavor: a tribe learning to survive, a band of artists seeking new forms of expression, a group of engineers working on similar problems, a clique of pupils defining their identity in the school, a network of surgeons exploring novel techniques, a gathering of first-time managers helping each other cope.

The global digital world. Shared interests points to characteristics of homophily.

If we consider the number of hashtags and health topics on the Twitter, creating a network of extensive number of nodes and links may become strenuous or even impossible. Here, we will have to decide the network boundary as it may pertain to our specific research question.

Unfortunately, this is very true. We can say the same about fake news. Such practices can contribute to hurting the validity of the overall data. The Twitter data is not collected with systematic investigation or systematic collection methods. This data collection method heavily relies on “public opinion”. I do think that if one wants to find general public sentiment or general public opinion, this is a great way to do it.

This reminds me of readings a few weeks back where we learned how social networks are used in giving warnings about public epidemic outbreaks. For example, bird flu. In fact, the SNA is also used for need of a disaster response via social media.

Absolutely. There are hardly any topics that are not discussed on the Twitter. The networks are created when the like-minded twitter users retweet each other’s tweets, creating a unique social network.

I think this is a great idea. I have conducted a project before where I collected data by querying a specific research terms on Twitter. Twitter is a treasure cove of data. Do you think you can use this data collection method for your research projects? If so, what type of hashtags or terms would you query?

I came across this article while doing research for last week’s blog. I know this is not a straight forward SNA article, but I found it very interesting since it is a combination of SNA and content analysis. Considering this week’s readings on different data collection method, I found their approach of collecting data from Twitter very unique. In this context, content analysis refers to analyzing tweets and their content. Recently, content analysis is being used in various fields. Even social researchers are taking this opportunity of exploring already existing data. Do you think you can use the combination of both SNA and content analysis in your own research field?

This reminds me of analysis by Yang et al. They suggest that often social network that includes many other drinkers or even one drinker, an individual's risk of relapse increases. I wonder how this analysis may apply to egocentric network. They also mention how Alcoholics Anonymous (AA) help drinkers with their social networks, they help reshape their network with those who may be role models. They try to reduce pro-drinking ties and increase pro-abstinent social ties. I feel like applying SNA in such networks can really produce positive results on both individual and community level.

I think this week's readings by Yang et al were really helpful in understanding how addictive behavior can spread through the network. A study by Cohen and Lemay (2007) suggested that there is a link between having less diverse social networks and getting influenced into drinking and smoking. It will be really interesting to see the results of this study. Especially, how the network dynamics might change since this is a egocentric network.

I find this really interesting.

When I think of villagers, I think of less weak ties. But, I could be completely wrong.Can strong ties play a role in here?

I think this is brilliant and relat-able for us since most of us are more familiar with academic domain in the United States.

Universities and academics.. both nodes? Or can universities work as links for academics?

Hi, I wasn't able to find the article.

This relates to Weber's functional rationality of bureaucratic organizations, where rationality is following the rules and regulations for the efficient functioning of the organization.

This also reminds me of Michael Hechter's article on Sociological Rational Choice theory in 1997. In describing how members of church face a collective action problem, Hechter explains that strict churches often impose 'costly and esoteric' requirements on their members, which helps them solve 'free riders' problem as only those who are really committed to church will join the church, making churches more successful and strong.

ADE and Collins both discuss the problem of 'free rider' in their books. This issue was formulated by Mancur Olson in 1965. Olivia does a great job of explaining how rational actors 'free ride'. In my opinion, many of us are guilty of 'free riding'. At least, I am. The basic assumption behind it is, "whether I make a contribution to the cause or not, the output will not change, then why to bother?" Collins explains the 'free rider' problem by giving an example of free bus service and ADE describes by giving an example of the fight for the protection of natural environment. In a rational mind, it makes sense to not contribute to some cause if the benefits will be free anyway when other people contribute to it. Olivia doesn't mention here but both Collins and ADE explain the different solutions offered by rational choice theorists which can help prevent 'free rider' problem. For example, selective incentives - when those who participate are rewarded exclusively, and negatively sanctioning those who do not participate in the cause to the public good.

ADE provides the same example for describing the role of trustor and trustee in an exchange. Olivia does a great job by presenting this example, as in my opinion, all of us can relate to it because all of us have been through similar kind of situation where we had to weigh our gains and losses. If the gain in this situation outweighs the possible losses, one might consider the risk worth taking. The 'trust' in another person depends on the rational calculations which are based on the information available on another person (their reputation of being trustworthy). In the case of Julia and Malika, Malika will be able to make her decision based on a rational calculation of if she can place a bet on Julia's trustworthiness. As given in ADE, it is of advantage for Julia to be trustworthy to receive benefits ($200) and it is of advantage for Malika to trust Julia to when possible gain outweighs the possible loss.

The content in ADE emphasizes that exchange theorists focus their attention on the strategic decision-making of the individuals and how these particular decisions can have an impact on social relationships within small groups. On the other hand, rational choice theorists examine how these strategic decisions and rational interactions between the individuals can have an influence on group dynamics in broader social conditions by "producing group solidarity, norms, and control of resources" (ADE).

Yes! Many businesses associated with providing the necessary services and products for the wedding are benefited when two people decide to tie a knot. This reminds me of Collin's explanation of 'conflict tradition'. Collins states that from 'conflict tradition', we learn about 'the economics of culture'. He also goes further and describes that 'ideas are weapons and their dominance is determined by the distribution of social and economic resources'. In my opinion, this relates to the recent need (trend) for doing something "unique" & "different" than others. People are ready to pay more than usual if the service or the product they are getting is unique. That involves services and products from all the different parts of the Wedding Industrial Complex.