is it too late?

will go

maybe this one

will go to this one

I wonder if this is not the dialectic of the modern network society that is pushing for change?? I am thinking marx here.

This is powerful and important...how could we show this using Twitter data?

I think this duality is what is most captivating and perplexing about the network society. Could this be the ying/yang of a society governed more by networks and less by bureaucracy?

Do you think the internet has facilitated this?

a form of stalking? or fascism?

I also wonder if digital can work to consolidate power. We tend to think of disruption as a move towards more equality but what if it is a move towards fascism?

And can circumvent points of control and power making bureaucracies less important for command and control.

Do you think networks are also breaking down bureaucracies?

I wonder how many profiles in the 3,389 tweets? Did the automate the review and capture of the details? Or did they review each profile by hand?

Again, take note of these research questions. Look back at the literature review to observe how theory and research was used to set up the basis for these questions. When the answer is found, the theory/research will be used to interpret it and discuss the importance of the answer.

Take note of this research question. It is a descriptive question but it is based in theory.

Think of these as clusters. We will do cluster analysis in a week or so. These are attributes of nodes.

I wonder what the methodology of this paper was?

these are node attributes. I wonder how they derived them from twitter. Hopefully this will be spelled out in the methods.

I think you have this backwards; nodes are people connections are between them.

Are these males playing as females and females playing as females in each of these groups?

This is not really a SNA question...more a statistics question.

This is not really a SNA question...more a statistics question.

This is a subjective decision on how to display the data. You can make these decisions based on how you want to describe the network.

You will learn this in the second part of the class.

Notice, the network is constructed through the perceptions of the ego. This is totally fine but it does require analytical attention.

That is A LOT of people! Can you name 30 people with whom you had a relationship of some type in the past year?

SNA is an excellent tool for intervention planning. By providing a map of the interactions, interventions can target specific locations in the network for change.

This is an excellent use of SNA. I have never seen it used chronologically to map feelings. I love it!

I am not sure I understand this? Can you be more specific?

Did they look at any outcomes of the different circuits? For example, did Circuit C have more successful prosecutions? Or less re victimization? Any way of measuring whether one network was better than another?

Good! You are beginning to think about the usefulness of SNA as a tool AND as a way of asking research questions.

You need to briefly discuss the infographic to help the reader understand what it is saying. Just posting an image does not really connect it to the narrative.

Begin to think about the network and relationship between EITHER churches or preachers. Do preachers live near each other? Children go to the same schools? How do they know each other beyond the church? Is there an annual meeting of preachers?

Begin to ask yourself...where is the network? How do they link to one another? How do they know each other?

The churches should be the node and the preacher should be the link. How would you find out who speaks at which church? Is there a listing?

Is there an online discussion group or Reddit group for these people?

Again, this does not really define the measures.

This section is vague and a bit repetitive. What exact does degree measure? What way is closeness influential? What specifically does betweenness focus on?

Patient outcomes seems key! I would also wonder about how this relates to the amount of care able to be delivered in the home since that has positive health outcomes.

Interesting...did it correlate at all with positive health outcomes?

This is a bit unclear...how was degree measured? More doctors?

This is interesting...how was this measured?

Why did the network thin? Less happiness? Not quite sure I understand the measurement here.

Node centrality does not really provide this information. This info is provided by structural measures. We turn to those after the small paper.

Yes. This is the correct way to understand the role of node centrality measures.

Excellent question. Can you use this research methodology in your research? Does it give you any ideas?

Who are these people? Need context for the uncultured reader :-)!

Excellent point! This is key!

Do you see any possibility for your own research?

Would love to see a personal conclusion where you reflect on this information as it has to do with your research or any other sociological observations.

This is an example of a SNA theoretical construct used for measurement and research questions.

I wonder what media they are consuming?

I am not quite sure how team cohesion is being measured by the soccer picture? Where is the network? I see the path and I see a rendering of a play. Did the researchers look at the off field network? I am unclear on this.

Closeness is not measured by 'in degree' or 'out degree'. Closeness is a centrality measure and can take into account the direction of a tie. But in degree and out degree are measures of degree.

Without references, 'we' don't know. The reader must take your word for it.

References?

'are' not 'is'

This seems a bit short. No real conclusion or analytical exploration. Need to do a bit more than describe. Connect to data. Research. Explore new questions. Discuss the impact of the theory on the lives of people.

I think this is a critical question for the new subfield of digital sociology. What is the impact of the new online world on our corporeal lives? Good? Bad? Both?

Could you detect this in a discussion forum? How could you define homogeneity in a way that could be measured via discussion?

Excellent point. Has any research been done to compare the actual social networks of rich and poor kids? For example, asking a poor kid to name five people she would go to for advice and asking a rich kid the same question. Has that been done?

Good point. How can we quantify this? Can you include some data to show how we are leading parallel lives?

Is this your project? I could imagine a knowledge diffusion question. If someone goes through this program, how many people do they influence?

Again, any research? If not, can you do it?

Is there data on this? What research has been done looking at networks and bystander intervention behaviors and/or beliefs? This would be a very interesting project.

Yes! This is the cost of geographical, educational and social marginalization. Different economic groups travel in different circles which reproduces their current economic position.

Again, I think the theoretical point behind social capital is that all relationships can have some value but it is also to show how some connections have more value than others. Certainly, knowing your neighbor or sharing stories with the clerk at the 7-11 is helpful to those how live in poverty. But, for those who are born at the top, they know the head of the corporations so the pay off is bigger. Both pay off but one pays off more.

I am not sure this is the best example of social capital in that these are family relationships not social relationships. I think the idea of social capital is to show that other relationships beyond family or blood have value.

I think this is one of the central questions of the new subfield of Digital Sociology.

This is an excellent research question! Does access and use of social media improve the mental and emotional health of older people/

Where? Can you provide a citation?

These are empirical assertions. Provide data to support this point.

What are the benefits of this? In terms of cost/benefit, if these ties pay off just as well as in person ties without the expending of as much time and labor, is that a net positive? Or is something lost in the ease of contact? Again, what does data say?

Do we know this for sure? Or is this our perception? What does data say?

What is an economy of friendship? Your term?

big sentence! The issue with Putnam is a question of level of analysis. Can an individual level measure describe a social system? But don't we do that all the time. This society is more or less healthy based on aggregate measures of individual health?

data?

This also may be a question of homophily vs heterogenity. Students pick probably more homogeneous groups. Do they produce a 'better' outcome?

Are these students building social capital? Do these ties follow them outside the class? Do they draw on these ties for other purposes?

You also have a lot of smaller networks embedded in the larger network. It might be interesting so map how each group interacts, i.e. leader or democratic or something else to see which kind produces a 'better' outcome.

don't understand this visual? How does it relate?

How did they define this?

Almost too easy and it does not push us towards difference.

Are weak ties now more important than strong ties for seeking and finding social support? I am thinking of discussion boards/forums.

This is a new line of research and theory!!

These are the new questions raised by the digital world. What does digital social capital look like? Have our new ways of interacting replaced bowling? Are we still as social only in different ways?

Or how many non-participants does it take to fracture the community and/or network?

I would love to see you submit this to the new DigiSoc@VCU Medium.com page. You would need to strengthen the conclusions. You discuss is so very powerful up until the end. The it falls a bit flat. What are the implications of this new form of digital social capital? Are there other ways of mapping and measuring it? How can SNA advance this literature? What research questions come out of the alt-right study? These are the type of questions you should explore in your conclusions.

I am disappointed they did not present a sociogram of the network. An image of the network would have been MUCH more helpful in being able to conceptualize their points.

Symmetrically = no direction Asymmetrically = direction of the ties

Indicates directionality of the tie and strength.

Think about this for your own research. Pay attention to the methods so you can begin to think about how you will collect your own data.

Weak ties also induces heterogeneity in knowledge.

I wonder about weak vs strong ties. This strikes me as a difference, i.e. heterogeneity. I also wonder about knowledge network analysis...maybe this is about how knowledge travels.

How so? Can you expand here a bit?

I LOVE LOVE LOVE this. It tells me you have a purpose to your blog post. You have an audience in mind and you understand the goal here is to communicate beyond the academy to inform a broader public. This is what public sociology is all about! Excellent!

FB finds we are separated by 3.5 degrees of separation!

Why a small world here? Does the friend live far away? Thinking about the ways in which details matter to really demonstrate a point.

Could this be a central question for your NSF grant?

When I read this blog, I thought about how knowledge comes to mature academics. When we are junior, we spend a great deal of time reading the specifics of articles and texts. Do we do the same as senior academics? Or does knowledge come to us via our networks? We talk to people at conferences or exchange ideas via email or other digital means? Just wondering if knowledge networks change over the life course of an academic?

This is the entire premise of LinkedIn. I wonder if Granovetter gets a cut of the LinkedIn profits?

I like this statement. Can we think of uniqueness as also diversity? Do those who benefit most from weak ties have more diverse ties?

I wonder if people with social anxiety fear weak ties more? What is the psychological relationship between strong and weak ties? I also wonder about social mobility--do those at the higher levels have more weak ties? Spend more time on their weak ties?

I wonder if those who are more aware of their weak ties or have more contact with more ties have higher or lower social anxiety? We always think of social support as a net positive but is there such a thing as too much?

FB used its data to show 3.5 degrees of separation!

What do you think some of those changes are? Do you think we recognize the number and value of our weak ties differently than we did prior to social media?

This could be a small paper study!

TRUE! We can't know everyone REALLY well. In fact, we have more weak ties than strong.

FB research shows that we are connected by about 3.5 steps! I wonder if the world is getting smaller?

Here is a SNA measure linked to an outcome. Cohesion leads to stronger team performance. SNA can help map and measure this through comparisons.

YES!

This is different than traditional social science which focuses on independent and dependent variables. For SNA, all data is related to all other data; no variables are mutually exclusive. This is why SNA is fundamentally descriptive.

This is what we mean with the term 'sociological imagination'. Theory allows us to 'see' below the surface of society and to understand the invisible network of norms, values, structures, institutions and systems of inequality that shape individual choice and behavior. In this way, SNA should be fundamental to sociological methods.

We will be doing this in the second half of the class. The first part looks at nodal metrics.

Network should be the Time word of the decade!

Bystander intervention could be contagious much like other healthy or unhealthy behavior is; we know obesity is contagious. Bystander intervention could travel as well.

It is an analytic shift that requires you to rethink how you ask research questions. Questions are more descriptive than predictive.

This space is fundamental to sociological theory. It the place where social forces exert power in the lives of individuals. SNA seeks to capture that influence and power.

Sociologists use the term 'sociological imagination' which refers to our ability to 'see' below the surface of society and to understand the invisible network of norms, values, structures, institutions and systems of inequality that shape individual choice and behavior.

What type of outcomes can SNA be used for? Thinking about this will help you think about research questions.

The challenge of descriptive research for traditional social scientists is the change in how questions are asked. Questions should focus on describing something in a deep and informative way. Traditional social science relies more on predictive and inferential analysis. Can I predict what will happen if this variable changes in this way? Research questions identify the independent and dependent variables. SNA does not have IV and DV so questions are more about revealing what is going on underneath; i.e. how do the members of corporations know each other?

The space between individuals is where the social capital resides. Where peer pressure occurs. Where norms are exchanged and regulated. It is an important space :-)!

But does it actually work? What does the data say? Can SNA be used to answer that question?

Can you expand here?

I am a bit confused here...SNA focuses directly on the space between individuals. Our relationships live in this space. Traditional social science looks at the characteristics of individuals to see if they vary according to another variable, i.e. independent and dependent variables. There are no IV and DV in SNA, at least in basic SNA. More advanced SNA blends statistics and SNA data.

It is the blessing and the curse of SNA--it can do so much but it can also do too much. The analyst has to be clear in their question, defining what is a node and what is a link. It can get even trickier since nodes and links can also be reversed. Sometimes a node can be a link and a link can also be a node!

This is fundamental to sociology as a discipline. We call it peer pressure, social support, social capital, norms, etc. This is why many who use SNA see it as the best methodology for doing sociology.

in-degree and out-degree

The focus of analysis is on the space between the individuals, i.e. the air, rather than on the character or traits of the individual. The traits and character can be used to understand what is going on in the relationship but SNA measures the links not the nodes.

Haha...Mike and I did the training for the RPD!

Excellent! Therefore SNA requires three points of data--Node A, Node B and the link between them. There is no dependent and independent variable. The means there is no inferential or predictive questions. Questions are more descriptive and comparative.

While traditional social science focuses on the characteristics of the individual, SNA takes the idea of social pressure and social forces seriously and analyzes the space in between individuals, i.e. the 'air'.

Could Rush be a link not a node?

Can we demonstrate this with data?

What a great way of using SNA to compare two competing ways of knowing. How would you collect data to show the different flow of information through these networks? What what would you be looking for? What would the node be? The link?

I think this is the main methodology for digital sociology. We just don't know it yet.

SNA requires three points of data: Node A, Node B and a link between them. The focus of analysis is on the link such that A and B are not independent. Predictive requires an independent and a dependent variable.

This is what the word recursive means. When we say something is recursive it means mutually reinforcing over time.

Networks are what sociologists talk about all the time but our methods don't fully 'see' them. We find relationships between variables--i.e. race and class--and then discuss how this relationship is due to social forces. Networks are the way in which social forces exert power!

There are three points of data in SNA; node A, node B and the link between them. Traditional social science requires only two--independent variable and dependent variable.

It is this contortion that will make it hard to ask SNA driven research questions. You must think about describing patterns rather than making predictions.

This is what makes SNA so different. Usual sociological analysis holds the individual as the unit of analysis. Even when looking at the institutional level, the unit is usually the individual. SNA asks you to see, analyze and conceptualize the space between individuals, i.e. air.

It also reveals the distance between formal norms and informal norms; theory vs. practice.

Think of this question in Week #3 when you read 'strength of weak ties'. Do people with large FB networks have better job prospects?

Your challenge will be to make these type of questions more specific and relevant to digital sociology.

This is what makes SNA so different. Usual sociological analysis holds the individual as the unit of analysis. Even when looking at the institutional level, the unit is usually the individual. SNA asks you to see, analyze and conceptualize the space between individuals, i.e. air.

Each of these could be a network. You could compare the networks to see if they are structured differently as a way of trying to understand who is most responsible for the push towards Academic Capitalism.

What do we mean by knowledge based economy?

Why are they not living? They are certainly dynamic, have needs, pressures and structures and exist beyond the singular person?

It also may be that certain ways in which networks function produce and reproduce inequality. See Power Law question.

Isn't this the foundation of the sociological imagination? Why is SNA not more central to sociological methods?

This is called the horizon of visibility. We generally know who are friends friends are but it is really hard to know who are friends friends friends are. SNA and the internet give us sight beyond the horizon. I wonder if that makes a difference in our choices or social capital?

That there are patterns in the structures of networks that cut across nature, people and technology makes me wonder about human control, free will and agency. Is life controlled by networks rather institutions, culture and choice?

This is called the horizon of visibility. We can see our friends friends but it is really hard to know who our friends friends friends are.

The internet has revealed what has always been the fabric of society--human networks. It has made it easier to see them and understand how deeply we are embedded in them.

SNA also gives you the ability to see beyond your social horizon. It is easy to know our friends friends but it is very hard to know our friends friends friends. Much less our friends friends friends friends. But do they influence us in some way? How many steps out does influence remain? Is there a way to measure this in your small paper?

As I think about this, I am always a bit perplexed as to why SNA is not more foundational to Sociology. SNA reveals that which is very fabric of our society. Why is is not more utilized as a methodology? I suspect it has something to do with how hard it is to collect data.

These outcomes have been linked to friends and social contacts. Research asks how many friends or how often do you socialize? While this hints at the issue of networks, asking for lists or numbers does not produce network data. You have to find the links between people and between those people that people know.

Social networks are like 'air'; they surround us and we don't even see them. To me, this is what makes the methodology of SNA harder to grasp; how to access the data for 'air'? How to understand the discreet influence of 'air'? But once you see it, you can't unsee it! Very powerful!

Networks are like 'air'; they are all around us constantly. This class will not only help you see networks but also to see the complexity of them. They are growing more complex and more important to how our society functions. I often wonder if networks are not replacing institutions.

This is what is called 'native data'; data that is built through everyday behaviors.

What would be the links between these people? If you asked someone to list their friends, you will get lists which produce a star network. There needs to be a second round of questions involving friends of friends. Getting network data requires asking interrelated people.

How would you analyze this via SNA? What networks would shape bystander intervention? Networks at the party? Personal or friendship networks? Networks on campus? Could you think about doing something on this for your small paper?

This perspective of looking at individuals in categories is the foundation of statistics--two variables that are mutually exclusive and the goal is to see if they relate in any way. SNA is very different--all variables are related and dependent. That is why SNA is descriptive--can't do predictive without mutually exclusive variables.

I think this is why we are so fascinated by social media; it has revealed what has always been under the surface. To me, networks are like 'air'; all around us but hard to see. SNA reveals the air.

We will discuss how networks can produce and reproduce inequality. It is called the power law.

This is what is so hard about democracy in the modern digital age. Habermas tells us that democracy requires an open and free exchange of idea in a equally accessible public space. While the internet is not entirely open, free and equally accessible, it is very close. Yet, we have lost the ability to vet, validate and trust most information. What does that mean about democracy in the modern age?

I think this is why they are hard to analyze...it is like trying to see and understand air. It is everywhere so it feels so normal and invisible. Networks, particularly human networks are the same. Humans have always been embedded in networks; we live, thrive and die in networks. They are another form of 'air'. The difference is that today, social media has made them more visible. We can now see them and analyze them in new ways. Hence, why this class is online :-)

I agree. These ideas are foundational for sociology! When I lecture in Intro to Socy, I spend a great deal of time on trying to help them grasp the fundamentals of the sociological imagination. While network theory may seem like common sense, it directly challenges the ideology of individualism and pull yourself up by your bootstraps. If you accept that others influence you, then you have to begin to accept the realities of privilege and discrimination. This can often be too much cognitively, particularly for privileged students who prefer to think of their benefits as wholly earned. SNA reveals how inequality is produced and reproduced.

I think this is a central question of our age--does social media make us happier? Increase democracy? Smarter? And the question always changes because the technology always changes. I now wonder about SnapChat. It functions a bit differently but with the same goal of connection. Does it produce better feelings than FB? Worse? More vicitimization? Less?

Use these questions to drive what article you bring in to annotate. Or bring them into the reflection. The questions you are asking focus on dynamic network analysis. We will not do any of that in this class but you can find a lot of work on this way of doing SNA via Google.

When I lecture in Intro to Socy, I spend a great deal of time on this statement to help them grasp the fundamentals of the sociological imagination. While network theory may seem like common sense, it directly challenges the ideology of individualism and pull yourself up by your bootstraps. If you accept that others influence you, then you have to begin to accept the realities of privilege and discrimination. This can often be too much cognitively, particularly for privileged students who prefer to think of their benefits as wholly earned. SNA reveals how inequality is produced and reproduced.

I think this is why they are hard to analyze...it is like trying to see and understand air. It is everywhere so it feels so normal and invisible. Networks, particularly human networks are the same. Humans have always been embedded in networks; we live, thrive and die in networks. They are another form of 'air'. The difference is that today, social media has made them more visible. We can now see them and analyze them in new ways. Hence, why this class is online :-)

Is there a way to compare what these networks look like? Could you compare the friendship network of a grandparent, parent and child? And compare the ways in which they maintain those networks? I would also include a strength of ties. I could see the grandparent having stronger ties but fewer. The child having more but weaker. Just thinking of ideas for your small paper.

Is this an idea for your small paper? How have others mapped and measured what interactions take place at social gatherings? Could you reproduce this for your small paper?

What SNA will help with is not only creating visuals of networks but providing metrics to be able to understand the different roles and positions each nodes plays in the network as well as comparing different network structures.

I think this is why they are hard to analyze...it is like trying to see and understand air. It is everywhere so it feels so normal and invisible. Networks, particularly human networks are the same. Humans have always been embedded in networks; we live, thrive and die in networks. They are another form of 'air'. The difference is that today, social media has made them more visible. We can now see them and analyze them in new ways. Hence, why this class is online :-)

This is also the power law; it takes links to get links. Power law is how inequality produced and reproduced in networks. Check it out!

I wonder if you can repeat this experiment in some limited way for your small paper? Only digitally. Has anyone done this?

I too believe this is common sense. This is why I am always struck by how tightly people hold to the 'pull yourself up by your bootstaps' model of thinking. It also reveals how you can tell ideology from practice. Those who profess the bootstraps also move their children to good schools and neighborhoods b/c they know this is common sense. Does this make sense?

This is the essence of sociology. And is the fundamental challenge to the logic of individualism and neoliberalism.

Sometimes this new framework feels a bit overwhelming to me because it asks me to 'see' the world differently. I am use to seeing through discreet categories containing individuals; i.e. race, class and gender. SNA is asking me to see it through interconnections and links--the stuff behind the categories. Sometimes it feels like I am being asked to see 'air'; I know it is there, but it is all around me--ubiquitous--which makes it harder, and more intellectually challenging, to see.

It would be interesting to discuss these similarities. From my non-chemist brain, I see more pattern and regularity in the chemical than in the social. Reminds me of NDTyson quote that physics is easy and sociology is hard because of the nonlinearity of human behavior.

Sociologically, this law of networks is how inequality is built in and reproduced, i.e. it takes money to make money. People gravitate to those who already have connections, power or influence which gives those people more power, connections and influence.

Do you know how to measure power law? I have some data that I am sure follows a power law because of the curve of the line. I don't know how to calculate it. I am just eyeballing it. Is there a better way?

Isn't all sociology really about networks? Why don't we see them?

How does this perspective differ from a non-network perspective?

I will be posting videos for the next week on Sunday. Look for an active link each Sunday.

more directions on how to do this are forthcoming