Lithosphere The Lithium Community

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From Weak Ties to Strong Ties: Community vs. Social Networks 3

Lithium Alumni (Retired) Lithium Alumni (Retired)
Lithium Alumni (Retired)

michael-wu.pngMichael Wu, Ph.D. is Lithium's Principal Scientist of Analytics, digging into the complex dynamics of social interaction and online communities.

He's a regular blogger on the Lithosphere and previously wrote in the Analytic Science blog. You can follow him on Twitter at mich8elwu.


 

Last time I talked about the first stage in any relationship: The formation of a weak tie or, how people become connected. It turns out that weak ties can form pretty much anywhere (in communities and through social networks). If you don’t know the factors that govern the formation of weak ties, or don’t know the difference between a community and a social network, I recommend you reading the following posts in this miniseries before diving into this one.

  1. Community vs. Social Network
  2. How Do People Become Connected?

 

The Value of Strong Ties vs. Weak Ties

Creating a weak tie is the first and the easiest step in any relationship. Other than kinship, nearly all other social relationships start as weak ties. One can argue that even kinships start out weak, and it is only through the frequent family gatherings and interactions that kinships develop into strong relationships. The only difference is that we can’t choose the connections in our kinship. But, we can still choose to what extend we develop these kinships (i.e. whether we want to maintain them as strong ties, or just leave them as weak ties).

 

Since it is the strong ties that are most valuable, the important question is how does a weak tie grow into a strong tie? For the record, I want to state that I am not saying weak ties are not valuable. They definitely do have value. However, the value of weak ties does not lie within the ties themselves, but in their sheer number and diversity.

 

A good example is when you are looking for a job. Your close friends (strong relationships) will probably go through great length and spend a lot of time to help you. But since you only have few close friends, they might not be able to get you a job because none of them can find a job opening matching your skill set. In contrary, your acquaintances (weak ties) probably will only spend few minutes to forward your resume to their HR. But you can have many more acquaintances then close friends. Since one success is all you need, by having many weak ties, the odds that one of them would finds something suitable can be quite high. Essentially, having a large number of weak ties enables us to crowdsource our weak ties for help.

 

The value of strong ties is in the relationship. And their value is far greater than any number of weak ties that you can put together. Just ask yourself, are you willing to trade any of your close friends with 10 acquaintances you met online? How about 100 or 1000? I wouldn’t; definitely not! Strong relationships take a long time to build and they are irreplaceable. I don’t think I need to give you any examples on this.

 

Social Networks Need Communities to Build Tie Strength

Community Builds Relationship_small.jpgAlthough weak ties can form in both communities and social networks, tie strength are built up predominantly in communities. Certainly, most of my close friends (strong relationships) are people who share some common communities with me at some point in my life. These communities may be neighborhoods where I grew up, schools that I attended, research labs where I’ve worked, or special interest groups, such as photography club and badminton club. Although I often meet new friends of friends (through my personal social network), without a community to develop these shallow relationships, our “friendship” would remain purely as acquaintance.

 

Take a look at some of the most successful social network services (SNS), such as Facebook (FB) and LinkedIn. They were created around a natural community where shallow relationships between their members can grow and strengthen over time. For FB, these communities are initially colleges and universities, and later spread into the corporate world. For LinkedIn, these natural communities are companies, professional societies, and industry associations.

 

This is also true in online communities. I’ve certainly gotten to know a few people quite well on Lithosphere (Lithium’s online community about community) and the various LinkedIn groups that I’ve joined. Having a common topic of interest where we can discuss, debate, and learn from each other, is crucial to the development of our relationship. The combination of frequent engagement, deep interaction, and time spent together is what builds strong relationships within communities. As a result, some of these community acquaintances have become my friends.

 

Therefore, successful social networks must have some form of community for their members to interact and build their relationships. Without communities, social networks are merely glorified phonebooks and contact lists. It didn’t take long for SNS providers to figure this out. As a result, we can expect to see an increase effort for SNS companies to build out their community solutions. In fact, FB groups, fan pages, and LinkedIn groups were early attempts to build communities within the social network. They are indeed communities according to the characteristic differences that were layout in Community vs. Social Network.

  1. These groups and fan pages are certainly interest focused, and new members who join them may not know the other members in them
  2. People can be part of many groups and fan pages
  3. Groups and fan pages can certainly overlap, and some groups may have subgroups (i.e. nested)

These groups and fan pages provide community-like interactions, such as sharing news and discussions on the SNS platform. However, these community building interactions are very limited, and they are often inefficient for cultivating strong relationship. The recent launch of FB community page provides further evidence in support of this theory.

 

Conclusion

So the message for today’s post is simple.

  1. The value of strong ties is the relationship itself
  2. The value of weak ties is in their number and diversity
  3. Community (online or offline) is where the weak ties are developed into strong relationships. Although social networks are the hot thing right now, we must not forget the role of communities in building tie strength.

 In my next post, I will cover Stage 3, the maintenance of strong ties. Until then, I welcome any discussion.

 

 Related Blogs

About the Author
Dr. Michael Wu was the Chief Scientist at Lithium Technologies from 2008 until 2018, where he applied data-driven methodologies to investigate and understand the social web. Michael developed many predictive social analytics with actionable insights. His R&D work won him the recognition as a 2010 Influential Leader by CRM Magazine. His insights are made accessible through “The Science of Social,” and “The Science of Social 2”—two easy-reading e-books for business audience. Prior to industry, Michael received his Ph.D. from UC Berkeley’s Biophysics program, where he also received his triple major undergraduate degree in Applied Math, Physics, and Molecular & Cell Biology.
11 Comments
Occasional Commentator matnl
Occasional Commentator

Good food for thought Michael,

 

I'd add a fourth point, namely that strong ties and weak ties are fluid notions based on time and context. You yourself use terms such as "at some point in my life", "frequent engagement", "time spent together". It's like the person in your College group of friends that never got married and the rest of the group that did; at one time that person will ahve more difficulties to relate to the life of the others and what was once a strong tie can peter out. And there are hundreds of thousands of examples like that

 

In terms of online communities, it may be interesting to look at how ties evolve over time as interests evolve or simply the lifestage changes: a tie is not set in stone (but I guess you will cover this in stage 3...)., so it may be just as interest to research how strong ties devolve into weak ones - and maybe do something about it...  Smiley Happy

 

Cheers,

Mark

Lithium Alumni (Retired) Lithium Alumni (Retired)
Lithium Alumni (Retired)

Great suggestion, Mark. I see what you mean, and would also be interested to hear Michael's thoughts on that. Some obvious ones that jump out are proximity and frequency of interaction. If someone leaves the community (online or off), or frequents it (or contacts their friends in other ways) less often, ties tend to weaken.

Lithium Alumni (Retired) Lithium Alumni (Retired)
Lithium Alumni (Retired)

Hello Mark and Mike

 

Thank you for the comments.

 

It is defnitely true that communities are dynamic entities, so are social networks. Ties form, grow in community, and then weaken over time when members leave the communities. It is the natural course of things. That is why there need to be 3 stages of relationships as mentioned in my earlier post. So weak ties or strong ties are definitely based on time and context.

 

I hope I didn't give the impression that they are static. Thank you for pointing this out. Good observation.  Smiley Happy

 

However, nearly all the social network analysis (SNA) out there do not take into account of time. In fact, SNA inherently eliminated the temporal dimension (essentially freezing time) for simplicity. But there is another field called Dynamic Network Analysis (DNA) that takes into account of the temporal evolution of the network. DNA essentially combines SNA with time series analysis from statistics, and it is much more powerful than SNA.

 

You guys are way ahead of the crowd. Next time, I will discuss precisely what happen when you leave a community due to change interest, moving on to different stages of life, job changes etc. That should finalize this introductory mini-series that explore the anthropological roles of communities vs social networks.

 

Evolution of tie strength is a bit tricky, but we can certainly do it, since we compute the tie strength between every interacting pair of users in our community. Will try to put some analysis together and see if the results are interesting enough to merit a blog post. Smiley Happy

 

 

Occasional Commentator matnl
Occasional Commentator

Glad to have been able to add my 2c here Smiley Happy

 

I had never heard of Dynamic Network Analysis before, it seems like a very interesting field of research, thanks for drawing my attention to it!

 

We have been talking about finding the influencers, but if their influence is waning over time, or on the contrary, we miss that their influence is increasing, we miss an opportunity to provide 'added support' to them.

 

Keep up the good work!

 

Cheers,

Mark

@MarkTamis

Occasional Commentator Iceman65
Occasional Commentator

Thanks Michael for sharing a highly valuable blog post with the community.

 

I would like to add that it is much easier and less time consuming to create a large number of weak ties online. The treshold (social barrier) to initiate online interaction with strangers is much lower compared to the offline world. Most of us never talk to strangers in the subway simply because we don't know if we share the same interest. The online community help human beeings to find likeminded people. The total time you invest in a relationship (social capital) will always be taken into account. That´s why it is so easy to reconnect with people you havn't seen for ages.

 

Hans Leijström

Community Evangelist

@iceman65 / LinkedIn

Lithium Alumni (Retired) Lithium Alumni (Retired)
Lithium Alumni (Retired)

Hey Mark,

 

Glad I can bring up an interesting subject to you. It happens all the time for me due to my interdisciplinary background: Math, Physics, Neuroscience, Statistics/Machine Learning and now Social Analytics. I often find solutions to a difficult problem in one domain from a totally different domain of knowledge.

 

With regards to influencers, time (temporal relevance) is definitely very important. Not sure if you read my social media influence model. One important factor in this model that many people overlooked is timing. This post actually give an example using SNA at different temporal slices of the data. This is another way (besides DNA) to incorporate temporal dimensions into the static nature of SNA. Essentially we do many static SNA over time, so you get the temporal evolution of the SNA metrics. This allow you to monitor people's influence over time and see when they are rising and when they are falling. This way you can pick the most relevant influencer for reaching your target.

 

Thanks again for the comment.

 

Lithium Alumni (Retired) Lithium Alumni (Retired)
Lithium Alumni (Retired)

Hello Hans,

 

Thanks for the affirmation of the value of this little research project of mine.

 

Yes, the Internet + web 2.0 technologies definitely make the creation of weak ties much easier (either via community or social network). There are actually some social psychology theory that can explain why that is the case. This particular aspect has to do with a sense of safe distance. This is a topic that I promised that I will cover after I finish exploring the social anthropological roles of community and social network in human history.  See previous post when I talked about The Desire to Connect is a Basic Requirement to move through the 3 stages of relationship lifecycle.

 

I also like to take the opportunity here to address some of your question in email, so others can pitch in if they like.

 

Having been through so many discipline of science and research. I've come to the realization that reality is usually never as simple as any model that people can build or any theory that people can come up with. People can always build  models and hypothesize theories, but none will ever be complete. Good models/theories that tend to stay are those that can explain a lot with very few simle underlying principles. And great models and theories are those that have predictive power.

 

The key is to understand when will a theory/model work, and under what conditions will the theory/model break down. For example, Newton's law of motion works great on earth. But when you are traveling near light speed or near very massive objects that are millions times larger than the our sun, Newtonian Mechanics fails! And you need Einstein's Theory of Relativity to make sense of things. In the ultra-tiny regime, Newtonian Mechanics also fail, and Shroedinger, Dirac and other bright modern physicist develop Quantum Mechanics to deal with small particles like atoms, electrons, and other subatomic particles. There are so many more case that I can think of.

 

But to your point, social media is very new and many people are still exploring and testing their own hypothesis. We are all still learning. Lots of new theory will be proposed and refuted in this pre-paradigm era before the good/great one emerge and stay. So whether it is social objects, social network analysis (SNA), or dynamics network analysis (DNA), they all have their validity. None of them explains everything, but that doesn't mean the theory is bad. Some expains more, but that doesn't meant it's better either (if the theory is too complex).

 

Newtonian Mechanics, although incomplete, still governs all the civil/mechanical engineering that builds the building we live and work in, and the cars we drive every day. Relativity, although more complete is too complex that most people only use it when they have to. You get the idea, is the Occam's Razor, the simplest theory that explain the most.

 

With respect to DNA, not many people use it out there, because it is a more complex theory than SNA and SNA is already quite daunting for some people already. Since most data are stored by date, many people just apply SNA for a series of dates (e.g. daily, weekly or monthly). This method seem to fits better with the data architecture within most organization. I know LinkedIn uses SNA. But I am not sure if FB use SNA, although I'm quite certain that they are not using DNA. However, DNA is more powerful when you are looking at many years of network data all at once, rather than week by week or month after month. Researchers and scientists tend to do that lot more than enterprises, which focuses more on the daily, weekly, monthly operational metrics.

 

Alright, this reply is getting a bit long... But thank you for dropping by and commenting.

 

Carolyn Robbins
Not applicable

Hello Mike, something I am interested in, is  DNA when time and events within a group of communities perpetuate the making of strong ties because of the event and the timing of it.  Is not my social network enhanced when two or more communities come together around this event and it's timing? For instance, if I am interested in a particular LEED standard test analysis that a local green organization, Build it Green has to offer, I might join their community and listen in. Then I might join a similar dialogue going on within the United States Green Building Council, a national community, on the same topic, all because of a seminar on the subject coming to my area. When one program lends it's expertise to another, say in a local testing service for the national standards, then the possibility of my linking to both communities and the interconnectivity between the two communities, allows me greater chances for my own social networking and those people coming together for that event, at that point in time Does that make sense?

 

I am a novice at this kind of thinking, being that I am a designer by trade, yet the prospects of using the 'community to community' linking fascinates me. Isn't it sort of the way you describe the familiarity accessed by one individual because of their community affiliations or interests?   But instead, one community is bolstered because of events and their timing, by those following such events and seeking information from a multitude of communities. Would that not also be a form of Dynamics Network Analysis?

Carolyn

Lithium Alumni (Retired) Lithium Alumni (Retired)
Lithium Alumni (Retired)

Hello Carolyn,

 

Thank you for commenting.

 

I am not 100% sure if I get your point. But my understanding of the situation you described can be sufficiently analyzed simply by social network analysis (SNA). Using SNA you will be identified as a bridge (or connector, boundary spanner, hidden influencers, etc) between the multiple communities. That is, if we compute the betweenness centrality using SNA, you will have extraordinarily high value for this SNA metric. I've written about an example of such analysis in an earlier post "Social Network Insights from Unconventional Graph Metrics."

 

The time dimension is a characteristics distinction between Dynamic network analysis (DNA) and SNA, because all DNA applications deal with changes of the network over time. That is why it is called Dynamic. However, not all problems required the temporal dimension to reach a good solution. So DNA is often not used because most of the time SNA is sufficient. Just as Einstein's Relativity is rarely used for problems we encounter on earth, because Newtonian Mechanics are plenty sufficient for that, even though Relativity is a much more complete theory and much more powerful.

 

DNA as opposed to SNA will show its superior strength when dealing with complex network systems where the entities (the nodes and vertices in a graph) and relationships (edges in a graph) can both change over time. An example of change of relationship is when two person were friends today, but become enemies tomorrow. An example of change of entities is where a person change from being healthy to being infected. Another example would be if a caterpillar metamorephosed into a butterfly. As you can see in my examples, DNA is used frequently in conflict and resolution studies and their simulations, as well as disease propagation models in epidemiology, or animal population dynamics in ecology.

 

So having multiple communities interacting with each other or with actors mediating the interactions between them would probably not be considered as a kind of DNA. Nevertheless, you have posed a very interesting SNA problem that I've recently analyzed. If this subject interests you, I highly recommend that you take a look at "Social Network Insights from Unconventional Graph Metrics." The discussion following that post may also be interesting to you, if my memory still serves me well.  Smiley Happy

 

Carolyn Robbins
Not applicable

Hello again Mike. Thank you for explaining to me the difference between this SNA example and how DNA is different. I enjoyed reading your unconventional graph metrics although at times it was a bit over my head. I do understand how one connector can make all the difference and not be a pro and that is very interesting. What I didn't ask correctly, in my last note is this: because of certain information around a time frame, wouldn't communities shift, and dynamics shift and because of this better exposure is possible? Remember, I am not a social scientist, so I'm out of my comfort zone here. I appreciate your patience with me for this reason.

 

The reason I am interested in these various dynamics within a given time period,  is this: it is my belief, that if I were to track green design events and connect to people before, during and after these events, I have a better chance of making contacts and creating bridges, giving me a better network with new communities, because of the frequency most connections are made around these times. Is there any data that you know of pertaining to this idea?

 

Connecting to people around design events might mean 1. people gain more information, assimilate information faster and communicate more  2. the communities they connect to, shift, and morph, based on these interactions. 3. the communities change in context to the events sometimes just as a butterfly comes out of a cocoon.  

 

This is more accurate I'm sure for certain professions of course. The design communities often alter considerably after a seasonal show of products and styles. This in turn offers new dialogue and in turn new possibilities. Sometimes even new communities develop because of a particular show. I know this is true for a green festival where more LED lighting was shown than ever before. Now new communities develop around LED lightiing products. Is there more possibility for connection and forming strong ties because of this product and in turn because of this event, is my question.

 

I enjoy reading your articles Mike. You make your point so well and with good diagrams and theories. Thank you.

Carolyn

Lithium Alumni (Retired) Lithium Alumni (Retired)
Lithium Alumni (Retired)

Hello Carolyn,


Not a problem. We are all learning in some ways, just in different areas. I'm glad you find my articles informative and instructive.

 

Now I get what you are asking. Yes, communities is not a rigid social structure. It is definitely dynamic, and there are a lot of fluidity in them. People come and go, and topics of interest shift all the time. I've definitely seen this in our data. For example, a tech support community can shift it focus to be more marketing and sales driven after a product launch. Likewise, an enthusiast community can behave more like a support community after some bugs were found. All these time sensitive events are responsible for the shift in the community (ie bug report, product launch).

 

These shift certainly brings in different groups of people and allow different sets of people to interact. So there are certainly more chance to create weak ties. However, to develop these into strong relationships, members of the community still need to invest the time into building the relationship. But, if you are asking the possibility, then yes. I've definitely seen what you are describing in our data.


Either way, thank you the inquisitiveness and for posting your question here.