Marc Smith, Lee Rainie, Ben Shneiderman, and Itai Himelboim found six conversational archetypes on Twitter conversation networks. We are going to discuss how and why these different archetypes are formed and will mainly focus on the influence of infomediation and vertical integration. First, we will choose two different types of graphs and discuss their properties. Then will analyze and synthesize the graphs based on the concept of infomediation and vertical integration.
1 #SoMe4surgery Twitter
The first graph located at https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=169358 represents a network of 681 Twitter users whose recent tweets contained #SoMe4surgery, or who were replied to or mentioned in those tweets. #SoMe4surgery constructs a virtual collaboration community for those medical experts, professors, especially in the surgical aspects, which can also be proved by the top 10 influences in this network.
According to the Conversational Archetypes, these discussions in the above figure can be characterized as “Tight Crowd”. One proof is that in the Tight Crowd networks, there are unique topics or technical terms that are unlikely to be discussed or used by people who do not belong to the virtual community. And that is what bring these people into a cohesive population. In the #SoMe4surgeon network, most people in these discussions are densely interconnected by the use of URL and hashtags.
The most frequently mentioned URLs in the entire graph and in the largest groups in the #SoMe4surgeon network are displayed in Figure 1. The top one URL links to the twitter which calls for the participants in the community of #SoMe4surgeon. The overlap among these lists is an indication that groups share a common interest of similar topics such as surgery, healthcare collaboration, collaborative practice or surgical research.
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Top Hashtags in Tweet in Entire Graph
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Top Hashtags in Tweet in G1
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Top Hashtags in Tweet in G2:
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Top Hashtags in Tweet in G3:
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Top Hashtags by frequency of mention in the three largest groups in the #SoMe4surgery
The common focus is also showed clearly in the most frequently used hashtags between different groups. The top one hashtag in each group is also the top one hashtag in the entire graph, which refers directly to the name of this tight crowd –“soMe4surgeon”. And different crowds here have focuses on some specific hashtags, but at the same time, they also share some common hashtags, like #surgerytraining, #opensourceresearch, #escp2018 etc.
The several tight crowds here are naturally formed by the interest on different subtopics of the communities. Although there is a clear formation of different crowds or communities, they are not isolated from each other. For the“SoMe4surgeon” network, the sub-groups represent the sub-groups of the member who focuses on the different part of the surgery, like surgery training, colorectal surgery or surgical research. These topics are distinctly different, but they are not in conflict.
2 #CommCharterAcad Twitter
The second graph located at https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=171086 represents a network of 1,108 Twitter users whose tweets in the requested range contained “CommCharterAcad”, or who were replied to or mentioned in those tweets. These discussions can be characterized as “Broadcast Network”. There is a very distinct hub in these discussions as well as a spoke structure. Many people in those discussions repeat what prominent news and media organizations tweet and generally, they are only connected to the hub news source. The interconnections between individual users are very weak. The hub is the twitter account @CommCharterAcad. It works as the major source of news and technology developments that are related to the commonwealth charter. On the left side of the graph, we can see there are people who are linked only to the hub twitter account. On the right side of the graph, there are denser groups of people who are interested in different aspects of the topic #CommCharterAcad, and discusses within small groups. In addition, we can notice that Twitter users in different groups use very similar hashtags and terms, like #schoolchoice, #ccagrad, #wearecca, etc.
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Top Hashtags in Tweet in G1
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Top Hashtags in Tweet in G2
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Top Hashtags in Tweet in G3
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Top Hashtags by frequency of mention in the three largest groups in the #CommCharterAcad
By Smyrnaios, “the main objective of the oligopoly is to control infomediation, defined as the set of socio-technical mechanisms such as software, services, and infrastructures that provide internet users with all types of information online and connect them with other users.” The second graph of hub and response interactions can be best understood by the goal to control infomediation. The distinct importance of the hub twitter account is a good example of how oligopoly tries to control infomediation. They broadcast news and information from a central platform, making them available to huge amounts of the audience and making the audience repeat or discuss that information. The hub is an intermediary media between the demand for information from the audience and the supply of information from the hub. The hub select and priorities the information before broadcasting them. The production of the information is centralized and are made to the public via the Twitter platform. The response and discussion among the audience can in return be analyzed by the hub to further optimize the future marketing. Based on these characteristics, I think infomediation empower the network communication because it can make the content in an efficient way and then reach a wide audience. The downside of this type of network is that the general public has very little control over what information they will receive. They must rely on the credibility and ability of the central hub to get the information they are interested in.
Besides infomediation, vertical integration also plays a very important role in forming those network type here. “Vertical integration is defined as bringing together a complementary set of business activities that constitute a production chain under the same decision-making power.” When the oligopoly controls the four subsets and markets of some infomediation infrastructure, i.e. operating systems, consumer electronics, telecommunications networks, and data centers, they hold great decision-making power and control the supply chain. Therefore, they can choose what kind of content they want to distribute, how they plan to reach the audience, and who they want to reach. Those decisions combined can influence all aspects of the network, for example, the interconnection between different users and the formation of the crowd inside certain communities. In the first graph we analyzed, we can see the crowds are formed based on different interest on the various topic.
To conclude, I believe the precise distribution and the selection of audience to reach are the keys behind the formation of those different types of networks. The conversation networks proposed by Smith et. al. are the inevitable outcome of infomediation and integration.
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Reference
Rainie, H., & Wellman, Barry. (2012). Networked: The new social operating system. Cambridge, Mass.: MIT Press.
Smith, M. A., Rainie, L., Shneiderman, B., & Himelboim, I. (2014). Mapping Twitter topic networks: From polarized crowds to community clusters. Pew Research Center. Retrieved from http://www.pewinternet.org/2014/02/20/mapping-twitter-topic-networks-from-polarized-crowds-to-community-clusters/
Smyrnaios, N. (2018). Internet oligopoly: The corporate takeover of our digital world. Bingley: Emerald Group Publishing.