The polarized crowds, tight crowd, brand clusters, community clusters, broadcast network, and support network are the six types of Twitter conversation networks that found by Smith, Rainie, Sheneiderman, and Himelboim. Nowadays, with the development of modern technology, people are more and more familiar with those social media platforms. As a result, the information transformation will be more and more typical and complex inside the social media. Nowadays, we can see social media as “cloud”, information is stored in the cloud. In the storage, users give out information and also receive other information from the cloud. “Documents and drawings are now internet attachments or are stored in internet “clouds” where they can be accessed from anywhere.”(Rainie & Wellman,2014) And in the communication process in the social media, users transfer information one by one in the mapping structure. Those six structures of Twitter conversation networks show us how information sharing, delivering, how all users get connection in those social media through mobile devices and the relationship between users and information. And those structures are related to vertical integration. The information shares from top influencers to those subgroups. For each conversation networks structure, we can clearly find different contents and different relationship involved. I find two typical examples that relate to the findings of Smith, Rainie, Sheneiderman, and Himelboim.
(Retrieved from:https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=171389)
Tight Crowd Network
According to the first graph, we can clearly find that “#aoir2018” is the hashtag mentioned by the users involve in those five clusters. The graph represents the network of 1753 users whose tweets or replies contain “#aoir2018”. “The Association of Internet Researchers is pleased to announce Montreal, Canada as the site of #AoIR2018.” (AoIR,2018) AOIR represents Association of Internet Researchers, as a result, those internet researchers will use the hashtag “#aoir2018” during the conference on 13 October, 2018. And on that conference, AI information, digital media methods, digital technologies and other internet topics will be discussed during the workshops.
Himelboim and his collogues mention, the difference between tight crowd network and polarized crowd network is that tight crowd network will have stronger connections between those subgroups. In the tight crowd network structures, users will not only follow up and communicate with each other in the communities and groups, but also frequently reply to each other as well. Furthermore, in this community, people have one common interest and this common interest will lead all information sharing and exchange. Just go back to the graph mentioned above, we can clearly find that the strong bonds connect those participants is the interested in internet. All the topic and tweets lead by internet, even though they are from different areas. All the central users in each groups have strong relationships and those bonds connect them all together. They will share information and exchange ideas about those workshops and talks during the conference. As a result, from the graph, we can find that the recent tweets are all relate to the topic of various workshops in the preconference and conference as well.
(Retrieved from:https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=170780)
Brand Cluster Network
For the second graph I find, it shows us the network of 1133 users contained, replied, or mentioned “#Cadillac”. This structure relates to the Brand Cluster mentioned by Himelboim and his collogues. Cadillac is a general motors accompany worldwide. Brand Cluster structure mentioned by Himelboim and his collogues is a kind of network that includes popular products or events. From the graph, we can know that the tweets in the time period from 23 September 2018 to 6 October 2018 are all about Cadillac brand, which is a worldwide luxury motors company. And in the brand cluster structure, it is quite different from other structure, while it does not need connection between users. From the example of Apple, people talk about Apple brand, but about various topics, such as new features, release date and devices of Apple company. This is the similar with Cadillac graph above.
From the graph, we can clearly find that there are multiple individuals or small groups of users in the community. Compare with the previous graph, there are much less links between each group or inside the group. People discuss about the brand Cadillac, but about different areas of Cadillac. Some of them share the information about new edition of cars of Cadillac, some of them talk about classic model, and others mention those companies under Cadillac. From the data collection, the hashtag “#Cadillac” is used most frequently. This is the reasonable. And from the list of top hashtag in G1, there is a list of different vehicle brands, because they are all competitors in the market of Cadillac. Furthermore, in G2 group, the top hashtag is the briff sooyoung who is a Korean star, because 2017, she was the model of Cadillac XT5. From here we can find the main purposes of brand cluster easily that it used commonly in advertising products or promoting events. Not only competitors of the company, but also those super models of products can bring attention from public.
(Retrieved from:http://app.yonhapnews.co.kr/YNA/Basic/ForeignGallery/view.aspx?lang=EN&contents_id=PYH20170512025000341)
Brand cluster structure is more about advertising, which is relate to what have mentioned by Smyrnaios. Smyrnaios defines the market of advertising as a two-sided market, which is “a source of indirect externalities, understood as consumer satisfaction with a good sold in a market, which depends on the size of demand for another good, on a different market, and conversely.”(Smyrnaios, 2018) But the in the structure of brand cluster we have mentioned above, we can clearly find that in the public, there are various focus by separate audiences or potential customers. They have several different focus on one single brand. Moreover, the data shows us that information of competitors are also receive a lot of attention when people hashtag Cadillac, such as BMW, Lexus and Chevrolet. So that is important for business to take care about different market mentioned by Smyrnaios. And business should also do some researches on their potential customers’ attention in social media as well. Because there is not so much connection between people in the community, and this will lead the users in the community separately and act more individually. The wider rage topics of message the business taking care will attack more attention from public, and meet more needs and wants in the market.
Citation:
“AoIR 2018.” AoIR, aoir.org/.
Rainie, L., & Wellman, B. (2014). Networked: The new social operating system. Cambridge, MA: MIT Press.
Smyrnaios, N. (2018). INTERNET OLIGOPOLY: The corporate takeover of our digital world. BINGLEY: EMERALD GROUP PUBL.