Ting Chen
Since the founding in 2006, Twitter has become a popular social network platform for internet users to acquire information, follow news updates and share opinions with a certain amount of other Twitter users. Until today, as Nikos Smyrnaios (2018) noted, Twitter remains its independence as one of the only two vibrant global social networking sites that do not belong to the five Internet oligopolies, while many other similar platforms have been merged into part of the oligopolies’ horizontal concentration system through purchase and acquisition.
Marc Smith (2014) and his colleagues at the Pew Research center found six patterns for Twitter users’ conversations and interactions by studying NodeXl network visualization maps. The six patterns have its own distinct features and cover a variety of topics, forming their own group of networks. Right now, a few years have passed, and Twitter users have increased from 14% when Smith did his research to over 20% of Internet users, with a much larger increase in the actual amount of monthly active users of 335 million. (Aslam 2018) Therefore, I chose two recent visualization maps on the NodeXL websites to see if the six patterns still hold true or if there have been new archetypes emerged in recent years.
Graph 1 #WBGMeetings
This graph contains a total of 5,033 Twitter users who tweeted about #WBGMeetings in a ten-day-period from, October 2, 2018, to October 12. The topic here is basically about the World Bank and International Monetary Fund Annual Meeting. As Smith (2014) concluded, meetings and conferences usually take the form of a tight crowd, where people are closely tied to form several medium sized groups, this conference hashtag bears no exception. From this graph, we can clearly identify six larger groups, where people closely give comments, retweets and mentions one another closely on several subtopics including keywords of “global resources”, “human capital”, “Indonesia”, “partnerships”. Each group has their big influencers that communicate beyond the group ties. The only change from the time when the Pew Research Center report was released, is the increased number of small groups, as a consequence of the increase Twitter users, especially international non-English Speaking Twitter users over the world as some of the keywords clusters here are in Spanish, French and Russian.
Top influencers tweeted on this topic include the official Twitter Account of World Band (@worldbank) and its the Spanish and French language outlets (@bancomundial, @banquemondiale), Jim Yong Kim (@JimYongKim), the current president of World Bank Group, several officials working in different department of the World Bank in charging of Europe, Pakistan, and the UK. Therefore, in such a network, those organizers and attendees played a big role in leading a conversation related to the conference. They are using this platform to instantly inform the public of their themes and major issues at the conference.
Graph 2 #awretaurants
This graph contains a network of 2,642 Twitter users tweeted or retweeted with a hashtag of #awretaurants within a time frame of 26 days and 9 hours from September 16 to October 12. It is a lottery winning campaign initiated by twitter account of A&W Restaurants. The basic rule of that event is anyone who follows the official account and retweeted its post can have a chance to win a free mug. Therefore, in this chart, the connection displays one large cluster with a one-way link from a hub center to multiple separate users. This structure is similar to a “Broadcast Network” as Smith defined in their research. However, the topic of this map doesn’t fit the topics tied to this type of structure by Smith, which in theory, a restaurant official account, as one business in the service industry, should be handling costumers’ complains and replying in an outward conversation structure. This graph suggests otherwise. The customers here had voluntarily become promoters and advertisers for the restaurant when they were retweeting for that a chance to win the free mug. The message, therefore, creating inward spokes, even when spreading outward from the hub center – the account of the restaurant – to a wider audience. Thus, those businesses are taking advantages of those users, luring those who wish to win the prize to recommend and promoting their product and services at the cost of only one mug.
These two examples show how Twitter acts as a mediator of all types of information through its platform, ranging from people’s professional talks and idea dissemination to basic restaurant recommendation. Even though Twitter hasn’t invested in starting other internet services other than this social media platform, but it still has the potential to be part of the Internet oligopoly’s vertical integration as Smyrnaios (2018) pointed out, “platforms become infomediaries when they generate complex sets of signifiers that make sense for humans in their social and political context.”
Reference
Smith, Marc. Rainie, Lee. Shneiderman, Ben. & Himelboim, Itai, (2014). “Mapping Twitter Topic Networks: From Polarized Crowds To Community Clusters | Pew Research Center”.Pew Research Center: Internet, Science & Tech. http://www.pewinternet.org/2014/02/20/mapping-twitter-topic-networks-from-polarized-crowds-to-community-clusters/.
Smyrnaios, Nikos. Internet Oligopoly: The Corporate Takeover of Our Digital World (Digital Activism and Society: Politics, Economy and Culture in Network Communication). Emerald Publishing Limited. Kindle Edition.”
Aslam, Salman. (2018). “Twitter By The Numbers: Stats, Demographics & Fun Facts”. 2018. Omnicoreagency.Com. Accessed October 14 2018. https://www.omnicoreagency.com/twitter-statistics/.