FROM INCUBATORS TO ECOSYSTEMS: EVALUATING THE STARTUP DIGITAL ECONOMY CLUSTER OF HULL CITY

SOCIAL MEDIA AND NETWORK THEORY

Tsvetovat & Kouznetsov, in their manual ‘Social Network Analysis for Startups: Finding connections on the social web’, the authors observed how almost every startup in 2011 was using the word ‘social’ in their business plans, but very few knew how to analyze and understand “the social processes that can result in their firm’s success or failure” (Tsvetovat & Kouznetsov, 2011: vii). Very much the same can be said about the word ‘network’, in their manual “Understanding Social Networks (2012) Charles Kadushin wrote: “‘Networking seems to be on everyone's lips. No one simply goes to a party anymore. They go to Network. For many people, the World Wide Web exists for the main purpose of making connections” (2012:3)

Social Network Analysis has its origins in both social science and in the fields of network analysis and graph theory, and even its recent popularization due to the advent of the Social Internet. It has not always been such a popular field. A decade ago data was hard to get and hard to work with. Today, “every day, Twitter generates more social-network data then our entire field possessed 10 years ago; every social media site provides an API for easy retrieval of data; many governments of the world are releasing data that lends itself to SNA (Social Network Analysis) techniques” (Tsvetovat & Kouznetsov, 2011:1)

In their presentation during the data sprint summer school 2016 at the Chinese University of Hong Kong, professor Céline Yunya Song introduce the analysis and visualization of social networks with what she called the “Then master ideas of social networks” as compiled by Kadushin (2012)
 
In the specific context of organizational research and social network analysis, the idea of social capital may particularly relevant to be able to read network activities in terms of value (Putnam, 2008 in Kadushin, 2012:162). It is believed that “Networks in social systems may be nested, for example, organization networks within industry networks” and that social capital “brings us back to the fundamental premises of social networks, the tradeoff between the comfort and support individuals drives from dense networks of social relationships and the benefits achieved by going beyond local circles and forging bridges to wider universes” (Kadushin, 2012:162).

Over the last years, ‘big data’ has become a product of social networks, and, according to Tsvetovat & Kouznetsov “social networks, as they exist today, are important to us in one primary aspect: as colossal data collectors of human behavior patterns, eagerly powered by the examined themselves, operating on a global scale with near-instant response time. The end result is vast volumes of data, coming at us in a steady stream” (2011:151). But certainly, it seems quite important to remind that no all data is big data. On the matter of the realms of data sizes, Tsvetovat & Kouznetsov propose a pyramid to explain the differences between small, medium, and big data.  Medium data - data which contain millions of nodes, snapshots from APIs -  is still the traditional solution to process large datasets in SQL-based databases. Small data refers to flat file representations - data which contain 1000s of nodes, manually collected- and datasets that do not require the complexity of a relational database. Big data is too big for relational databases, we are talking about real-time social media data with billions of nodes (2011:38)

Even if not all data is big data, a widely held assumption is the correlation between social media interactions -in form of social media data-  and the formation of new networks. In order to understand and map the relation between networks in organizational research, Colin Crook suggest approaching business “as if a business was a ‘living system’”. Therefore as it, the relation between networks was an ecosystem itself (in Kleindorfer, 2009:214).

In their paper “Strategy as ecology” published the Harvard Business Review defined the use of the term “ecosystem” as something closer to the biological term “community”.  The ecosystem-based perspective the authors described has, as they stated, a number of broad implications for managers. One is the central importance of interdependence in business “a company operating in today’s networked setting can use resources that exist outside of its own organization”. To sum up, the author’s advice on how “rather than involving individual companies that are engaged in technology races, battles in the future will be waged between ecosystems or between ecosystem, domains” (Iansiti and Levien, 2004:10). The authors also suggested a correlation between the characterization of business models and biological ecosystems, in a sense that in both can be found the presence of crucial hubs that assume “the keystone functions of regulating ecosystem health”. In other words, a healthy ecosystem is what enables the growth of any dynamic living system. (Iansiti and Levien, 2004:5)

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