The concept of social ties was introduced by Granovetter through the seminal paper titled" Strength of weak ties". Across the past five decades, this topic has attracted much attention from both academics and practitioners. In the past two decades, the rapid increase in digitization and new modes of communication have led to collecting and analyzing data about people. One of the most popular sources for such large and granular data about people is social media platforms. The rise in the popularity of social media in the past 15 years has resulted in many research studies that have used social media data to understand a lot of different phenomena. Some of this research has focused on using social data, including social media data, on identifying different kinds of social ties online and the role these social ties play in various contexts. Over the past decade, many different approaches and models have been built to identify social ties using social media data. These methods have been built using private data and explicit social relationship data of users’ social media platforms. However, in the past few years, it has become nearly impossible to access this kind of social media data due to the changes in the business models of the social media platforms and the introduction of new privacy laws like GDPR.
This thesis aims to identify the social ties from publicly available social data and study the role of the identified social ties in different contexts like business conferences and business phenomena. In order to achieve this research objective, three separate studies were conducted. The first two studies were single-case case studies, while the third was an experiment where two different sets of hypotheses were tested using empirical data. All three studies used publicly available social media data related to a specific context. The first study used a large dataset related to a game developer community on Facebook. The second study used social media data related to a business event from Twitter and Facebook. The third study used a large dataset associated with social media data about crowdfunding projects from Twitter.
This study adds to the existing literature related to identifying social ties from social media data in multiple manners. The thesis illustrates a novel approach based on reciprocal interaction for filtering relevant social ties from large publicly available social media data. The thesis also contributes to the understanding of the role multiple social media platforms play in an event. Thus, showing the impact this can have on identifying social ties from publicly available social media data in case of an event. The dissertation adds to the existing literature about the role social ties have towards crowdfunding success. The thesis shows that implicit social ties, in general, positively impact crowdfunding project success. In addition, the thesis has practical implications for designers of conference recommendation systems. The dissertation also has implications for the crowdfunding project owners and the crowdfunding project campaign designers
