Abstract:
Transnational global interactions observed through activities such as international voting
measures, trade transactions and participations in alliances have historically provided
researchers an opportunity to analyze international relations (IR) amongst national actors
within the global power structure. In addition to these traditional macro-level global
interactions, the recent emergence of social media has ushered in a new era of global
connectivity amongst individual people throughout the world, thus enabling micro-level
global interactions. This thesis provides a more holistic view of global international
relations by capturing both macro-level and micro-level global interactions and viewing
them as comparable networks. By using social network analysis (SNA) tools to detect
emergent communities within networks, this thesis directly compared the community
structure of two macro-level networks (United Nations General Assemble (UNGA)
voting records and arms trade transaction networks) and one social media micro-level network (e.g. Twitter). The UNGA macro-level voting network served as a measure of
validation for this approach by properly showing East-West geopolitical divisions during
the Cold War and a North-South socio-economic division following the Cold War. The
micro-level Twitter network was created from tweets harvested from conversations about
the Ukrainian crisis from the initial Euromaidan protests in November 2013 through June
2014, which included the annexation of Crimea by Russia. The community detection
results for the micro-level Ukrainian Twitter network shared the greatest similarity (0.42
on a 0-1 scale) with the UNGA Cold War community results. This result suggests that
Ukrainian citizens did not shed their historical cultural roots that aligned themselves with
the Cold War East-West geopolitical structure. Additionally, a further analysis evaluating
the level of cooperation between the NATO alliance and Ukraine showed that there exists
very little evidence of cooperation between the two entities in either the micro-level or
macro-level networks.
