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Mapping Memetic Images : An Analysis of Russian Cyber Troop Activity

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Title: Mapping Memetic Images : An Analysis of Russian Cyber Troop Activity
Author(s): Mantell, Gabrielle
Contributor: University of Helsinki, Faculty of Social Sciences
Degree program: Master's Programme in European and Nordic Studies
Specialisation: Social Sciences Study Track
Language: English
Acceptance year: 2020
Social media was initially viewed as a democratising force that allowed anyone to participate in political discourse, however in recent years there has been a significant increase in the number of state-sponsored cyber troops using these technologies to spread disinformation and computational propaganda with the intent to influence the behaviour and opinions of individuals, sow chaos and confusion and undermine social cohesion. In recent years, Russia has emerged as the global leader in developing and deploying these tactics against foreign nations, conducting operations on an industrial scale through what are colloquially termed ‘troll factories,’ the most famous of which is the Internet Research Agency (IRA). This study examines images produced by Twitter accounts attributed to the IRA and the corresponding account-level metadata, in order to understand how cyber troops are using Twitter to propagate memetic content and in what ways tactics differ based upon Russian strategic culture. This study also looks at how a nation’s perceived geopolitical position can be interpreted through analysing the output of state-sponsored digital actors. Key to the success of these tactics is the dissemination of weaponised information that spreads ‘virally’ from person to person. For this reason, memetics is employed as a theoretical framework. Strategic culture is also used as an analytical tool to interpret the objectives behind Russian cyber troop activity. The research design of this study comprises three phases. First, images that occur in the dataset 5 or more times are computationally clustered, producing 1,346 clusters of visually similar images, representing 11,742 images in total. Qualitative Content Analysis is then used to create a coding framework which categorises the content of each cluster, capturing three primary dimensions: mode of delivery, type of message and country of focus. Finally, account-level metadata is analysed to determine key account characteristics, providing insight into five factors: location, account lifespan (age), language, activity and originality. Each of these factors is then cross tabulated with five regions: Russia, Post-Soviet, Europe, USA and Rest of World. The findings of this study indicate that IRA actors have pursued a multidirectional strategy based upon Russian strategic culture, in which highly political information is distributed to target audiences primarily in Russia, USA, Europe and Ukraine. The type of information spread is predominantly photographic in nature. Images of public figures and other types of political imagery frequently occur in the dataset, as do images that reinforce an insider/outsider dichotomy. Neutral images are also strategically utilised to construct Twitter accounts that appear authentic, thereby maximising the propagation rate of targeted information. When looking at references made to countries, Russia and the USA emerge as the primary centres of focus. However, when geo-visually plotted on a map, the data indicates that, as the space between these two powers, the European region is commensurate in strategic significance. Ukraine is also prioritised as a fulcrum between the Russian and Western spheres of influence, highlighting divergence in interpretations of how to define Europe and its boundaries. These findings suggest that as Russia vies for digital sociopolitical influence in the West, Europe emerges as a key strategic space between the evolving perception of ‘us’ and ‘them’.
Keyword(s): Information warfare memetic Russia strategic culture cyber social media trolling computational propaganda disinformation computational social science geopolitics international relations

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