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During the 60 years of publication of the journal Vojnoistorijski glasnik it was to be expected that a prominent place in its pages would be granted to the person and the work of the Yugoslav leader Josip Broz Tito. Tito featured as the author of some contributions, usually aimed at explaining certain tenets of the complicated relations between Yugoslavia and the USSR. Over time Tito became interesting for authors of various fields, mostly from the top brass of the Yugoslav People’s Army and primarily with the aim of glorifying him and portraying him as a symbol of the Yugoslav unity and authentic approach to the development of the armed forces. The end of the Cold War, fall of communism and the break-up of Yugoslavia opened a new chapter in dealing with such a complicated subject as the place and the role of Josip Broz Tito in the more recent Yugoslav history. Thanks to the new researches based on archival sources, the „personality and work" of Josip Broz Tito migrated from journalism and yellow press to pages of several monographs and scholarly journals, among them to the Vojnoistorijski glasnik.
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The last few years have provided an abundance of examples of how malicious actors can exploit user data to the detriment of social media users, armed forces, and society. This study explores what kind of user data is available in the digital environment and demonstrates how a malicious actor can exploit this data in the context of a military exercise. The results of an experiment conducted by a NATO StratCom COE research team suggest that in the current digital arena an adversary would be able to collect enough personal data on soldiers to create targeted messages with precision, successfully influencing their chosen target audience to carry out desired behaviors.
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As social media, and the web as a whole, become more visual, organizations and governments can no longer rely solely on textual analysis when seeking to better understand their audiences in the online environment. Methods for thorough analysis of the online information environment, including visual content, must be developed. This chapter discusses the type of information images contain and how it can be extracted, and proposes a computer based image retrieval to extract valuable information from large volumes of images and aggregate it in a meaningful way.
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In May 2017, the President of Ukraine put into effect a decision of the National Security and Defence Council (NSDC) to impose economic sanctions on 468 Russian companies. The largest Russian social network, VKontakte (VK), was banned, among others. Because of the ban, the audience for VK in Ukraine decreased significantly and the social network site dropped out of the top ten most popular sites in the country. To better understand the effects of the VK ban, a study was organised to monitor changes in posting dynamics, to analyse user demographics before and after the ban, and to identify the rhetoric used in posts before and after the ban. The dataset includes more than 300,000 Ukrainian VK user profiles. Because the ban does not apply to the territories occupied by Russia, the study examined two target regions: government controlled areas (GCA) subject to the ban, and non-government-controlled areas (NGCA) where the ban was not imposed. The study took place between 1 May 2016 and 14 June 2018. This period was divided into three intervals: before the ban, the first ‘user exodus’, and the second ‘user exodus’. Our analysis shows that VK is markedly less popular in the area controlled by the Ukrainian government (19% less, compared to NGCA). However, those few users left after the ban are more active, producing 4.37 times as much content as those in non-governmentcontrolled-areas. Moreover, these VK profiles are more densely connected. To study the rhetoric appearing in user posts, we used a clustering algorithm that could identify accounts posting about ideological issues. When compared with the majority of other profiles, the characteristics of ideological posts stood out. Before the ban a typical VKuser would write, on average, one post every four days; after the ban the frequency dropped to one post every ten days. Ideological users55 were notably more active — they wrote four posts per day before the ban and 1.6 posts after the ban. Ideological users were also significantly more connected — after the ban the average number of friends for an ideological user grew from 197 to 501, and such users subscribed to 2.25 times more groups than typical VK-users. Our analysis of reposts from ideological groups showed that although the number of users decreased by a factor of three, the activity level of these groups remained unchanged. However, taking into account that most pro-Ukrainian groups left VK after the ban, those who continued to use the network were increasingly posting to an echo-chamber. We conclude that the VK ban was effective in some ways. The network lost a significant portion of its audience and its popularity decreased, but those users who retained their VK profiles after the ban became more connected on average and began consuming more information from a greater number of groups. Despite the fact that the number of ideological users also dropped, those who continued to use VK lost their opposition, so rhetoric became less diverse.
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In the last 6 months increasing quantities of information have been released regarding exactly how attempts to influence the 2016 U.S. presidential election may have been carried out. In this study we use a combination of quantitative analysis, machine learning and natural language processing to map out the topics of conversation promoted by the Russian troll factory, the Internet Research Agency (IRA) between 2015 and 2018. We show how this activity involves coordinated messaging across multiple social media platforms (Facebook, Twitter, Reddit and Instagram), and how this seeks to promote both sides of controversial debates with inflammatory material. Additionally, we demonstrate how real-world events are utilised to spread division in societies abroad with a common pattern of progressively provocative content. Finally, we show how this same agency uses these platforms for a very different purpose for domestic audiences, and spreads single pro-regime messages without attempts to intensify divisions at home. These results demonstrate how any successful solutions to counter this type of activity will need to tackle the problem from a multi-platform approach, and also must consider how alternative audiences may be targeted in different ways by hostile influence.
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Throughout this publication, we have explored some of the ways in which technology can be exploited to influence our behavior. In this brief section, we offer some recommendations. Given current trends, it is likely that more and more personal data will be available online in the coming years. This issue is particularly delicate with regard to the personal data of people belonging to sensitive categories (such as servicemen/-women, government officials, and decision-makers). On the one hand, it will be necessary to devise ways to curb current trends for what concerns these categories, i.e. reducing the amount of information available on these individuals. On the other hand, it is equally important to consider how to mitigate the negative effects of data proliferation once data is already available and can be exploited by malicious actors. The research presented here has demonstrated that current standards must be improved to reduce the risks posed by personal data exploitation. Conducting experiments, such as the one described in this volume should be a staple component of tactical-level exercises and could significantly improve the awareness of our servicemen/-women.
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