SURVEI LITERATUR INFORMATION SECURITY INTELLIGENT UNTUK MEMPREDIKSI POTENSI KERUSUHAN MELALUI ANALISA JARINGAN MEDIA SOSIAL

Kajian ini bertujuan untuk manganalisa literature terdahulu yang berkaitan dengan penerapan Information Security Intelligent (ISI) untuk memprediksi potensi kerusuhan melalui media sosial. Kajian literatur penelitian terdahulu menunjukkan bahwa berbagai platform media sosial di Internet seperti Twitter, Tumblr, Facebook, YouTube, Blog dan forum diskusi disalahgunakan oleh kelompok-kelompok ekstremis untuk menyebarkan kepercayaan dan ideologi mereka. Situs web microblogging populer seperti Twitter digunakan sebagai platform real time untuk berbagi informasi dan komunikasi selama perencanaan dan mobilisasi massa. Penerapan analisa jaringan media sosial untuk memprediksi kejadian kerusuhan adalah area yang telah menarik perhatian beberapa peneliti selama beberapa tahun terakhir. Ada berbagai macam metode yang telah digunakan dalam literatur terkait prediksi kejadian kerusuhan. Dalam jurnal ini, penulis melakukan kajian literatur mengenai semua metode yang ada dan melakukan analisis yang komprehensif untuk memahami situasi, tren dan kesenjangan penelitian. Analisa kajian ini menghasilkan karakterisasi, klasifikasi, dan meta-anlaysis dari puluhan  jurnal untuk mendapatkan pemahaman yang lebih baik tentang literatur tentang potensi kejadian kerusuhan dengan menggunakan metode sosial media intelligent

From Social Data Mining to Forecasting Socio-Economic Crisis

Socio-economic data mining has a great potential in terms of gaining a better understanding of problems that our economy and society are facing, such as financial instability, shortages of resources, or conflicts. Without large-scale data mining, progress in these areas seems hard or impossible. Therefore, a suitable, distributed data mining infrastructure and research centers should be built in Europe. It also appears appropriate to build a network of Crisis Observatories. They can be imagined as laboratories devoted to the gathering and processing of enormous volumes of data on both natural systems such as the Earth and its ecosystem, as well as on human techno-socio-economic systems, so as to gain early warnings of impending events. Reality mining provides the chance to adapt more quickly and more accurately to changing situations. Further opportunities arise by individually customized services, which however should be provided in a privacy-respecting way. This requires the development of novel ICT (such as a self- organizing Web), but most likely new legal regulations and suitable institutions as well. As long as such regulations are lacking on a world-wide scale, it is in the public interest that scientists explore what can be done with the huge data available. Big data do have the potential to change or even threaten democratic societies. The same applies to sudden and large-scale failures of ICT systems. Therefore, dealing with data must be done with a large degree of responsibility and care. Self-interests of individuals, companies or institutions have limits, where the public interest is affected, and public interest is not a sufficient justification to violate human rights of individuals. Privacy is a high good, as confidentiality is, and damaging it would have serious side effects for society.Comment: 65 pages, 1 figure, Visioneer White Paper, see http://www.visioneer.ethz.c

Global Risks 2014, Ninth Edition.

The Global Risks 2014 report highlights how global risks are not only interconnected but also have systemic impacts. To manage global risks effectively and build resilience to their impacts, better efforts are needed to understand, measure and foresee the evolution of interdependencies between risks, supplementing traditional risk-management tools with new concepts designed for uncertain environments. If global risks are not effectively addressed, their social, economic and political fallouts could be far-reaching, as exemplified by the continuing impacts of the financial crisis of 2007-2008

Predicting Social Unrest Events with Hidden Markov Models Using GDELT

Proactive handling of social unrest events which are common happenings in both democracies and authoritarian regimes requires that the risk of upcoming social unrest event is continuously assessed. Most existing approaches comparatively pay little attention to considering the event development stages. In this paper, we use autocoded events dataset GDELT (Global Data on Events, Location, and Tone) to build a Hidden Markov Models (HMMs) based framework to predict indicators associated with country instability. The framework utilizes the temporal burst patterns in GDELT event streams to uncover the underlying event development mechanics and formulates the social unrest event prediction as a sequence classification problem based on Bayes decision. Extensive experiments with data from five countries in Southeast Asia demonstrate the effectiveness of this framework, which outperforms the logistic regression method by 7% to 27% and the baseline method 34% to 62% for various countries

State of the art 2015: a literature review of social media intelligence capabilities for counter-terrorism

Overview This paper is a review of how information and insight can be drawn from open social media sources. It focuses on the specific research techniques that have emerged, the capabilities they provide, the possible insights they offer, and the ethical and legal questions they raise. These techniques are considered relevant and valuable in so far as they can help to maintain public safety by preventing terrorism, preparing for it, protecting the public from it and pursuing its perpetrators. The report also considers how far this can be achieved against the backdrop of radically changing technology and public attitudes towards surveillance. This is an updated version of a 2013 report paper on the same subject, State of the Art. Since 2013, there have been significant changes in social media, how it is used by terrorist groups, and the methods being developed to make sense of it.  The paper is structured as follows: Part 1 is an overview of social media use, focused on how it is used by groups of interest to those involved in counter-terrorism. This includes new sections on trends of social media platforms; and a new section on Islamic State (IS). Part 2 provides an introduction to the key approaches of social media intelligence (henceforth ‘SOCMINT’) for counter-terrorism. Part 3 sets out a series of SOCMINT techniques. For each technique a series of capabilities and insights are considered, the validity and reliability of the method is considered, and how they might be applied to counter-terrorism work explored. Part 4 outlines a number of important legal, ethical and practical considerations when undertaking SOCMINT work

Digital Access, Political Networks and the Diffusion of Democracy

We examine the effects of digital access on the prevalence of democracy and its diffusion via geographical and trade networks across 152 countries between 2000 and 2008. Although civil liberties and media freedom show a consistently positive relationship with different forms of digital access, our dynamic models that allow co-evolution of digital access, democracy and trade tie formation suggest that high mobile penetration has a more significant impact on civil liberties than Internet access does, and may also increase a country's "susceptibility" to democratic changes in neighboring nations. We explore possible drivers of these empirical findings, discussing some social and political implications.NYU Stern School of Busines