15 research outputs found

    RTbust: Exploiting Temporal Patterns for Botnet Detection on Twitter

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    Within OSNs, many of our supposedly online friends may instead be fake accounts called social bots, part of large groups that purposely re-share targeted content. Here, we study retweeting behaviors on Twitter, with the ultimate goal of detecting retweeting social bots. We collect a dataset of 10M retweets. We design a novel visualization that we leverage to highlight benign and malicious patterns of retweeting activity. In this way, we uncover a 'normal' retweeting pattern that is peculiar of human-operated accounts, and 3 suspicious patterns related to bot activities. Then, we propose a bot detection technique that stems from the previous exploration of retweeting behaviors. Our technique, called Retweet-Buster (RTbust), leverages unsupervised feature extraction and clustering. An LSTM autoencoder converts the retweet time series into compact and informative latent feature vectors, which are then clustered with a hierarchical density-based algorithm. Accounts belonging to large clusters characterized by malicious retweeting patterns are labeled as bots. RTbust obtains excellent detection results, with F1 = 0.87, whereas competitors achieve F1 < 0.76. Finally, we apply RTbust to a large dataset of retweets, uncovering 2 previously unknown active botnets with hundreds of accounts

    Unveiling Coordinated Groups Behind White Helmets Disinformation

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    Propaganda, disinformation, manipulation, and polarization are the modern illnesses of a society increasingly dependent on social media as a source of news. In this paper, we explore the disinformation campaign, sponsored by Russia and allies, against the Syria Civil Defense (a.k.a. the White Helmets). We unveil coordinated groups using automatic retweets and content duplication to promote narratives and/or accounts. The results also reveal distinct promoting strategies, ranging from the small groups sharing the exact same text repeatedly, to complex "news website factories" where dozens of accounts synchronously spread the same news from multiple sites.Comment: To be presented at WWW 2020 Workshop on Computational Methods in Online Misbehavior and forthcoming in the Companion Proceedings of the Web Conference 202

    The Camera in conservation: determining photography’s place in the preservation of wildlife

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    This MA by research study is a reflection of photography’s past, current and future role within wildlife conservation, or whether there is indeed a necessity for it moving forwards. The following investigation and analysis of photography seeks to materialise how in fact the photographic medium can be both beneficial and negatively impactful to the preservation of wildlife, and how best it can be used by photographers in future conservation projects to ensure the preservation of wildlife. Several significant aspects of photography and external influences are engaged with in this study, firstly investigating the importance of empathy within wildlife conservation and how it can be elicited through imagery and photographic methods. Furthermore, I investigate the other side of conservation photography’s success, analysing what negative or neutral impacts it can bring with it, before researching the role that social media does and has the potential to play in conservation, and how photography can adapt to it to maximise its success. Lastly, I explore alternative visual media such as moving image, and how photography can best applicate successful techniques learned from them to reinterpret how conservation photography is perceived. Finally, using information and research from across my thesis, I have produced a ‘guide’ as to how conservation photography can be shaped to achieve its full potential for success, drawing upon previous successes and failures of other conservation attempts and photographers

    SYSTEMIC ANALYSIS OF ILLEGAL MASS MIGRATION IN THE CENTRAL MEDITERRANEAN REGION

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    This thesis explores the systemic behavior of illegal mass migration in the Central Mediterranean region and proposes strategic approaches to address the problem. We hypothesize that the illegal migration is a complex systemic problem, where parts of the system are interdependent and behavioral change of any element effects the behavior of the whole. This research applies a series of quantitative and qualitative analyses where each reveals different aspects and properties of the migration system as a whole. The systemic analysis highlights the interconnectedness of different parts and their impact of the system’s output. Also, it reveals the cognitive background as a unique aspect of this region: namely, the decision to migrate is based on biased perception and bounded rationality rather than rational choice. In conclusion, we claim that the system’s output (i.e. level of illegal migration) is characterized by the interrelated behavior of parts of the migration system; therefore, strategic planning requires the notion of the dominant feedback loops, self-organization, time delays, limitations, and non-linear relations. Also, we conclude that a skewed perception based on social influence and cognitive biases influences a large number of people in that region to migrate.Captain, Hungarian Defence ForceApproved for public release. Distribution is unlimited

    Comment se propagent les informations sur Twitter ?

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    This thesis presents the measurement study of Online Social Networks focusing on Twitter. Twitter is one of the largest social networks using exclusively directed links among accounts. This makes the Twitter social graph much closer to the social graph supporting real life communications than, for instance, Facebook. Therefore, understanding the structure of the Twitter social graph and the way information propagates through it is interesting not only for computer scientists, but also for researchers in other fields, such as sociologists. However, littles is known about the information propagation in Twitter. In the first part, we present an in-depth study of the macroscopic structure of the Twitter social graph. In the second part, we study the propagation of the news media articles shared on Twitter. In the third part we present an experimental study of graph sampling.Cette thèse présente une étude sur la mesure des réseaux sociaux en ligne avec un accent particulier sur Twitter qui est l'un des plus grands réseaux sociaux. Twitter utilise exclusivement des liens dirigés entre les comptes. Cela rend le graphe social de Twitter beaucoup plus proche que Facebok du graphe social représentant les communications dans la vie réelle. Par conséquent, la compréhension de la structure du graphe social de Twitter et de la manière dont les informations se propagent dans le graphe est intéressant non seulement pour les informaticiens, mais aussi pour les chercheurs dans d'autres domaines, tels que la sociologie. Cependant, on sait peu de choses sur la propagation de l'information sur Twitter
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