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Many extreme right groups have had an online presence for some time through the use of dedicated websites. This has been accompanied by increased activity in social media platforms in recent years, enabling the dissemination of extreme…
Social networks play a fundamental role in the diffusion of information. However, there are two different ways of how information reaches a person in a network. Information reaches us through connections in our social networks, as well as…
Extracting topics from large collections of unstructured text-documents has become a central task in current NLP applications and algorithms like NMF, LDA as well as their generalizations are the well-established current state of the art.…
Graph structures are powerful tools for modeling the relationships between textual elements. Graph-of-Words (GoW) has been adopted in many Natural Language tasks to encode the association between terms. However, GoW provides few…
Online social media such as Twitter, Facebook, Wikis and Linkedin have made a great impact on the way we consume information in our day to day life. Now it has become increasingly important that we come across appropriate content from the…
Online behaviors of consumers and marketers generate massive marketing data, which ever more sophisticated models attempt to turn into insights and aid decisions by marketers. Yet, in making decisions human managers bring to bear marketing…
The ever-growing datasets published on Linked Open Data mainly contain encyclopedic information. However, there is a lack of quality structured and semantically annotated datasets extracted from unstructured real-time sources. In this…
To be prepared against cyberattacks, most organizations resort to security information and event management systems to monitor their infrastructures. These systems depend on the timeliness and relevance of the latest updates, patches and…
Social media and social networks have already woven themselves into the very fabric of everyday life. This results in a dramatic increase of social data capturing various relations between the users and their associated artifacts, both in…
The serious privacy and security problems related to online social networks (OSNs) are what fueled two complementary studies as part of this thesis. In the first study, we developed a general algorithm for the mining of data of targeted…
Cities have been a thriving place for citizens over the centuries due to their complex infrastructure. The emergence of the Cyber-Physical-Social Systems (CPSS) and context-aware technologies boost a growing interest in analysing,…
Inferring latent attributes of people online is an important social computing task, but requires integrating the many heterogeneous sources of information available on the web. We propose learning individual representations of people using…
Big data research is currently split on whether and to what extent Twitter can be characterised as an informational or social network. We contribute to this line of inquiry through an investigation of digital humanities scholars' uses and…
Social media is nearly ubiquitous in modern life, raising concerns about its societal impacts -- from mental health and polarization to violence and democratic disruption. Yet research on its causal effects is still inconclusive: Various…
In recent years, malicious information had an explosive growth in social media, with serious social and political backlashes. Recent important studies, featuring large-scale analyses, have produced deeper knowledge about this phenomenon,…
Online government petitions represent a new data-rich mode of political participation. This work examines the thus far understudied dynamics of sharing petitions on social media in order to garner signatures and, ultimately, a government…
The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relevant features of graphs representing real systems is community structure, or clustering, i. e. the organization of…
Social relationships can be divided into different classes based on the regularity with which they occur and the similarity among them. Thus, rare and somewhat similar relationships are random and cause noise in a social network, thus…
Comparing networks is essential for a number of downstream tasks, from clustering to anomaly detection. Despite higher-order interactions being critical for understanding the dynamics of complex systems, traditional approaches for network…
In recent years, people spend a lot of time on social networks. They use social networks as a place to comment on personal or public events. Thus, a large amount of information is generated and shared daily in these networks. Using such a…