Related papers: A Comprehensive Bibliometric Analysis on Social Ne…
The growing demand for computer security and the cyberization trend are hallmarks of the 21st century. The rise in cyber-crime, digital currency, e-governance, and more, is well met by a corresponding recent jump in investment in new…
One way to assess a certain aspect of the value of scientific research is to measure the attention it receives on social media. While previous research has mostly focused on the "number of mentions" of scientific research on social media,…
The cybersecurity landscape evolves rapidly and poses threats to organizations. To enhance resilience, one needs to track the latest developments and trends in the domain. It has been demonstrated that standard bibliometrics approaches show…
Social Network Analysis (SNA) tries to understand and exploit the key features of social networks in order to manage their life cycle and predict their evolution. Increasingly popular web 2.0 sites are forming huge social network. Classical…
We have collected and cleaned two network data sets: Coauthorship and Citation networks for statisticians. The data sets are based on all research papers published in four of the top journals in statistics from $2003$ to the first half of…
There are three approaches in the current social network analysis study: Graph Representation, Content Mining, and Semantic Analysis. Graph Representation has been used for analyzing social network topology, structural modeling,…
As the field of neuroimaging grows, it can be difficult for scientists within the field to gain and maintain a detailed understanding of its ever-changing landscape. While collaboration and citation networks highlight important…
Anonymization of graph-based data is a problem which has been widely studied over the last years and several anonymization methods have been developed. Information loss measures have been used to evaluate data utility and information loss…
Anonymizing textual documents is a highly context-sensitive problem: the appropriate balance between privacy protection and utility preservation varies with the data domain, privacy objectives, and downstream application. However, existing…
The Semantic Web is one of the main efforts aiming to enhance human and machine interaction by representing data in an understandable way for machines to mediate data and services. It is a fast-moving and multidisciplinary field. This study…
In this article, we develop a method that uses altmetric data to analyse researchers' interactions, as a way of mapping the contexts of potential societal impact. In the face of an increasing policy demand for quantitative methodologies to…
The growing use of voice user interfaces has led to a surge in the collection and storage of speech data. While data collection allows for the development of efficient tools powering most speech services, it also poses serious privacy…
Here we present a holistic approach for data exploration on dense knowledge graphs as a novel approach with a proof-of-concept in biomedical research. Knowledge graphs are increasingly becoming a vital factor in knowledge mining and…
Anxiety affects hundreds of millions of individuals globally, yet large-scale screening remains limited. Social media language provides an opportunity for scalable detection, but current models often lack interpretability,…
The authorship attribution is a problem of considerable practical and technical interest. Several methods have been designed to infer the authorship of disputed documents in multiple contexts. While traditional statistical methods based…
The use of science to understand its own structure is becoming popular, but understanding the organization of knowledge areas is still limited because some patterns are only discoverable with proper computational treatment of large-scale…
Two decades ago three pioneering papers turned the attention to complex networks and initiated a new era of research, establishing an interdisciplinary field called network science. Namely, these highly-cited seminal papers were written by…
Identity is one of the most commonly studied constructs in social science. However, despite extensive theoretical work on identity, there remains a need for additional empirical data to validate and refine existing theories. This paper…
The primary objective of an anonymity tool is to protect the anonymity of its users through the implementation of strong encryption and obfuscation techniques. As a result, it becomes very difficult to monitor and identify users activities…
Anonymous social networks present a number of new and challenging problems for existing Social Network Analysis techniques. Traditionally, existing methods for analysing graph structure, such as community detection, required global…