Social networks are considered today as revolutionary tools of communication that have a tremendo... more Social networks are considered today as revolutionary tools of communication that have a tremendous impact on our lives. However, these tools can be manipulated by vicious users namely terrorists. The process of collecting and analyzing such profiles is a considerably challenging task which has not yet been well established. For this purpose, we propose, in this paper, a new method for data extraction and annotation of suspicious users from social networks threatening the national security. Our method allows constructing a rich Arabic corpus designed for detecting terrorist users spreading on social networks. The amendment of our corpora is ensured following a set of rules defined by a domain expert. All these steps are described in details, and some typical examples are given. Also, some statistics are reported from the data collection and annotation stages as well as the evaluation of the annotated features based on the intra-agreement measurement between different experts.
An extraction and unification methodology for social networks data: an application to public security
Social media are invaded our daily life where millions of users are subscribed. Those online site... more Social media are invaded our daily life where millions of users are subscribed. Those online sites provide great tool for users to communicate with others from all over the world, share information, and express their opinion. Unfortunately, this ease of access and availability of information is exploited by malicious users to spread their radical ideas and prepare for terrorist attacks. In this paper, we have proposed a new methodology for data extraction, annotation, and unification in order to identify suspicious content from online social media threatening public security. To the best of our knowledge, there is no specific data collected method from social media devoted to suspicious user profile extraction. Also, implying an expert for data annotation for a security purposes remain a new research task that necessitate expertise and knowledge. In this paper, we tackle this research area by collecting suspicious content from different social media.
Social networks are considered today as revolutionary tools of communication that have a tremendo... more Social networks are considered today as revolutionary tools of communication that have a tremendous impact on our lives. However, these tools can be manipulated by vicious users namely terrorists. The process of collecting and analyzing such profiles is a considerably challenging task which has not yet been well established. For this purpose, we propose, in this paper, a new method for data extraction and annotation of suspicious users from social networks threatening the national security. Our method allows constructing a rich Arabic corpus designed for detecting terrorist users spreading on social networks. The amendment of our corpora is ensured following a set of rules defined by a domain expert. All these steps are described in details, and some typical examples are given. Also, some statistics are reported from the data collection and annotation stages as well as the evaluation of the annotated features based on the intra-agreement measurement between different experts.
Tuser2: A New Method for Twitter and Youtube Matching Profiles
Matching user profiles is an efficient way to map users across social networks and communicate an... more Matching user profiles is an efficient way to map users across social networks and communicate an accurate portrait of a user. This study can be applied in different application domains such as recommendation, privacy, cyber-security, etc. In this paper, we address the problem of matching profiles in two popular social networks: YouTube and Twitter. First, we identify users by their shared publicly information and private information implicitly extracted from their published contents. Based on this information, we propose a method that matches profiles in both social networks using different features extraction. Then, we propose an algorithm we call Tuser2 that returns for a targeted profile in Twitter its matched profiles in YouTube and vice versa based on public and inferred attributes comparison. Our preliminary results show that profiles in YouTube and Twitter can be matched with high accuracy. Therefore, exploiting both publicly shared attributes and inferred ones can improve t...
Social networks are considered today as revolutionary tools of communication that have a tremendo... more Social networks are considered today as revolutionary tools of communication that have a tremendous impact on our lives. However, these tools can be manipulated by vicious users namely terrorists. The process of collecting and analyzing such profiles is a considerably challenging task which has not yet been well established. For this purpose, we propose, in this paper, a new method for data extraction and annotation of suspicious users from social networks threatening the national security. Our method allows constructing a rich Arabic corpus designed for detecting terrorist users spreading on social networks. The amendment of our corpora is ensured following a set of rules defined by a domain expert. All these steps are described in details, and some typical examples are given. Also, some statistics are reported from the data collection and annotation stages as well as the evaluation of the annotated features based on the intra-agreement measurement between different experts.
Social networks are considered today as revolutionary tools of communication that have a tremendo... more Social networks are considered today as revolutionary tools of communication that have a tremendous impact on our lives. However, these tools can be manipulated by vicious users namely terrorists. The process of collecting and analyzing such profiles is a considerably challenging task which has not yet been well established. For this purpose, we propose, in this paper, a new method for data extraction and annotation of suspicious users from social networks threatening the national security. Our method allows constructing a rich Arabic corpus designed for detecting terrorist users spreading on social networks. The amendment of our corpora is ensured following a set of rules defined by a domain expert. All these steps are described in details, and some typical examples are given. Also, some statistics are reported from the data collection and annotation stages as well as the evaluation of the annotated features based on the intra-agreement measurement between different experts.
Social networks are considered today as revolutionary tools of communication that have a tremendo... more Social networks are considered today as revolutionary tools of communication that have a tremendous impact on our lives. However, these tools can be manipulated by vicious users namely terrorists. The process of collecting and analyzing such profiles is a considerably challenging task which has not yet been well established. For this purpose, we propose, in this paper, a new method for data extraction and annotation of suspicious users from social networks threatening the national security. Our method allows constructing a rich Arabic corpus designed for detecting terrorist users spreading on social networks. The amendment of our corpora is ensured following a set of rules defined by a domain expert. All these steps are described in details, and some typical examples are given. Also, some statistics are reported from the data collection and annotation stages as well as the evaluation of the annotated features based on the intra-agreement measurement between different experts.
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Papers by Atika Mbarek