Understanding Security Threats in Spam Detection on Social Networks

2017 ◽  
Vol 2 (5) ◽  
pp. 18-22
Author(s):  
Balogun Abiodun Kamoru ◽  
Azmi Bin Jaafar ◽  
Masrah Azrifah Azmi Murad ◽  
Marzanah A. Jabar
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Spam Detection ◽  
Security Threats ◽  
Network Community ◽  
Data Mining Approach ◽  
Internet Users ◽  
Strategic Approach ◽  
Web Social ◽  
E Mail

Social network has become a very popular way for internet users to communicate and interact online. The socia; networks provide a platform to maintain a contact with friends. Increasing social network’s popularity allows all of them to collect large amounts of personal details about their users. Globally, the issue of identifying spammers have received great attention due to its practical relevance in the field of social network analysis. Social network community users are fed with irrelevant information while surfing, due to spammer's activity. Spam pervades any information system such as e-mail or web, social, blog or reviews platform. The aim of this paper is to examine previous works in the field of spam detection in social networks, the study attempts to review various spam detection frameworks which details about the detection and elimination of spam's in various sources, By classification and Clustering Method of spam detection and by raising security awareness among the users of social networks and stake holders , by prescribing a strategic approach or data mining approach for analyzing the nature of spam detection on social networks.

Gender Differences in the Technology’s Classic Models in Social Network Sites

2014 ◽  
pp. 126-142
Author(s):  
Begoña Peral-Peral ◽  
Ángel F. Villarejo-Ramos ◽  
Manuel J. Sánchez-Franco
Keyword(s):  
Gender Differences ◽  
Social Networks ◽  
Social Network ◽  
Technology Acceptance ◽  
Information And Communication Technologies ◽  
Social Network Sites ◽  
Communication Technologies ◽  
Internet Users ◽  
Information And Communication ◽  
Acceptance Model

Social Network Sites (SNS) have very rapidly become part of the daily reality of Internet users in recent years. Firms also use social networks as a two-way communication with their current and potential customers. This exploratory work means to analyze if Internet users’ gender influences the behavior of using social networks. There is a reason for this. Despite Information and Communication Technologies (ICT) acceptance and use being more frequent in men, according to the previous literature, in line with different surveys on the subject, social networks are more used by women. The authors, therefore, analyze in this chapter if there are gender differences in the constructs of technology’s classic models, such as the TAM (Technology Acceptance Model) and the TPB (Theory of Planned Behavior). They use a sample of 1,460 university students.

Motif Analysis and the Periodic Structural Changes in an Organizational Email-Based Social Network

2011 ◽  
pp. 292-302
Author(s):  
Krzysztof Juszczyszyn ◽  
Katarzyna Musial
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Network Topology ◽  
Structural Changes ◽  
Structural Parameters ◽  
Local Network ◽  
Network Motifs ◽  
Motif Analysis ◽  
University Of Technology ◽  
E Mail

Network motifs are small subgraphs that reflect local network topology and were shown to be useful for creating profiles that reveal several properties of the network. In this work the motif analysis of the e-mail network of the Wroclaw University of Technology, consisting of over 4000 nodes was conducted. Temporal changes in the network structure during the period of 20 months were analysed and the correlations between global structural parameters of the network and motif distribution were found. These results are to be used in the development of methods dedicated for fast estimating of the properties of complex internet-based social networks.

Detecting Pharmaceutical Spam in Microblog Messages

2011 ◽  
pp. 101-115
Author(s):  
Kathy J. Liszka ◽  
Chien-Chung Chan ◽  
Chandra Shekar
Keyword(s):  
Data Mining ◽  
Social Networks ◽  
Social Network ◽  
Online Social Networks ◽  
Cell Phones ◽  
Pharmaceutical Products ◽  
Spam Detection ◽  
Data Mining Techniques ◽  
Flow Through ◽  
Special Category

Microblogs are one of a growing group of social network tools. Twitter is, at present, one of the most popular forums for microblogging in online social networks, and the fastest growing. Fifty million messages flow through servers, computers, and cell phones on a wide variety of topics exchanged daily. With this considerable volume, Twitter is a natural and obvious target for spreading spam via the messages, called tweets. The challenge is how to determine if a tweet is a spam or not, and more specifically a special category advertising pharmaceutical products. The authors look at the essential characteristics of spam tweets and what makes microblogging spam unique from email or other types of spam. They review methods and tools currently available to identify general spam tweets. Finally, this work introduces a new methodology of applying text mining and data mining techniques to generate classifiers that can be used for pharmaceutical spam detection in the context of microblogging.

scholarly journals Extraction of Multilayered Social Networks from Activity Data

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Katarzyna Musial ◽  
Piotr Bródka ◽  
Przemysław Kazienko ◽  
Jarosław Gaworecki
Keyword(s):  
Social Networks ◽  
Social Network ◽  
New Method ◽  
Activity Data ◽  
Communication Medium ◽  
Web Based ◽  
Characteristic Element ◽  
Additional Challenge ◽  
Different Types ◽  
E Mail

The data gathered in all kinds of web-based systems, which enable users to interact with each other, provides an opportunity to extract social networks that consist of people and relationships between them. The emerging structures are very complex due to the number and type of discovered connections. In web-based systems, the characteristic element of each interaction between users is that there is always an object that serves as a communication medium. This can be, for example, an e-mail sent from one user to another or post at the forum authored by one user and commented on by others. Based on these objects and activities that users perform towards them, different kinds of relationships can be identified and extracted. Additional challenge arises from the fact that hierarchies can exist between objects; for example, a forum consists of one or more groups of topics, and each of them contains topics that finally include posts. In this paper, we propose a new method for creation of multilayered social network based on the data about users activities towards different types of objects between which the hierarchy exists. Due to the flattening, preprocessing procedure of new layers and new relationships in the multilayered social network can be identified and analysed.

Detecting Pharmaceutical Spam in Microblog Messages

Data Mining ◽  
2013 ◽  
pp. 1407-1420
Author(s):  
Kathy J. Liszka ◽  
Chien-Chung Chan ◽  
Chandra Shekar
Keyword(s):  
Data Mining ◽  
Social Networks ◽  
Social Network ◽  
Online Social Networks ◽  
Cell Phones ◽  
Pharmaceutical Products ◽  
Spam Detection ◽  
Data Mining Techniques ◽  
Flow Through ◽  
Special Category

Microblogs are one of a growing group of social network tools. Twitter is, at present, one of the most popular forums for microblogging in online social networks, and the fastest growing. Fifty million messages flow through servers, computers, and cell phones on a wide variety of topics exchanged daily. With this considerable volume, Twitter is a natural and obvious target for spreading spam via the messages, called tweets. The challenge is how to determine if a tweet is a spam or not, and more specifically a special category advertising pharmaceutical products. The authors look at the essential characteristics of spam tweets and what makes microblogging spam unique from email or other types of spam. They review methods and tools currently available to identify general spam tweets. Finally, this work introduces a new methodology of applying text mining and data mining techniques to generate classifiers that can be used for pharmaceutical spam detection in the context of microblogging.

An Exploratory Analysis Using Co-Authorship Network

2019 ◽  
pp. 166-200
Author(s):  
Burçin Güçlü ◽  
Miguel Ángel Canela ◽  
Inés Alegre
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Organizational Behavior ◽  
Human Behavior ◽  
Online Social Networks ◽  
World Wide ◽  
Academic Research ◽  
E Mail

Social network analysis has been widely used by organizational behavior researchers to stress the importance of the context, social connections, and social structure on human behavior. In the last decade, social network analysis has emerged as one of the most useful techniques for exploring online social networks, world wide web, e-mail traffic, and logistic operations. In this chapter, the authors present an application of social network analysis techniques for academic research. The authors choose Kahneman and Tversky's prospect theory as the focus of their analysis and, based on that, develop a co-authorship structure that depicts in a clear manner the key authors and/or the researchers that dominate and bridge different sub-fields in the field of management. The authors discuss the implications of this study for academic research and management discipline.

scholarly journals Getting to know the potential of social media in forest education

2019 ◽  
Vol 80 (2) ◽  
pp. 159-166
Author(s):  
Radosław Lewoń ◽  
Ewa Pirożnikow
Keyword(s):  
Social Networks ◽  
Social Network ◽  
The State ◽  
Ecological Awareness ◽  
The Public ◽  
Virtual Groups ◽  
Advantages And Disadvantages ◽  
Internet Users ◽  
Forest Education ◽  
Motivating Factor

Abstract The development of social network sites not only facilitates the acquisition and deepening of knowledge but also provides the possibility of easily contacting foresters, specialists in natural sciences and nature enthusiasts. In addition, for some years already, Internet users have been able to make use of websites operated by institutions and participate in nature-related social network groups. The purpose of our survey was to evaluate the possibility of using the main fanpage of the State Forests and virtual nature groups in Poland and Great Britain to propagate knowledge about nature and forestry. The aim was to verify the recipient groups and explore the benefits derived by users from informal forest education as well as to determine how they assess the work of foresters or the reliability of the provided content posted on the portals. The research found that the majority of respondents use portals to gain knowledge and communicate with specialists whilst social networks are a motivating factor encouraging people to take advantage of recreation in forest areas by collecting mushrooms and herbs. Our results clearly point out the advantages and disadvantages of the State Forests’ fanpage and other nature-related social groups. The importance of social networks in education and communicating with the public is steadily increasing. Therefore, social networking websites should be refined and accommodate the constantly-changing needs of society as well as allow members of virtual groups to converse with foresters. The State Forests should support nature-related groups in attracting real enthusiasts. Organisational and substantive support for these groups would allow an increase in ecological awareness and knowledge about forest management directly from the practitioners.

Motif Analysis and the Periodic Structural Changes in an Organizational Email-Based Social Network

2010 ◽  
pp. 1957-1968
Author(s):  
Krzysztof Juszczyszyn ◽  
Katarzyna Musial
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Network Topology ◽  
Structural Changes ◽  
Structural Parameters ◽  
Local Network ◽  
Network Motifs ◽  
Motif Analysis ◽  
University Of Technology ◽  
E Mail

Network motifs are small subgraphs that reflect local network topology and were shown to be useful for creating profiles that reveal several properties of the network. In this work the motif analysis of the e-mail network of the Wroclaw University of Technology, consisting of over 4000 nodes was conducted. Temporal changes in the network structure during the period of 20 months were analysed and the correlations between global structural parameters of the network and motif distribution were found. These results are to be used in the development of methods dedicated for fast estimating of the properties of complex internet-based social networks

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