Security Visualization Analytics Model in Online Social Networks Using Data Mining and Graph-based Structure Algorithms

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.

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Emergent Data Mining Tools for Social Network Analysis

Open Source Technology ◽

10.4018/978-1-4666-7230-7.ch078 ◽

2015 ◽

pp. 1539-1556

Author(s):

Dhiraj Murthy ◽

Alexander Gross ◽

Alex Takata

Keyword(s):

Data Mining ◽

Social Networks ◽

Social Network ◽

Network Analysis ◽

Online Social Networks ◽

Data Extraction ◽

Future Directions ◽

Effective Development ◽

Mining Tools

This chapter identifies a number of the most common data mining toolkits and evaluates their utility in the extraction of data from heterogeneous online social networks. It introduces not only the complexities of scraping data from the diverse forms of data manifested in these sources, but also critically evaluates currently available tools. This analysis is followed by a presentation and discussion on the development of a hybrid system, which builds upon the work of the open-source Web-Harvest framework, for the collection of information from online social networks. This tool, VoyeurServer, attempts to address the weaknesses of tools identified in earlier sections, as well as prototype the implementation of key functionalities thought to be missing from commonly available data extraction toolkits. The authors conclude the chapter with a case study and subsequent evaluation of the VoyeurServer system itself. This evaluation presents future directions, remaining challenges, and additional extensions thought to be important to the effective development of data mining tools for the study of online social networks.

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Towards Privacy-Preserving Data Mining in Online Social Networks: Distance-Grained and Item-Grained Differential Privacy

Information Security and Privacy - Lecture Notes in Computer Science ◽

10.1007/978-3-319-40253-6_9 ◽

2016 ◽

pp. 141-157 ◽

Cited By ~ 1

Author(s):

Shen Yan ◽

Shiran Pan ◽

Yuhang Zhao ◽

Wen-Tao Zhu

Keyword(s):

Data Mining ◽

Social Networks ◽

Online Social Networks ◽

Differential Privacy ◽

Privacy Preserving ◽

Privacy Preserving Data Mining

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The Anti-Data-Mining (ADM) Framework - Better Privacy on Online Social Networks and Beyond

2019 IEEE International Conference on Big Data (Big Data) ◽

10.1109/bigdata47090.2019.9006050 ◽

2019 ◽

Author(s):

Shah Mahmood

Keyword(s):

Data Mining ◽

Social Networks ◽

Online Social Networks

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Detection of Behavior Patterns through Social Networks like Twitter, using Data Mining techniques as a method to detect Cyberbullying

2018 7th International Conference On Software Process Improvement (CIMPS) ◽

10.1109/cimps.2018.8625625 ◽

2018 ◽

Cited By ~ 1

Author(s):

Freddy Tapia ◽

Cristina Aguinaga ◽

Roger Luje

Keyword(s):

Data Mining ◽

Social Networks ◽

Behavior Patterns ◽

Data Mining Techniques ◽

Using Data

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The Alt-social Network of Natalie Bookchin’s Testament

Television & New Media ◽

10.1177/1527476416670011 ◽

2016 ◽

Vol 18 (5) ◽

pp. 459-477

Author(s):

Sarah Whitcomb Laiola

Keyword(s):

Data Mining ◽

Social Networks ◽

Social Media ◽

Social Network ◽

Online Social Networks ◽

Social Web ◽

User Interactions ◽

Media Criticism ◽

Direct Translation ◽

The Social

This article addresses issues of user precarity and vulnerability in online social networks. As social media criticism by Jose van Dijck, Felix Stalder, and Geert Lovink describes, the social web is a predatory system that exploits users’ desires for connection. Although accurate, this critical description casts the social web as a zone where users are always already disempowered, so fails to imagine possibilities for users beyond this paradigm. This article examines Natalie Bookchin’s composite video series, Testament, as it mobilizes an alt-(ernative) social network of vernacular video on YouTube. In the first place, the alt-social network works as an iteration of “tactical media” to critically reimagine empowered user-to-user interactions on the social web. In the second place, it obfuscates YouTube’s data-mining functionality, so allows users to socialize online in a way that evades their direct translation into data and the exploitation of their social labor.

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