Privacy in Social Media: Identification, Mitigation and Applications

Abstract

The increasing popularity of social media has attracted a huge number of people to participate in numerous activities on a daily basis. This results in tremendous amounts of rich user-generated data. This data provides opportunities for researchers and service providers to study and better understand users' behaviors and further improve the quality of the personalized services. Publishing user-generated data risks exposing individuals' privacy. Users privacy in social media is an emerging task and has attracted increasing attention in recent years. These works study privacy issues in social media from the two different points of views: identification of vulnerabilities, and mitigation of privacy risks. Recent research has shown the vulnerability of user-generated data against the two general types of attacks, identity disclosure and attribute disclosure. These privacy issues mandate social media data publishers to protect users' privacy by sanitizing user-generated data before publishing it. Consequently, various protection techniques have been proposed to anonymize user-generated social media data. There is a vast literature on privacy of users in social media from many perspectives. In this survey, we review the key achievements of user privacy in social media. In particular, we review and compare the state-of-the-art algorithms in terms of the privacy leakage attacks and anonymization algorithms. We overview the privacy risks from different aspects of social media and categorize the relevant works into five groups 1) graph data anonymization and de-anonymization, 2) author identification, 3) profile attribute disclosure, 4) user location and privacy, and 5) recommender systems and privacy issues. We also discuss open problems and future research directions for user privacy issues in social media.

This survey is currently under review

References in corpus (8)

• A Survey of Location Prediction on Twitter
• Geotagging One Hundred Million Twitter Accounts with Total Variation Minimization
• A survey of location inference techniques on Twitter
• Preserving Link Privacy in Social Network Based Systems
• Graph Annotations in Modeling Complex Network Topologies
• Securing Social Media User Data - An Adversarial Approach
• Social Media and User Privacy
• Similar but Different: Exploiting Users' Congruity for Recommendation Systems

Cited by in corpus (7)

• Privacy-Aware Recommendation with Private-Attribute Protection using Adversarial Learning
• I Am Not What I Write: Privacy Preserving Text Representation Learning
• Social Science Guided Feature Engineering: A Novel Approach to Signed Link Analysis
• Towards Plausible Graph Anonymization
• Signed Link Prediction with Sparse Data: The Role of Personality Information
• Early Identification of Pathogenic Social Media Accounts
• Target Privacy Preserving for Social Networks