Contouring the Behavioral Patterns of the Users of Social Network(ing) Sites and the Need for Data Privacy Law in India: An Application of SEM-PLS Technique

Author(s):  
Sandeep Mittal ◽  
Priyanka Sharma
Author(s):  
Dan Jerker B. Svantesson

Internet jurisdiction has emerged as one of the greatest and most urgent challenges online, severely affecting areas as diverse as e-commerce, data privacy, law enforcement, content take-downs, cloud computing, e-health, Cyber security, intellectual property, freedom of speech, and Cyberwar. In this innovative book, Professor Svantesson presents a vision for a new approach to Internet jurisdiction––for both private international law and public international law––based on sixteen years of research dedicated specifically to the topic. The book demonstrates that our current paradigm remains attached to a territorial thinking that is out of sync with our modern world, especially, but not only, online. Having made the claim that our adherence to the territoriality principle is based more on habit than on any clear and universally accepted legal principles, Professor Svantesson advances a new jurisprudential framework for how we approach jurisdiction. He also proposes several other reform initiatives such as the concept of ‘investigative jurisdiction’ and an approach to geo-blocking, aimed at equipping us to solve the Internet jurisdiction puzzle. In addition, the book provides a history of Internet jurisdiction, and challenges our traditional categorisation of different types of jurisdiction. It places Internet jurisdiction in a broader context and outlines methods for how properly to understand and work with rules of Internet jurisdiction. While Solving the Internet Puzzle paints a clear picture of the concerns involved and the problems that needs to be overcome, this book is distinctly aimed at finding practical solutions anchored in a solid theoretical framework.


Author(s):  
Leah Plunkett ◽  
Urs Gasser ◽  
Sandra Cortesi

New types of digital technologies and new ways of using them are heavily impacting young people’s learning environments and creating intense pressure points on the “pre-digital” framework of student privacy. This chapter offers a high-level mapping of the federal legal landscape in the United States created by the “big three” federal privacy statutes—the Family Educational Rights and Privacy Act (FERPA), the Children’s Online Privacy Protection Act (COPPA), and the Protection of Pupil Rights Amendment (PPRA)—in the context of student privacy and the ongoing digital transformation of formal learning environments (“schools”). Fissures are emerging around key student privacy issues such as: what are the key data privacy risk factors as digital technologies are adopted in learning environments; which decision makers are best positioned to determine whether, when, why, and with whom students’ data should be shared outside the school environment; what types of data may be unregulated by privacy law and what additional safeguards might be required; and what role privacy law and ethics serve as we seek to bolster related values, such as equity, agency, and autonomy, to support youth and their pathways. These and similar intersections at which the current federal legal framework is ambiguous or inadequate pose challenges for key stakeholders. This chapter proposes that a “blended” governance approach, which draws from technology-based, market-based, and human-centered privacy protection and empowerment mechanisms and seeks to bolster legal safeguards that need to be strengthen in parallel, offers an essential toolkit to find creative, nimble, and effective multistakeholder solutions.


2016 ◽  
Vol 113 (4) ◽  
pp. 913-918 ◽  
Author(s):  
Michael Kearns ◽  
Aaron Roth ◽  
Zhiwei Steven Wu ◽  
Grigory Yaroslavtsev

Motivated by tensions between data privacy for individual citizens and societal priorities such as counterterrorism and the containment of infectious disease, we introduce a computational model that distinguishes between parties for whom privacy is explicitly protected, and those for whom it is not (the targeted subpopulation). The goal is the development of algorithms that can effectively identify and take action upon members of the targeted subpopulation in a way that minimally compromises the privacy of the protected, while simultaneously limiting the expense of distinguishing members of the two groups via costly mechanisms such as surveillance, background checks, or medical testing. Within this framework, we provide provably privacy-preserving algorithms for targeted search in social networks. These algorithms are natural variants of common graph search methods, and ensure privacy for the protected by the careful injection of noise in the prioritization of potential targets. We validate the utility of our algorithms with extensive computational experiments on two large-scale social network datasets.


2021 ◽  
Vol 41 (1) ◽  
pp. 100-13
Author(s):  
Michele Estrin Gilman

Menstruation is being monetized and surveilled, with the voluntary participation of millions of women. Thousands of downloadable apps promise to help women monitor their periods and manage their fertility. These apps are part of the broader, multi-billion dollar, Femtech industry, which sells technology to help women understand and improve their health. Femtech is marketed with the language of female autonomy and feminist empowerment. Despite this rhetoric, Femtech is part of a broader business strategy of data extraction, in which companies are extracting people’s personal data for profit, typically without their knowledge or meaningful consent. Femtech can oppress menstruators in several ways. Menstruators lose control over their personal data and how it is used. Some of these uses can potentially disadvantage women in the workplace, insurance markets, and credit scoring. In addition, these apps can force users into a gendered binary that does not always comport with their identity. Further, period trackers are sometimes inaccurate, leading to unwanted pregnancies. Additionally, the data is nearly impossible to erase, leading some women to be tracked relentlessly across the web with assumptions about their childbearing and fertility. Despite these harms, there are few legal restraints on menstrual surveillance. American data privacy law largely hinges on the concept of notice and consent, which puts the onus on people to protect their own privacy rather than placing responsibility on the entities that gather and use data. Yet notice and consent is a myth because consumers do not read, cannot comprehend, and have no opportunities to negotiate the terms of privacy policies. Notice and consent is an individualistic approach to data privacy that envisions an atomized person pursing their own self-interest in a competitive marketplace. Menstruators’ needs do not fit this model. Accordingly, this Essay seeks to reconceptualize Femtech within an expanded menstrual justice framework that recognizes the tenets of data feminism. In this vision, Femtech would be an empowering and accurate health tool rather than a data extraction device.


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