Research: Risks of Friendships on Social Networks
Authors: Prepared by Cuneyt Gurcan Akcora, Barbara Carminati and Elena Ferrari (DISTA, Universita` degli Studi dell’Insubria Via Mazzini 5, Varese, Italy), Risks of Friendships on Social Networks is a prepared paper submitted and accepted by the 2012 IEEE Conference on Data Mining (ICDM).
Abstract: In this paper, the authors explore the risks of friends in social networks caused by their friendship patterns, by using real life social network data and starting from a previously defined risk model. Particularly, they observe that risks of friendships can be mined by analyzing users’ attitude towards friends of friends. This allows new insights into friendship and risk dynamics on social networks.
Analysis: Summarized analysis from this paper includes observations on:
Applicability: Risks of Friendships on Social Networks offers unique insight into the privacy risks of online friendships and provides salient considerations for the development of risk models that could be applied to social network users.
Access: (PDF) http://bit.ly/Xk5mlX (arXiv.org)
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Daily we read, see, and hear more and more about the tension corporate legal departments face as they decide how to source technology and talent for their eDiscovery efforts. Balancing cost, time, and complexity is a continual challenge and what is the right balance today may be out of balance tomorrow. This week our cartoon and clip provides one look at the impact of technology on outsourcing (cartoon), and shares considerations for right sourcing eDiscovery (clip).
Daily we read, see, and hear more and more about how technology is changing the game of document classification and revolutionizing document review. While there may be evidence that new data governance and discovery technologies can absolutely change current approaches to document classification and review, it is important to remember that technology is only as good as its ability to be delivered, managed, and supported by vendors and integrators.
While some may dispute the existence of unstructured data, definitions for the term “unstructured data” do exist. This week our cartoon and clip provides a quick look at how people convey meaning in different ways (cartoon) and provides a short list of definitions for the term “unstructured data” (clip).
The focus on the technology and talent elements of an information governance vendor’s capability is certainly warranted as these elements ultimately provide the cutting edge for the knife of task execution. However, just as there is much more to the utility of a knife than its edge (especially if you want to use it more than once), there are additional areas worthy of consideration in vendor selection if one is considering the long term strategic utility and viability of a vendor.
Since the advent of Technology Assisted Review (aka TAR, predictive coding or computer-assisted review), one of the open questions is whether you have to run a separate TAR process for each item in a document request. As litigation professionals know, it is rare to have only one numbered request in a Rule 34 pleading. Rather, you can expect to see scores of requests (typically as many as the local rules allow).
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Technology-Assisted Review (hereinafter TAR) is broadly defined as the use of computer tools to determine the relevance of selected documents to any issues in a given controversy. The most utilized form of TAR, known as predictive coding, allows a human reviewer to utilize a select sample of documents to “train” a computer to recognize patterns of relevance in the universe of documents under review.
In this episode of Digital Detectives, Sharon Nelson and John Simek interview Judge Andrew Peck, an expert in issues relating to electronic discovery. Together they discuss the current state of technology-assisted review, how FRCP amendments will affect the way lawyers do discovery, and best practices when using TAR.
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Updated 7/23/2013: Provided for your consideration and use are the in-progress results of the Predictive Coding and Provider Survey launched...