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)
This entry was posted on Tuesday, February 19th, 2013 at 2:26 pm. It is filed under chronology, discover and tagged with research, social media. You can follow any responses to this entry through the RSS 2.0 feed.
Comments are closed.
Based on an informal review of research from technology providers, industry analyst firms, and industry expert reports in the data discovery arena, the following short list of enablers highlights companies and technologies that may be useful to technology providers as legal discovery professionals seek to move “to the left of the EDRM” and closer to the point of data creation in their data discovery efforts.
The Victorian Supreme Court will issue a practice note about the use of TAR on 1 January 2017. We understand it will be the first court in Australia to do so. We expect that other Australian courts will follow suit in issuing a practice note, and it will be interesting to follow the approaches taken by other Australian courts.
The biggest takeaway of the joint research project by nonprofit Electronic Discovery Institute and tech giant Oracle Corp. is that TAR is often faster and cheaper when identifying relevant documents. But when it comes to isolating privileged or sensitive information, human reviewers outperformed machines.
ComplexDiscovery | Creative Commons Attribution 4.0 International
Updated 7/23/2013: Provided for your consideration and use are the in-progress results of the Predictive Coding and Provider Survey launched...