In social network analysis, a conventional approach relies heavily on available metadata, allowing to match a virtual entity (social network account) to a real-world entity (person, company) in the network. However, a single person using multiple accounts for any reason obviously breaks the connection, forming multiple virtual entities in the network. Or multiple people can share their account, forming a single virtual entity in the network. If these cases are not taken into account, they can affect reliability of social network analysis significantly without any warning, possibly leading to misinformed decisions and further bad consequences.
The success of many enterprises greatly depends on their ability to gather useful information and process it in a timely manner. Automation is essential and so is presentation, giving tangible feedback, to decision makers. This is where technology reaches out to management, where science and design are combined to put the right people in the position of making better and more sustainable choices.
I have just finished a year-long MSc. program in Computing at Imperial College London. My thesis was called GraphAware:Towards Online Analytical Processing in Graph Databases, which you can freely download. It’s not an easy, cover-to-coverread, but there might be some interesting parts, even if you don’t go through all the (over 100) pages.