Situation

Social media are everywhere. Almost everyone is member of one or more social networks (Hyves, Facebook, LinkedIn, Twitter, and so forth). Additionally, new social networks emerge every day. Some of your friends or colleagues use Hyves, others use Facebook, and some of these persons also use Twitter. Besides, you may also have some business connections on LinkedIn. In short, you have a rich network of contacts and information.

Needs

We identify a need of a search algorithm for social networks. In other words, there is a need for searching over multiple social networks. It can be used for personal use, but also for business use. Also we identify the need of relevant information. Therefore, it is important to arrange the search results by relevance. The relevance should be based on how close they are to you in your social networks.

Research Question

Based on the overview of the situation and aforementioned needs, there are a number of questions that arise. How can we search across multiple social networks? How do you prioritize the search results based on how close they are related to you? What kind of search algorithm is needed? This question consists of a couple of aspects:

• What kind of search algorithm is needed to search within someone’s social network? Additionally, the search results should be arranged by how close they are to you in your network.
• Technical possibilities (prototype)
• Is it possible to recognize opinions? (Sentiment Analysis)?
• How can different kinds of information (status updates, photos videos, etc) be distinguished?
• Is it possible to make a secured search algorithm?
• Is it extendable? More Social Networks?
• Own input…

Method

It is our suggestion to make use of expert interviews in addition to prototyping the algorithm.