Social aspects are of great importance in Information Technology since the science mainly uses information gathered by users, usually without their consent. It is very important for users to understand that they are part of the systems that they use. Especially in the context of Web 2.0 where they tend to disclose their private information quite easily .
Two of the most important social aspects that arise on social networking applications are privacy and trust.
Privacy is the right of every individual person to keep enclosed their personal data. Users believe that when they surf on the Web, their interaction is made with machines. As a result, they do not hesitate to provide those “machines” with every kind of personal and even confidential data, without thinking that the machine acts on behalf of a person and/or a business. Users must understand that through social networking applications they do not interact with machines but with other people who may even try to take advantage of posted private user data.
Another important social factor that arises on social networking applications is trust. The anonymity that Web gives to users allows them to pretend a different identity. Moreover, Web 2.0 is an open platform that allows everyone to post content on applications like social networks, blogs and wikis . This content may be malicious, fake or it may serve implicit aims of the publisher. Trust bears in mind several thoughts about whether we should trust data and information found on the Web, posted by people who have not proved their identity .
Privacy and Trust into our System
For the design and development of the Real-Time Aggregator, we are going to pay special attention on the arisen social aspects.
Regarding privacy, there are not many issues related our system because it will mainly use and exploit data that exist on social networking applications. Users will not be obliged to post, create, or add data into our system. The system’s tag clouds and other mechanisms, used to help our users perform their searches, will be created by anonymous contributions made by our users when performing searches. However, those searches will not be personalised. The only user data that the system will store is their username and password. In order to ensure confidentiality, usernames and passwords will be encrypted before storing them into our database.
Dealing with Trust issues is not that straightforward. Social networking related applications have low levels of trust and even “great players”, like Facebook and Twitter, cannot guarantee trust into their systems. If the comments made by users on platforms like Facebook and Twitter are fake and aim to misguide customers, then there are very few things that our aggregator can do to avoid it. However, we have made some thoughts about how to ensure that the comments we return to our results will be as true as possible. We are actually planning to create a black list into our data model, as an “Advanced functionality” feature. The list will store the social networking application ids of users (e.g. Twitter user id, Facebook user id) that show great preference to products of specific vendors and who use to accuse competitive products. The module will also take into account the reputation of such users before putting them in our black list, meaning that users who have good network reputation will not be considered as malicious. Comments of ”black listed” users, will not be returned by our system. Once again, we recognise that it is a confident idea that might be considered for the “advanced functionality” implementation. Moreover, we may re-examine the feasibility of this feature before its implementation.
 S. Murugesan, “Understanding Web 2.0″, IT Professional, vol. 9, no. 4, July-August 2007
 V. Cerf, “Trust and the Internet”, IEEE Internet Computing, vol. 14, no. 5, September-October 2010, pp 96-97