Reading 1 - Computational Approaches in Social Computing

1. The main contributions of the paper can be described on the first page when they discuss the three characteristics that capture the essence of social computing: Connectivity, Collaboration, and Community. The three writers of this paper discuss how these characteristics make up the bounds of social interactions. Connectivity is the emphasis on relationships within the group, how they are connected, and how they communicate, such as through email, instant messaging, SMS, ect. Collaboration is how people can facilitate one another in a collaborative manner, which can be in a positive or negative way. And Community is how people cluster together to form groups such as through functional similarity, spatial closeness, ect. The rest of the paper goes on to detail these concepts and expand on them.
2. One of the largest limitations that i can see from the paper is that the topic they are studying is constantly evolving and social networks continually change. They discuss many approaches to extracting, refining, interpreting, and analyzing data taken from social sources such as social networks and data mining. But what is hard about this is that the dynamics of social sites are constantly changing. 
3. The most important assumptions made by the authors is that "we observe that the latent information among people in communities give rise to the exciting prospect to view and process social computation differently than what we have before." On top of this they believe that this is just the "tip of the iceberg" and that they are going to continue their work in Social Computing in the future. I believe these assumptions are realistic but at the same time can be difficult for the same reason i stated previously, that social environments where communities form such as social networks , social media, and forums are constantly changing and evolving. This in tern can be pretty limiting when trying to perform some type of concrete research on a topic. 
4. Since this paper was published, social media has continued to evolve. Many of the social networks that were analyzed for their traffic by Alexa have changed drastically. For example, since 2008, Facebook has gone from 5th to 1st and has overtaken Google in terns of internet traffic worldwide. While MySpace has gone from 3rd place to an embarrassing 214th. As well, Amazon has now made an appearance in 8th place and Twitter ranks 10th in the US; both not even making the list from 2008.    http://www.alexa.com/topsites
5. My experiences with respect to the materiel in the paper is that i have very little besides being an avid social media user and have deal with some data mining techniques in previous classes. Much of what they say is accurate while i still believe that it is difficult to create theories for things that are constantly changing. All we can do is try to predict where trends flow. Today, Facebook is the largest social networking site and continues to lead, while only a few years ago, MySpace was "the" site. Who knows what will change in a few years in terms of social media and thus social computing.