Naaman, Mor, Jeffrey Boase, Chih-Hui Lai. “Is it really about me? Message Content in Social Awareness Streams.” ACM Digital Library, ACM, dl.acm.org/citation.cfm?id=1718953. Accessed 1 Sept. 2017.
Akshay Java, Xiaodan Song, Tim Finin, Belle Tseng. “Why We Twitter: Understanding Microblogging Usage and Communities”. http://aisl.umbc.edu/resources/369.pdf. Accessed 1 Sept. 2017.
Summary
In “Is it really about me?: message content in social awareness streams,” the researchers sought to study how users treated twitter with respect to the kind of content they would post. What they ended up doing was classifying the content of posts and using that to determine what sort of user someone actually was, either a meformer(majority posts are about themselves) or an informer(majority posts provided non-user information).
While in “Why We Twitter: Understanding Microblogging Usage and Communities,” it was more focused on how users interact and how communities are created between those users given the rise of microblogs. They were able to check geographical distributions and user intentions before designing three groups that they believe encompass users: information sources, friends, and information seekers.
Reflection
I find it impressive the deductions made from data grabbed by third parties and the analysis and can only imagine what sort of nefarious metrics twitter themselves is probably conducting. It was interesting to see how they classified users in the above papers, but I can’t help but feel the catagories are too broad. In “Is it really about me?…” I felt that their sample size was to small and couldn’t account for possible biases so it was a little difficult to take to much stock from theirs.
Questions
– Does twitter artifically shelter sub-communities?
– Why is it that twitter succeeded where others failed?
– What makes twitter a preferred platform. I see the shortened versions of things to be very misleading?
– What other metrics might be more useful to have if twitter is not already collecting them?
– How accurately can major events be predicted based off of social media (i.e. arab spring)
