Yes, There is a Correlation - From Social Networks to Personal Behavior on the Web offence
Findings People talk to each other share common interests, People talk to each other have similar ages, People talk to each other are more likely to live in the same areas, …… All the findings are common-sense, even without reading this paper, people can expect the results, why do you write this paper without telling people anything that is surprising or counter-intuitive?
Title vs. Content Title of this paper: There is a Correlation From social networks to personal behavior on the web Problem addressed in this paper: Chatting vs. Interests/demographics Don’t match, title’s too broad!
Impact of this study Search engines could personalize their results to match not only a person’s stated interests, but also the interests inferred from the user’s social network. Useful, but how could you realize this? It could lead to more intelligent chat clients that, for example, recommend a new friend to join a chat based on the interests shared by the friends already chatting. Sounds interesting, but any requirement/demand for this application in reality? how could you properly invite a new friend to join a existing chatting?
Theory What’s the meaning of formula 4? Why you have formula 1, 2, 3, 4 here, where do you use them in the paper?
Dataset Personal interest data Biased, only on Microsoft Web search engine, which are not completed to characterize user’s Interests. (Google, Yahoo, etc may contain more representative info) Demographic data may be inaccurate People are movable (I move twice in a year.) Age may be faked (People do not disclose their ages, for example, they pretend to be young ) How do you correlate a MSN user with his/her info searching data?
Results Beautiful graphs, but could you explain how do you calculate the y-axles?
Results Fig. 2 and Fig. 3, and Fig. 4 and Fig. 5 contain the same information, do not see why you need draw them together? Bin5 has an exception, you do not have a single possible explanation there.