tag:blogger.com,1999:blog-6857842314311875399.post5170323165401311171..comments2023-08-21T05:47:55.886-07:00Comments on On the Path to Revival: Mining Tweets of World Cup T20 Match between India and Pakistan: Interesting Insights from Social Network AnalysisArjumandhttp://www.blogger.com/profile/03679172506796211394noreply@blogger.comBlogger1125tag:blogger.com,1999:blog-6857842314311875399.post-51016162526635965102012-11-11T13:51:10.237-08:002012-11-11T13:51:10.237-08:00Interesting analysis. A couple of things come to m...Interesting analysis. A couple of things come to mind.<br /><br />First of all... so what you've done is map the colocations of players. Now consider an alternate experiment. Suppose you were to take a list of sentiment words (horrible, terrible, disaster, wonderful, excellent etc.) and graph the colocations of players -> sentiment words. E.g. in this case you'd see Hafeez being colocated with negative sentiment mostly. it would be fun to see such a represntation (maybe not too much fun for Hafeez, admittedly)<br /><br />Secondly, I'm wondering what your process might contribute in other fields. At a higher level, what you've done is identify a group of subjects (players) in a topic (Pak vs Ind T20 match). then you've done the centrality and community analysis based on colocations of mentions of these subjects. What kind of analysis can we do if we forget about cricket and instead consider political candidates (subjects) in an election (topic), for instance? I'm not sure. It's a novel representation though, which makes it interesting ;)J Conroyhttps://www.blogger.com/profile/13060446058952558322noreply@blogger.com