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Hah...wondering how to explain the topic shortly...well, it has two parts. One is using twitter and it analyzes tweets of developers who use some open source frameworks for web app development. And I evaluate how happy/sad the devs are (sentiment analysis). And then I parse GitHub for those projects they are tlaking about and I look for patterns between releases of projects and sentiment change of developers. Basically said - is it bettee if frameworks offer new features and fix bugs more often but less or is it better if they offer a lot of new stuff once a year etc...

And the second part automatically tries to find bug reports - e.g. if some tweet is negative and talks about some bugs, I analyze the text and try to link it to some bugs/issues reported on the github. Usually in the comments under git issue report there's some workaround. So the output of my algorithm is like: Twitter account writes: Shit, there's parsing error in Angular module X,Y - and my algorithm provides him links to some known parsing errors in Angular. So he doesn't have to google but can directly read about the issue and to see if there's some workaround :)

Hah as you can see, im kinda proud of it, it was difficult task and works nice...my supervisor also wants me to present it on some software engineering conference :)

oh wow I'm impressed! I thought you were a college student still (didn't know you were already at the thesis level)! Now I have to ask how old YOU are LOL

Seems like really cool stuff! I figured it would be in this domain since you were creating your own token =) Good luck with the thesis and the presentation !!!

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