Sorry to spam, I couldn't find literature on sampling strategies for generating training data for classification tasks. I wasn't looking for a training dataset. So any literature recommendation on the possible sampling strategies is much appreciated. Best, Sina
-----Original Message----- From: Air-L <air-l-bounces@listserv.aoir.org> On Behalf Of Sina Furkan Özdemir Sent: Wednesday, April 29, 2020 11:08 AM To: air-l@listserv.aoir.org Subject: [Air-L] Sampling strategies for classification tasks
Dear all,
I have been following some 800 Twitter accounts for my Ph.D. dissertation over the last four months. I have ended up with 400.000 tweets that I need to categorize by four mutually exclusive categories.
I looked up some previous works with similar tasks, and it seems that the best way is to use a combination of word embeddings and recurrent neural networks with LSTM structure.
The problem I am having right now is that I couldn't find training data for the classification. Can anyone recommend me some literature on sampling strategies for short-text classification tasks?
Best, Sina Özdemir Ph.D. Candidate NTNU, Trondheim M.A Comparative and International Studies ETH Zurich & University of Zurich, Switzerland B.A. Political Science and International Relations Middle East Technical University, Turkey
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