[Air-L] Sampling strategies for classification tasks

[Giz Gulnerman]

Dear Sina Özdemir,

If I understand it correctly, I might suggest the link below searching for
a trained dataset.
https://www.kaggle.com/datasets
Good luck,
Giz
*Ar.Gör. Ayşe Giz Gülnerman*
İstanbul Teknik Üniversitesi
İnşaat Fakültesi - Geomatik Mühendisliği Bölümü
34469 Maslak İstanbul / Türkiye
gulnerman at itu.edu.tr
-----------------------------------------------------------------------------------------------------------------
*R.A. Ayse Giz Gulnerman*
Istanbul Technical University
Faculty of Civil Engr. - Geomatics Engr. Dep.
34469 Maslak Istanbul/ Turkey
gulnerman at itu.edu.tr


On Wed, Apr 29, 2020 at 12:08 PM Sina Furkan Özdemir <sina.ozdemir at ntnu.no>
wrote:

> 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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