Dataset Card for ForumSohbetleri

ForumSohbetleri a web forum tetx corpus for Turkish, indeed first large-scale Turkish forum text corpus.

This corpus is a part of large scale Turkish corpus Bella Turca. For more details about Bella Turca, please refer to the publication.

This collection is made up of several subsets, each subset is gathered from the corresponding forum website. Forum websites contains diverse topics, ladies only, tech, economics, life, relations and much more...

Dataset	num threads	size	num of words
donanimarsivi	17.510	37MB	5.2M
donanimhaber	162.525	472MB	61.5M
forumum	57.219	140MB	17.8M
iyinet	93.531	148MB	18.5M
kadinlarklubu	743.613	5.5GB	773M
memurlar.net	708.198	4GB	511M
tahribat	173.680	912MB	120M
technopatsosyal	688.237	1.4GB	177M
turkiyeforum	17.716	56M	7.1M
wardom	243.150	720M	91M
wmaraci	20.596	32M	3.8M
Total	2.925.975	13.41GB	1.7B

During the crawl, we processed each thread as its own. We made extensive text cleaning in order to cope with highly variable ortography in forum text.

Instances

Each instance represents a thread, hence contains a list of strings - posts in each thread. A typical instance from the dataset looks like:

{
"url": "https://forum.donanimarsivi.com/konu/modeme-baglananlari-nasil-cikarabilirm.790705/",
"texts": [
  "Nasıl değiştirilir bilmiyorum",
  "Komşularımın bazılarında internet sifremiz var ve sürekli baglaniyolar oyunlarda felan MS cıkıyo sürekli nasıl engelliyebilirim Mesaj otomatik birleştirildi: 10 Ağustos 2023 TTNet Tplink Messinin",
  "Sistemim: İntel Core İ5 11400f - Asus PRIME H510M-D - CORSAIR 16GB Vengeance RAM 2X8 - Kioxia 500 GB Exceria M.2 - Asus TUF-GTX1660TI-O6G-EVO-GAMING 192 Bit GDDR6 6 GB - Corsair 650 W Carbide Spec-05 Led Panel ATX Oyuncu Kasası - Asus TUF Gaming VG249Q1R 23.8 165HZ 1MS",
  "arcai netcut kullanabilirsin baya iyi E",
  "Şifreni değiştirsene aga İNTEL İ3 12100F / SAPPHIRE PULSE RX6700 / GIGABYTE H610M / GEIL 2X8 GB RAM 3200MHZ / MLD M300 500GB M.2 SSD / ASUS TUF VG247Q1A / ASUS X571GT GTX 1050 İ5 9300H ilkaycam. m 80+"
]

Citation

@InProceedings{10.1007/978-3-031-70563-2_16,
author="Altinok, Duygu",
editor="N{\"o}th, Elmar
and Hor{\'a}k, Ale{\v{s}}
and Sojka, Petr",
title="Bella Turca: A Large-Scale Dataset of Diverse Text Sources for Turkish Language Modeling",
booktitle="Text, Speech, and Dialogue",
year="2024",
publisher="Springer Nature Switzerland",
address="Cham",
pages="196--213",
abstract="In recent studies, it has been demonstrated that incorporating diverse training datasets enhances the overall knowledge and generalization capabilities of large-scale language models, especially in cross-domain scenarios. In line with this, we introduce Bella Turca: a comprehensive Turkish text corpus, totaling 265GB, specifically curated for training language models. Bella Turca encompasses 25 distinct subsets of 4 genre, carefully chosen to ensure diversity and high quality. While Turkish is spoken widely across three continents, it suffers from a dearth of robust data resources for language modelling. Existing transformers and language models have primarily relied on repetitive corpora such as OSCAR and/or Wiki, which lack the desired diversity. Our work aims to break free from this monotony by introducing a fresh perspective to Turkish corpora resources. To the best of our knowledge, this release marks the first instance of such a vast and diverse dataset tailored for the Turkish language. Additionally, we contribute to the community by providing the code used in the dataset's construction and cleaning, fostering collaboration and knowledge sharing.",
isbn="978-3-031-70563-2"
}

Acknowledgments

This research was supported with Cloud TPUs from Google's TPU Research Cloud (TRC).