TestiMole-Conversational: A 30-Billion-Word Italian Discussion Board Corpus (1996–2024) for Language Modeling and Sociolinguistic Research

Matteo Rinaldi, Rossella Varvara, Viviana Patti


Abstract
We present TestiMole-Conversational a massive collection of discussion boards messages in the Italian language. The large size of the corpus, almost 30B word-tokens (1996–2024), brings challenges in the processing and curation of the resource, but it renders it an ideal dataset for native Italian Large Language Models’ pre-training. Furthermore, discussion boards’ messages are a relevant resource for linguistic as well as sociological analysis. The corpus captures a rich variety of computer-mediated communication, offering insights into informal written Italian, discourse dynamics, and online social interaction in a wide time span. Beyond its relevance for NLP applications such as language modelling, domain adaptation, and conversational analysis, it also support investigations of language variation and social phenomena in digital communication.
Anthology ID:
2026.cmlc-1.1
Volume:
Proceedings of the 12th Workshop on Challenges in the Management of Large Corpora
Month:
May
Year:
2026
Address:
Palma, Mallorca (Spain)
Editors:
Piotr Bański, Dawn Knight, Marc Kupietz, Andreas Witt, Alina Wróblewska
Venues:
CMLC | WS
SIG:
Publisher:
ELRA Language Resources Association (ELRA)
Note:
Pages:
1–11
Language:
External URL:
https://lrec.elra.info/lrec2026-ws-cmlc-01
DOI:
10.63317/5643evropidu
Bibkey:
Cite (ACL):
Matteo Rinaldi, Rossella Varvara, and Viviana Patti. 2026. TestiMole-Conversational: A 30-Billion-Word Italian Discussion Board Corpus (1996–2024) for Language Modeling and Sociolinguistic Research. In Proceedings of the 12th Workshop on Challenges in the Management of Large Corpora, pages 1–11, Palma, Mallorca (Spain). ELRA Language Resources Association (ELRA).
Cite (Informal):
TestiMole-Conversational: A 30-Billion-Word Italian Discussion Board Corpus (1996–2024) for Language Modeling and Sociolinguistic Research (Rinaldi et al., CMLC 2026)
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