The dataset for presuicidal signals detection in text and its analysis

Buyanov, Igor; Sochenkov, Ilya

doi:10.28995/2075-7182-2022-21-81-98

Cited by 1 publication

(1 citation statement)

References 11 publications

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“…In social media, people tend to reduce some words and make abbreviations of frequent phrases to save typing time. This phenomenon can be seen in this work (Buyanov and Sochenkov, 2022) where authors study the language of Twitter posts of persons with suicidal tendencies. Another thing is that people try to mimic speech methods of emotional expression, thus they multiply vowels ("whaaaat?").…”

Section: A Note About Tokenizationmentioning

confidence: 87%

Who is answering to whom? Modeling reply-to relationships in Russian asynchronous chats

Buyanov,

Yaskova,

Sochenkov

2023

Computational Linguistics and Intellectual Technologies”

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The study highlights the asynchronous nature of modern group chats and related problems such as retrieving relevant information on the asked question and understanding reply-to relationships. In this work, we formalize the reply recovery task as a building block toward solving described problems. Using simple heuristics, we try to apply the result reply recovery model to a thread reconstruction problem. As a result, we show that modern pre-trained models such as BERT show great results on the task of reply recovery compared to more simple models, though it cannot be applied to thread reconstruction with just simple heuristics. In addition, experiments have shown that model performance depends on the chat domain. We open-sourced a model that can automatically predict which message the particular reply responds to and provide a representative Russian dataset that we built from Telegram chats of different domains. We also provide a test set for a thread reconstruction task.

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Section: A Note About Tokenizationmentioning

confidence: 87%