@inproceedings{govindarajan-etal-2020-help,
title = "Help! Need Advice on Identifying Advice",
author = "Govindarajan, Venkata Subrahmanyan and
Chen, Benjamin and
Warholic, Rebecca and
Erk, Katrin and
Li, Junyi Jessy",
editor = "Webber, Bonnie and
Cohn, Trevor and
He, Yulan and
Liu, Yang",
booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.emnlp-main.427",
doi = "10.18653/v1/2020.emnlp-main.427",
pages = "5295--5306",
abstract = "Humans use language to accomplish a wide variety of tasks - asking for and giving advice being one of them. In online advice forums, advice is mixed in with non-advice, like emotional support, and is sometimes stated explicitly, sometimes implicitly. Understanding the language of advice would equip systems with a better grasp of language pragmatics; practically, the ability to identify advice would drastically increase the efficiency of advice-seeking online, as well as advice-giving in natural language generation systems. We present a dataset in English from two Reddit advice forums - r/AskParents and r/needadvice - annotated for whether sentences in posts contain advice or not. Our analysis reveals rich linguistic phenomena in advice discourse. We present preliminary models showing that while pre-trained language models are able to capture advice better than rule-based systems, advice identification is challenging, and we identify directions for future research.",
}
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<abstract>Humans use language to accomplish a wide variety of tasks - asking for and giving advice being one of them. In online advice forums, advice is mixed in with non-advice, like emotional support, and is sometimes stated explicitly, sometimes implicitly. Understanding the language of advice would equip systems with a better grasp of language pragmatics; practically, the ability to identify advice would drastically increase the efficiency of advice-seeking online, as well as advice-giving in natural language generation systems. We present a dataset in English from two Reddit advice forums - r/AskParents and r/needadvice - annotated for whether sentences in posts contain advice or not. Our analysis reveals rich linguistic phenomena in advice discourse. We present preliminary models showing that while pre-trained language models are able to capture advice better than rule-based systems, advice identification is challenging, and we identify directions for future research.</abstract>
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%0 Conference Proceedings
%T Help! Need Advice on Identifying Advice
%A Govindarajan, Venkata Subrahmanyan
%A Chen, Benjamin
%A Warholic, Rebecca
%A Erk, Katrin
%A Li, Junyi Jessy
%Y Webber, Bonnie
%Y Cohn, Trevor
%Y He, Yulan
%Y Liu, Yang
%S Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
%D 2020
%8 November
%I Association for Computational Linguistics
%C Online
%F govindarajan-etal-2020-help
%X Humans use language to accomplish a wide variety of tasks - asking for and giving advice being one of them. In online advice forums, advice is mixed in with non-advice, like emotional support, and is sometimes stated explicitly, sometimes implicitly. Understanding the language of advice would equip systems with a better grasp of language pragmatics; practically, the ability to identify advice would drastically increase the efficiency of advice-seeking online, as well as advice-giving in natural language generation systems. We present a dataset in English from two Reddit advice forums - r/AskParents and r/needadvice - annotated for whether sentences in posts contain advice or not. Our analysis reveals rich linguistic phenomena in advice discourse. We present preliminary models showing that while pre-trained language models are able to capture advice better than rule-based systems, advice identification is challenging, and we identify directions for future research.
%R 10.18653/v1/2020.emnlp-main.427
%U https://aclanthology.org/2020.emnlp-main.427
%U https://doi.org/10.18653/v1/2020.emnlp-main.427
%P 5295-5306
Markdown (Informal)
[Help! Need Advice on Identifying Advice](https://aclanthology.org/2020.emnlp-main.427) (Govindarajan et al., EMNLP 2020)
ACL
- Venkata Subrahmanyan Govindarajan, Benjamin Chen, Rebecca Warholic, Katrin Erk, and Junyi Jessy Li. 2020. Help! Need Advice on Identifying Advice. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 5295–5306, Online. Association for Computational Linguistics.