%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