M
Margaret Mitchell
Researcher at Google
Publications - 109
Citations - 18187
Margaret Mitchell is an academic researcher from Google. The author has contributed to research in topics: Computer science & Context (language use). The author has an hindex of 42, co-authored 94 publications receiving 13094 citations. Previous affiliations of Margaret Mitchell include University of Aberdeen & Johns Hopkins University.
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Proceedings ArticleDOI
Multitask learning for mental health conditions with limited social media data
TL;DR: The framework proposed significantly improves over all baselines and single-task models for predicting mental health conditions, with particularly significant gains for conditions with limited data, and establishes for the first time the potential of deep learning in the prediction of mental health from online user-generated text.
Posted Content
Language Models for Image Captioning: The Quirks and What Works
Jacob Devlin,Hao Cheng,Hao Fang,Saurabh Gupta,Li Deng,Xiaodong He,Geoffrey Zweig,Margaret Mitchell +7 more
TL;DR: By combining key aspects of the ME and RNN methods, this paper achieves a new record performance over previously published results on the benchmark COCO dataset, however, the gains the authors see in BLEU do not translate to human judgments.
Proceedings ArticleDOI
Quantifying the Language of Schizophrenia in Social Media
TL;DR: Potential linguistic markers of schizophrenia using the tweets 1 of self-identified schizophrenia sufferers are explored, several natural language processing methods are described to analyze the language of schizophrenia, and preliminary evidence of additional linguistic signals are provided.
Proceedings ArticleDOI
deltaBLEU: A Discriminative Metric for Generation Tasks with Intrinsically Diverse Targets
Michel Galley,Chris Brockett,Alessandro Sordoni,Yangfeng Ji,Michael Auli,Chris Quirk,Margaret Mitchell,Jianfeng Gao,Bill Dolan +8 more
TL;DR: In tasks involving generation of conversational responses, ∆BLEU correlates reasonably with human judgments and outperforms sentence-level and IBM BLEU in terms of both Spearman's ρ and Kendall’s τ.
Proceedings ArticleDOI
Saving Face: Investigating the Ethical Concerns of Facial Recognition Auditing
Inioluwa Deborah Raji,Timnit Gebru,Margaret Mitchell,Joy Buolamwini,Joonseok Lee,Emily Denton +5 more
TL;DR: A set of five ethical concerns in the particular case of auditing commercial facial processing technology are demonstrated, highlighting additional design considerations and ethical tensions the auditor needs to be aware of so as not to exacerbate or complement the harms propagated by the audited system.