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Article
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2017

Inquire

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en
2017
DOI: 10.1145/2998181.2998363

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John F Canny
John F Canny

University of California, Berkeley

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Pablo Paredes
Ana Rufino Ferreira
Cory D. Schillaci
+5 more

Abstract

We introduce Inquire, a tool designed to enable qualitative exploration of utterances in social media and large-scale texts. As opposed to keyword search, Inquire allows the effective use of sentences as queries to quickly explore millions of documents to retrieve semantically-similar sentences. We apply Inquire to LiveJournal.com (LJ) database, which contains millions of personal diaries, and we use semantic embeddings trained in LJ or Google News (GN) datasets. We present the system design through iterative evaluations with qualitative researchers. We show how queries become a part of the inductive process, enabling researchers to try multiple ideas while gaining intuition and discovering less-obvious insights. We discuss the choice of LJ as a rich source of public posts, the preference for GN embeddings which link formal language (e.g. "reminiscence triggers") with colloquial expressions (e.g. "music brings back memories"), the interplay between tool and user, and potential qualitative and social research opportunities.

How to cite this publication

Pablo Paredes, Ana Rufino Ferreira, Cory D. Schillaci, Gene Yoo, Pierre Karashchuk, Dennis Xing, Coye Cheshire, John F Canny (2017). Inquire. , DOI: https://doi.org/10.1145/2998181.2998363.

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Publication Details

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Article

Year

2017

Authors

8

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0

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0

Language

en

DOI

https://doi.org/10.1145/2998181.2998363

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