@inproceedings{7115dee1566445bb88739ba4ea5cded2,
title = "Refining a coding scheme to identify actionable information on social media",
abstract = "This paper describes the use of a previously established qualitative coding scheme developed through a design workshop with public safety professionals, and applied the schema to social media data collecting during crises. The intention of applying this scheme to existing crisis datasets was to acquire training data for machine learning. Applying the coding scheme to social media data revealed that additional subcategories of the coding scheme are necessary to satisfy information requirements necessary to dispatch first responders to an incident. The coding scheme was refined and adapted into a set of instructions for qualitative coders on Amazon Mechanical Turk. The contribution of this work is a coding scheme that is more directly related to the information needs of public safety professionals. Implications of early results using the refined coding scheme are discussed in terms of proposed automated methods to identify actionable information for dispatch of first responders during emergency incidents.",
author = "Jess Kropczynski and Shane Halse and Doina Caragea and Rob Grace and Nathan Elrod and Cornelia Caragea and Andrea Tapia",
note = "Publisher Copyright: {\textcopyright} 2019 Information Systems for Crisis Response and Management, ISCRAM. All rights reserved.; 16th International Conference on Information Systems for Crisis Response and Management, ISCRAM 2019 ; Conference date: 19-05-2019 Through 22-05-2019",
year = "2019",
language = "English (US)",
series = "Proceedings of the International ISCRAM Conference",
publisher = "Information Systems for Crisis Response and Management, ISCRAM",
pages = "916--922",
editor = "Zeno Franco and Gonzalez, {Jose J.} and Canos, {Jose H.}",
booktitle = "ISCRAM 2019 - Proceedings",
}