Verifying baselines for crisis event information classification on Twitter

Crow, Justin Michael (2020) Verifying baselines for crisis event information classification on Twitter. 17th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2020), Virginia Tech, Blacksburg, Virginia, USA, 24th to 27th May 2020. Published in: ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management. 670-687. Virginia Tech, Blacksburg, VA (USA). ISSN 97819493732762 ISBN 2411-3448

[img] PDF - Accepted Version
Available under License All Rights Reserved.

Download (584kB)

Abstract

Social media are rich information sources during and in the aftermath of crisis events such as earthquakes and terrorist attacks. Despite myriad challenges, with the right tools, significant insight can be gained which can assist emergency responders and related applications. However, most extant approaches are incomparable, using bespoke definitions, models, datasets and even evaluation metrics. Furthermore, it is rare that code, trained models, or exhaustive parametrisation details are made openly available. Thus, even confirmation of self-reported performance is problematic; authoritatively determining the state of the art (SOTA) is essentially impossible. Consequently, to begin addressing such endemic ambiguity, this paper seeks to make 3 contributions: 1) the replication and results confirmation of a leading (and generalisable) technique; 2) testing straightforward modifications of the technique likely to improve performance; and 3) the extension of the technique to a novel and complimentary type of crisis-relevant information to demonstrate it’s generalisability.

Item Type: Conference Proceedings
Keywords: Social Media, Crisis Informatics, CNN, Twitter, Word Embeddings, Event Detection, Eyewitness Detection
Schools and Departments: School of Engineering and Informatics > Informatics
Related URLs:
SWORD Depositor: Mx Elements Account
Depositing User: Mx Elements Account
Date Deposited: 24 Mar 2020 15:10
Last Modified: 07 Jul 2020 15:54
URI: http://sro.sussex.ac.uk/id/eprint/90527

View download statistics for this item

📧 Request an update