| Record |
| Author |
Jeremy Diaz; Lise St. Denis; Maxwell B. Joseph; Kylen Solvik; Jennifer K. Balch |
| Title |
Classifying Twitter Users for Disaster Response: A Highly Multimodal or Simple Approach? |
Type |
Conference Article |
| Year |
2020 |
Publication |
ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2020 |
| Volume |
|
Issue |
|
Pages |
774-789 |
| Keywords |
User Classification, Disaster Response, Twitter, Model Comparison, Multimodal Deep Learning. |
| Abstract |
We report on the development of a classifier to identify Twitter users contributing first-hand information during a disaster. Identifying such users helps social media monitoring teams identify critical information that might otherwise slip through the cracks. A parallel study (St. Denis et al., 2020) demonstrates that Twitter user filtering creates an information-rich stream of content, but the best way to approach this task is unexplored. A user's profile contains many different “modalities” of data, including numbers, text, and images. To integrate these different data types, we constructed a multimodal neural network that combines the loss function of all modalities, and we compared the results to many individual unimodal models and a decision-level fusion approach. Analysis of the results suggests that unimodal models acting on Twitter users' recent tweets are sufficient for accurate classification. We demonstrate promising classification of Twitter users for crisis response with methods that are (1) easy to implement and (2) quick to both optimize and infer. |
| Address |
Institute for Computational and Data Sciences, The Penn State University Department of Geography, The Penn State University; CIRES, Earth Lab, University of Colorado, Boulder; CIRES, Earth Lab, University of Colorado, Boulder; CIRES, Earth Lab, Department of Geography, University of Colorado, Boulder; CIRES, Earth Lab, Department of Geography, University of Colorado, Boulder |
| Corporate Author |
|
Thesis |
|
| Publisher |
Virginia Tech |
Place of Publication |
Blacksburg, VA (USA) |
Editor |
Amanda Hughes; Fiona McNeill; Christopher W. Zobel |
| Language |
English |
Summary Language |
English |
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
978-1-949373-27-69 |
ISBN |
2411-3455 |
Medium |
|
| Track |
Social Media for Disaster Response and Resilie |
Expedition |
|
Conference |
17th International Conference on Information Systems for Crisis Response and Management |
| Notes |
jad6655@psu.edu |
Approved |
no |
| Call Number |
|
Serial |
2270 |
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