Is a Pretrained Model the Answer to Situational Awareness Detection on Social Media?

Simple item page
dc.contributor.authorLo, Siaw Ling
dc.contributor.authorLee, Kahhe
dc.contributor.authorZhang, Yuhao
dc.date.accessioned2022-12-27T19:02:43Z
dc.date.available2022-12-27T19:02:43Z
dc.date.issued2023-01-03
dc.description.abstractSocial media can be valuable for extracting information about an event or incident on the ground. However, the vast amount of content shared, and the linguistic variants of languages used on social media make it challenging to identify important situational awareness content to aid in decision-making for first responders. In this study, we assess whether pretrained models can be used to address the aforementioned challenges on social media. Various pretrained models, including static word embedding (such as Word2Vec and GloVe) and contextualized word embedding (such as DistilBERT) are studied in detail. According to our findings, a vanilla DistilBERT pretrained language model is insufficient to identify situation awareness information. Fine-tuning by using datasets of various event types and vocabulary extension is essential to adapt a DistilBERT model for real-world situational awareness detection.
dc.format.extent10
dc.identifier.doi10.24251/HICSS.2023.263
dc.identifier.isbn978-0-9981331-6-4
dc.identifier.other954cee6e-ded6-44f3-8fe1-3a162e116887
dc.identifier.urihttps://hdl.handle.net/10125/102894
dc.language.isoeng
dc.relation.ispartofProceedings of the 56th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectData Analytics, Data Mining, and Machine Learning for Social Media
dc.subjectbert
dc.subjectfine tuning
dc.subjectpretrained models
dc.subjectsituational awareness
dc.subjectvocabulary extension
dc.titleIs a Pretrained Model the Answer to Situational Awareness Detection on Social Media?
dc.type.dcmitext
prism.startingpage2110

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
0206.pdf
Size:
575.91 KB
Format:
Adobe Portable Document Format
Download

Collections

Data Analytics, Data Mining, and Machine Learning for Social Media