Understanding Social Media Engagement in Response to Disaster Fundraising Attempts During Australian Bushfires

Yohei Nii; Chahat Raj; Muhammad Salman Tiwana; Mahendra Samarawickrama; Simeon Simoff; Tony Jan; Mukesh Prasad

doi:10.1007/978-3-031-31164-2_23

Understanding Social Media Engagement in Response to Disaster Fundraising Attempts During Australian Bushfires

Yohei Nii, Chahat Raj, Muhammad Salman Tiwana, Mahendra Samarawickrama, Simeon Simoff, Tony Jan, Mukesh Prasad

Design and Creative Technologies

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This article studies the impact of social media posts specific to a disaster incident – the Australian bushfires of 2019–2020. We analyse the social media content posted by the Australian Red CrossOrganization’s Facebook page, and the user generated comments on their posts. We identify user sentiments in response to the natural disaster and towards the organization’s fundraising attempts. This study shall enable the stakeholders to understand how the general public reacts to fundraising protocols at the times of unforeseen disasters. It shall also allow policymakers to design sustainable goals to promote healthy donation behaviour through social media platforms. Further, we also analyse how benchmark Natural Language Processing tools, namely, VADER, Afinn, and TextBlob, perform in an unsupervised scenario to perform sentiment classification. OverallVADER results were best among the other algorithms Afinn and TextBlob in the term of accuracy, precision, recall and f1 score performance measure.

Original language	English
Title of host publication	Proceedings in Adaptation, Learning and Optimization book series (PALO,volume 17)
Subtitle of host publication	International Conference on Intelligent Vision and Computing
Publisher	Springer Nature
Pages	277-289
DOIs	https://doi.org/10.1007/978-3-031-31164-2_23
Publication status	Published - 2023

Keywords

Sentiment analysis
social media
disaster fundraising
Australian bushfires

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-031-31164-2_23

Cite this

Nii, Y., Raj, C., Tiwana, M. S., Samarawickrama, M., Simoff, S., Jan, T., & Prasad, M. (2023). Understanding Social Media Engagement in Response to Disaster Fundraising Attempts During Australian Bushfires. In Proceedings in Adaptation, Learning and Optimization book series (PALO,volume 17): International Conference on Intelligent Vision and Computing (pp. 277-289). Springer Nature. https://doi.org/10.1007/978-3-031-31164-2_23

@inproceedings{7a575526e7694037905b54112f925c9f,

title = "Understanding Social Media Engagement in Response to Disaster Fundraising Attempts During Australian Bushfires",

abstract = "This article studies the impact of social media posts specific to a disaster incident – the Australian bushfires of 2019–2020. We analyse the social media content posted by the Australian Red CrossOrganization{\textquoteright}s Facebook page, and the user generated comments on their posts. We identify user sentiments in response to the natural disaster and towards the organization{\textquoteright}s fundraising attempts. This study shall enable the stakeholders to understand how the general public reacts to fundraising protocols at the times of unforeseen disasters. It shall also allow policymakers to design sustainable goals to promote healthy donation behaviour through social media platforms. Further, we also analyse how benchmark Natural Language Processing tools, namely, VADER, Afinn, and TextBlob, perform in an unsupervised scenario to perform sentiment classification. OverallVADER results were best among the other algorithms Afinn and TextBlob in the term of accuracy, precision, recall and f1 score performance measure.",

keywords = "Sentiment analysis, social media, disaster fundraising, Australian bushfires",

author = "Yohei Nii and Chahat Raj and Tiwana, {Muhammad Salman} and Mahendra Samarawickrama and Simeon Simoff and Tony Jan and Mukesh Prasad",

year = "2023",

doi = "10.1007/978-3-031-31164-2_23",

language = "English",

pages = "277--289",

booktitle = "Proceedings in Adaptation, Learning and Optimization book series (PALO,volume 17)",

publisher = "Springer Nature",

}

Nii, Y, Raj, C, Tiwana, MS, Samarawickrama, M, Simoff, S, Jan, T & Prasad, M 2023, Understanding Social Media Engagement in Response to Disaster Fundraising Attempts During Australian Bushfires. in Proceedings in Adaptation, Learning and Optimization book series (PALO,volume 17): International Conference on Intelligent Vision and Computing. Springer Nature, pp. 277-289. https://doi.org/10.1007/978-3-031-31164-2_23

Understanding Social Media Engagement in Response to Disaster Fundraising Attempts During Australian Bushfires. / Nii, Yohei; Raj, Chahat; Tiwana, Muhammad Salman et al.
Proceedings in Adaptation, Learning and Optimization book series (PALO,volume 17): International Conference on Intelligent Vision and Computing. Springer Nature, 2023. p. 277-289.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Understanding Social Media Engagement in Response to Disaster Fundraising Attempts During Australian Bushfires

AU - Nii, Yohei

AU - Raj, Chahat

AU - Tiwana, Muhammad Salman

AU - Samarawickrama, Mahendra

AU - Simoff, Simeon

AU - Jan, Tony

AU - Prasad, Mukesh

PY - 2023

Y1 - 2023

N2 - This article studies the impact of social media posts specific to a disaster incident – the Australian bushfires of 2019–2020. We analyse the social media content posted by the Australian Red CrossOrganization’s Facebook page, and the user generated comments on their posts. We identify user sentiments in response to the natural disaster and towards the organization’s fundraising attempts. This study shall enable the stakeholders to understand how the general public reacts to fundraising protocols at the times of unforeseen disasters. It shall also allow policymakers to design sustainable goals to promote healthy donation behaviour through social media platforms. Further, we also analyse how benchmark Natural Language Processing tools, namely, VADER, Afinn, and TextBlob, perform in an unsupervised scenario to perform sentiment classification. OverallVADER results were best among the other algorithms Afinn and TextBlob in the term of accuracy, precision, recall and f1 score performance measure.

AB - This article studies the impact of social media posts specific to a disaster incident – the Australian bushfires of 2019–2020. We analyse the social media content posted by the Australian Red CrossOrganization’s Facebook page, and the user generated comments on their posts. We identify user sentiments in response to the natural disaster and towards the organization’s fundraising attempts. This study shall enable the stakeholders to understand how the general public reacts to fundraising protocols at the times of unforeseen disasters. It shall also allow policymakers to design sustainable goals to promote healthy donation behaviour through social media platforms. Further, we also analyse how benchmark Natural Language Processing tools, namely, VADER, Afinn, and TextBlob, perform in an unsupervised scenario to perform sentiment classification. OverallVADER results were best among the other algorithms Afinn and TextBlob in the term of accuracy, precision, recall and f1 score performance measure.

KW - Sentiment analysis

KW - social media

KW - disaster fundraising

KW - Australian bushfires

U2 - 10.1007/978-3-031-31164-2_23

DO - 10.1007/978-3-031-31164-2_23

M3 - Conference contribution

SP - 277

EP - 289

BT - Proceedings in Adaptation, Learning and Optimization book series (PALO,volume 17)

PB - Springer Nature

ER -

Nii Y, Raj C, Tiwana MS, Samarawickrama M, Simoff S, Jan T et al. Understanding Social Media Engagement in Response to Disaster Fundraising Attempts During Australian Bushfires. In Proceedings in Adaptation, Learning and Optimization book series (PALO,volume 17): International Conference on Intelligent Vision and Computing. Springer Nature. 2023. p. 277-289 doi: 10.1007/978-3-031-31164-2_23

Understanding Social Media Engagement in Response to Disaster Fundraising Attempts During Australian Bushfires

Abstract

Keywords

UN SDGs

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