COVID-19 impact on financial security: evidence from the National Public Engagement Survey in Wales

Allen, JA; Cotter-Roberts, Andrew; Kadel, Rajendra; Hughes, Karen; Dyakova, M

doi:10.1093/eurpub/ckab165.324

Cited by 2 publications

(1 citation statement)

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“…Even after the pandemic's peak, these negative consequences on public wellbeing still hold so far. In an attempt to assess public wellbeing, many governments have conducted several country-wide surveys to assess the public's wellbeing (Allen et al 2021;Shahriarirad et al 2021;Son et al 2020;Thapa et al 2020). However, the public wellbeing surveys used are deficient in inferring a holistic insight into the public's wellbeing due to the content limitation (i.e., intensive use of closed-ended questions), the subjectivity of the analysis, time limitations, geographic limitations, and other factors (Jones et al 2008;Schwartz et al 2014).…”

Section: Introductionmentioning

confidence: 99%

Public wellbeing analytics framework using social media chatter data

Ismail

Serhani

Hussien

et al. 2022

Soc. Netw. Anal. Min.

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Public wellbeing has always been crucial. Many governments around the globe prioritize the impact of their decisions on public wellbeing. In this paper, we propose an end-to-end public wellbeing analytics framework designed to predict the public’s wellbeing status and infer insights through the continuous analysis of social media content over several temporal events and across several locations. The proposed framework implements a novel distant supervision approach designed specifically to generate wellbeing-labeled datasets. In addition, it implements a wellbeing prediction model trained on contextualized sentence embeddings using BERT. Wellbeing predictions are visualized using several spatiotemporal analytics that can support decision-makers in gauging the impact of several government decisions and temporal events on the public, aiding in improving the decision-making process. Empirical experiments evaluate the effectiveness of the proposed distant supervision approach, the prediction model, and the utility of the produced analytics in gauging the public wellbeing status in a specific context.

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Section: Introductionmentioning

confidence: 99%

Public wellbeing analytics framework using social media chatter data

Ismail

Serhani

Hussien

et al. 2022

Soc. Netw. Anal. Min.

View full text Add to dashboard Cite

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Triggers and Tweets: Implicit Aspect-Based Sentiment and Emotion Analysis of Community Chatter Relevant to Education Post-COVID-19

Ismail

Khalil

Hussein

et al. 2022

BDCC

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This research proposes a well-being analytical framework using social media chatter data. The proposed framework infers analytics and provides insights into the public’s well-being relevant to education throughout and post the COVID-19 pandemic through a comprehensive Emotion and Aspect-based Sentiment Analysis (ABSA). Moreover, this research aims to examine the variability in emotions of students, parents, and faculty toward the e-learning process over time and across different locations. The proposed framework curates Twitter chatter data relevant to the education sector, identifies tweets with the sentiment, and then identifies the exact emotion and emotional triggers associated with those feelings through implicit ABSA. The produced analytics are then factored by location and time to provide more comprehensive insights that aim to assist the decision-makers and personnel in the educational sector enhance and adapt the educational process during and following the pandemic and looking toward the future. The experimental results for emotion classification show that the Linear Support Vector Classifier (SVC) outperformed other classifiers in terms of overall accuracy, precision, recall, and F-measure of 91%. Moreover, the Logistic Regression classifier outperformed all other classifiers in terms of overall accuracy, recall, an F-measure of 81%, and precision of 83% for aspect classification. In online experiments using UAE COVID-19 education-related data, the analytics show high relevance with the public concerns around the education process that were reported during the experiment’s timeframe.

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COVID-19 impact on financial security: evidence from the National Public Engagement Survey in Wales

Cited by 2 publications

References 0 publications

Public wellbeing analytics framework using social media chatter data

Public wellbeing analytics framework using social media chatter data

Triggers and Tweets: Implicit Aspect-Based Sentiment and Emotion Analysis of Community Chatter Relevant to Education Post-COVID-19

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