Tracking And Understanding Public Reaction During COVID -19: S audi A rabia As A Use Case (2020)

Abstract: The coronavirus disease of 2019 (COVID-19) has a huge impact on economies and societies around the world. While governments are taking extreme measures to reduce the spread of the virus, people are getting affected by these new measures. With restrictions like lockdown and social distancing, it became important to understand the emotional response of the public towards the pandemic. In this paper, we study the reaction of Saudi Arabia citizens towards the pandemic. We utilize a collection of Arabic tweets that were sent during 2020, primarily through hashtags that were originated from Saudi Arabia. Our results showed that people had kept a positive reaction towards the pandemic. This positive reaction was at its highest at the beginning of the COVID-19 crisis and started to decline as time passes. Overall, the results showed that people were so supportive of each other through this pandemic. This research can help researchers and policymakers in understanding the emotional effect of a pandemic on societies.

## introduction covid-19 was declared a pandemic by the world health organization (who) on january 30, 2020 @xcite . the spread of covid-19 around the world has raised many concerns and uncertainties about the future. several epidemic periods have been observed in the world. in recent years, epidemics have increased as globalization facilitates contagion. the current pandemic has affected 213 countries, with more than one and a half million confirmed cases to date @xcite . to overcome the rapid spread of the virus, the world health organization (who) has suggested that isolation and self-quarantine are among the major ways to stop this pandemic from spreading at such an alarming rate @xcite . china has witnessed the benefits of one of the largest lockdowns at the start of this pandemic, where it locked down 20 provinces and regions @xcite . one of the most widely used social media platforms is twitter, popular for its accessibility and ease of information sharing @xcite . with the increase in precautionary measures such as lockdowns and curfews, people have turned to social media platforms to continue their social interactions, with a 61% increase in the usage of these platforms @xcite . with 13.8 million active users out of 24 million internet users (91% of the total population), saudi arabia is among the countries with the highest number of twitter users among its online population @xcite . moreover, saudi arabia is producing 40% of all tweets in the arab world @xcite . since a majority of online communication is recorded in the form of text data, measuring the emotions around covid-19 will be a central part of understanding and addressing the impacts of the covid-19 situation on people. moreover, the rapid spread of covid-19 infections has created a strong need for understanding the development of mass sentiment in pandemic scenarios. because of the uncertainty that is provoked by the covid-19 situation and the many and long-lasting preventative measures applied, it is of vital importance to understand how governments, ngos, and social organizations can help those who are most affected by the situation and where they are located. in order to do so, understanding the emotions, worries, and concerns that people have and possible coping strategies is important. previous research in sentiment analysis has used the twitter platform to collect tweets in various languages, such as indian , nepali, turkish, arabic, and spanish to detect the tweets' sentiments during a crisis @xcite @xcite @xcite @xcite @xcite . recently, the arabic language has gained more attention in sentiment analysis since it is becoming widely used in social media platforms @xcite . several studies on arabic sentiment analysis have recently been conducted to detect opinions about crises and epidemics @xcite @xcite . in this study, we try to understand saudis' reactions towards this pandemic, by answering three questions: -what is the overall sentiment of saudi citizens towards the pandemic? -what is the geographical distribution of different sentiments? -how have saudis reacted to different topics/decisions related to the pandemic? analyzing emotions regarding covid-19 restrictions will be a central part of understanding and addressing the impacts of pandemics on people. moreover, this study might inform the development of models of social behavior that fit the saudi arabian culture. our results showed a high level of solidarity within society, where people were expressing positive sentiments in hashtags related to social solidarity. also, our results showed there was a high correlation between the number of covid-19 cases and the geolocation of the tweets. in the remainder of the paper, we first synthesize previous work and background information and relate that to our work. after that, we describe the dataset used for the analysis. we then discuss sentiment identification. finally, we discuss the findings, conclusions, and proposed directions for future research. ## data our primary dataset is a repository of tweet ids. each corresponds to arabic content posted on twitter and related to the coronavirus pandemic (addawood, 2020). the repository contains 3.8 million tweet ids for the period of january 1, 2020, to april 10, 2020. tweets were compiled utilizing crimson hexagon, which is a social media analytic platform that provides paid data stream access. the data was collected by identifying a list of trending hashtags and keywords mostly used by the public. the hashtags were categorized based on their meaning, how users were interacting with it, and who started the hashtags. the categorization was done by @xcite . to collect a comprehensive dataset, 70 keywords and hashtags were categorized based on how they were oriented and used in conversations. ## ethical considerations this research was conducted respecting the collected tweets and their authors' opinions. we also ensured that all tweets were collected without any modifications to their context, location, or all other related attributes. moreover, the annotation process was done using several lexicons to identify the tweets' polarity in order to avoid researcher intervention. the shared results are objective, transparent, and unbiased, so they meet the researchers' requirements. furthermore, this research does not discuss any political arguments. rather, it mainly focuses on citizens' opinions of the precautionary measures applied in saudi arabia by exploring the most popular hashtags that circulated in twitter during the studied time period. this research can be used for applications that might affect people negatively. it can be used to manipulate public opinion and drive them toward specific political agendas through a better understanding of people's reactions toward political topics. moreover, when applying a new dataset that differs from our original data with new domains or a less commonly presented population, the models used in this study may degrade. thus, the results of the evaluation metrics can differ due to the biases brought by the new dataset since our model's results, as demonstrated in ## conclusion in this research, our goal was to get a better understanding of saudis' reactions to the coronavirus. to do so, we explored the sentiments shared by the public with a focus on the analysis of saudi dialect. such understanding can contribute to fast