Research Question <\/p>\n
Define a research question that you are interested in. This should be stated in a single sentence. <\/p>\n
The question is: What is the impact of covid-19 pandemic on the prevalence of depression in Saudi Arabia by analyzing data from twitter?<\/p>\n
It focuses on 3 elements: 1- depression during the pandemic 2- in Saudi Arabia 3- collecting data from twitter<\/p>\n
Why we choose twitter as our data source?<\/p>\n
it is the most popular social media app in KSA <\/p>\n
According to psychological studies people lend to express their feeling anonymously on social media due to the fear of being criticize. <\/p>\n
It is used in many monitoring of mental health applications <\/p>\n
it used in many researches because it easy to obtain data from Twitter through its APIs<\/p>\n
The duration we consider is the whole year of 2020 with selected words<\/p>\n
– Depression? <\/p>\n
Depression is a common and serious medical illness that negatively affects how you feel, the way you think and how you act. Fortunately, it is also treatable. Depression causes feelings of sadness and\/or a loss of interest in activities you once enjoyed. It can lead to a variety of emotional and physical problems and can decrease your ability to function at work and at home. <\/p>\n
– How it is related to Covid pandemic? <\/p>\n
During the pandemic, about 4 in 10 adults in the U.S. have reported symptoms of anxiety or depressive disorder, a share that has been largely consistent, up from one in ten adults who reported these symptoms from January to June 2019. A KFF Health Tracking Poll from July 2020 also found that many adults are reporting specific negative impacts on their mental health and well-being, such as difficulty sleeping (36%) or eating (32%), increases in alcohol consumption or substance use (12%), and worsening chronic conditions (12%), due to worry and stress over the coronavirus. As the pandemic wears on, ongoing and necessary public health measures expose many people to experiencing situations linked to poor mental health outcomes, such as isolation and job loss and financial breakdowns. <\/p>\n
– Depression in Saudi Arabia during the pandemic (Define the practical and theoretical significance of your research question.) Knowing the real numbers of the depression in Saudi Arabia helps us visualize the size of the problem and prepare to build an awareness and treatment plan to help people and provide the best treatment solutions before the current situation gets worse. <\/p>\n
– Does it address a gap in the existing research? <\/p>\n
Most of the current research didn\u2019t focus on depression in particular like many other diseases. few of research focused on depression and it was limited by using general surveys. Which will not provide reliability as in Twitter. On Twitter, people feel comfortable expressing their feelings and emotions on a daily basis. Thus, it provides us with a set of data that can be used to know the true extent of depression in Saudi Arabia.<\/p>\n
Why Depression<\/p>\n
Depression Impact in life.<\/p>\n
Source of Depression.<\/p>\n
Predict How to Reduce Depression.<\/p>\n
11 –\u00a0https:\/\/www.mdpi.com\/1660-4601\/18\/15\/7857\/htm<\/p>\n
Why data collection using twitter?<\/p>\n
Source of Real-time Information.<\/p>\n
Classifier Models.<\/p>\n
12 –\u00a0https:\/\/aclanthology.org\/W11-0705.pdf<\/p>\n
Is it an instance of a more general problem?<\/p>\n
Depression It is a problem that affects most cultures around the world, but we are concentrating on our own country by using Twitter data to collect information from people, we were able to solve the problem.<\/p>\n
Why is our question important?<\/p>\n
it will be helpful in improving the psychological state in Saudi Arabia to increase people’s awareness of depression so that it can be recognized and treated.<\/p>\n
Why did we choose Twitter as the source of data?<\/p>\n
Must of the people from deferent Area in Saudi Arabia use Twitter to publish their information and diverse Tweets.<\/p>\n
\u201cIt showed an excellent solution that used word embedding and a collection of extracted features from Twitter to predict depression. The proposed model’s prediction performance was improved by using deep-learning techniques.\u201d<\/p>\n
Define the practical and theoretical significance of your research question. That is, how will it lead to improved practices and\/or improved theoretical understanding in the area? Does it address a gap in the existing research? <\/p>\n
Many research papers in mental health indicate the effect of COVID-19 on the mental health of the general population is significant. Our study should help decision-makers to understand the impact of corona on citizen’s depression and how people in KSA express themselves in order to decide how to solve this problem or how to identify early symptoms associated with depression and address them before it reaches very serious stage. Understanding the depression status in KSA during covid-19 will help the government to predict the impact of future health crisis on the citizen\u2019s mental health and to establish or boost mental health systems specialized in this area. <\/p>\n
The gap we found from existing researches: there is many papers address this issue but most of it did not study the people in KSA or they used distributed survey to identify the impact of corona on depression.<\/p>\n
Will it lead to improved practices in the area?<\/p>\n
The results we will acquire from twitter data may be useful in enhancing the psychological status of the society also People’s mental health may improve as a result of their increased knowledge and awareness.<\/p>\n
Does it address a gap in existing knowledge?<\/p>\n
Depression must be made more generally acknowledged in society in order to be properly treated We need to increase public awareness about depression because if it is not addressed, it can quickly escalate into a more serious illness.<\/p>\n
Initial Literature Review <\/p>\n
Conduct a review of the literature relating to this issue. Summarize previous research that has been carried out and the outstanding issues that remain to be resolved. <\/p>\n
How is our question different from previous research?<\/p>\n
Our question differs in that it covers all social groups and focuses on data collecting via Twitter, as well as focusing on numerous places in Saudi Arabia. Focusing in the depression on the pandemic.<\/p>\n
Lecturer review\u00a0<\/p>\n
What did previous studies focus on?<\/p>\n
Geographical Location.<\/p>\n
Gender.<\/p>\n
Targeted Sentiments.<\/p>\n
4- https:\/\/www.researchprotocols.org\/2020\/11\/e23748\/<\/p>\n
2-\u00a0https:\/\/www.mdpi.com\/1660-4601\/17\/24\/9183\/htm<\/p>\n
8-\u00a0https:\/\/www.mdpi.com\/2078-2489\/12\/2\/86\/htm<\/p>\n
9-\u00a0https:\/\/www.tandfonline.com\/doi\/full\/10.1080\/12460125.2020.1859745?casa_token=yyrak2d9ii8AAAAAiIAhJ42pj7S1xsXTJyEzcFv2UJTEV0lIVJumywGi0wT8tFyON8RtMEJrZY9zd0cQyKFGNpV4_w<\/p>\n
10 –\u00a0https:\/\/www.mdpi.com\/1424-8220\/21\/16\/5431<\/p>\n
This to know what has been done and what has not, and proofing that our research question did not answer before: <\/p>\n
We read a reasonable number of papers and these are the main ones:<\/p>\n
Subject <\/p>\n
Exist <\/p>\n
(similarities)<\/p>\n
Non-Exit<\/p>\n
(differences) <\/p>\n
Method Used<\/p>\n
A cross-sectional survey on the psychological impact of the COVID-19 pandemic on inflammatory bowel disease patients in Saudi Arabia<\/p>\n
1- depression in the pandemic 2- in Saudi Arabia<\/p>\n
3- using Twitter <\/p>\n
questionnaire <\/p>\n
Prevalence of Depression, Anxiety, and Stress among the General Population in Saudi Arabia during Covid-19 Pandemic<\/p>\n
1- depression in the pandemic 2- in Saudi Arabia<\/p>\n
3- using Twitter <\/p>\n
questionnaire. The questionnaire was uploaded online using social media platforms<\/p>\n
Public Concerns and Mental Health Changes Related to the COVID-19 Pandemic Lockdown in Saudi Arabia <\/p>\n
1- depression in the pandemic 2- in Saudi Arabia<\/p>\n
3- using Twitter <\/p>\n
survey on social media platforms (WhatsApp, and Twitter) to collect data<\/p>\n
A Mental Health Surveillance System for the General Population During the COVID-19 Pandemic: Protocol for a Multiwave Cross-sectional Survey Study<\/p>\n
1- depression in the pandemic<\/p>\n
2- in Saudi Arabia, 3- using Twitter <\/p>\n
questionnaire <\/p>\n
Mental Health Outcomes Amongst Health Care Workers During COVID 19 Pandemic in Saudi Arabia<\/p>\n
1- depression in the pandemic 2- in Saudi Arabia<\/p>\n
3- using Twitter <\/p>\n
The weblink to the questionnaire was sent to prospective participants through WhatsApp, Twitter, and official emails<\/p>\n
Depression and Obsessive-Compulsive Disorders Amid the COVID-19 Pandemic in Saudi Arabia<\/p>\n
1- depression in the pandemic 2- in Saudi Arabia<\/p>\n
3- using Twitter <\/p>\n
online surveys were distributed through social media platforms such as WhatsApp, Twitter, Instagram, Facebook, and LinkedIn<\/p>\n
The magnitude of COVID-19 related stress, anxiety and depression associated with intense mass media coverage in Saudi Arabia<\/p>\n
1- depression in the pandemic 2- in Saudi Arabia<\/p>\n
3- using Twitter <\/p>\n
A questionnaire was prepared and distributed online using different tools including WhatsApp, Twitter, and electronic mails<\/p>\n
Monitoring People\u2019s Emotions and Symptoms from Arabic Tweets during the COVID-19 Pandemic<\/p>\n
1- emotions in the pandemic 2- In Arab world 3- using Twitter <\/p>\n
in Saudi Arabia<\/p>\n
At a collection from Twitter. Arabic emotion lexicons were used to annotate a list of 300,000 tweets <\/p>\n
Prediction of depressed Arab women using their tweets<\/p>\n
1- depression in the pandemic 2- Arab world (woman only) 3- using Twitter <\/p>\n
in Saudi Arabia<\/p>\n
used different APIs to extract the Arabic tweets from Twitter.<\/p>\n
Theoretical Model <\/p>\n
Refine your research question into a theoretical model, consisting of constructs and relationships between them. Specify possible measures for each construct (i.e., operationalize your model) and draw a diagram summarizing your theoretical model. Try to incorporate existing theories from IS\/CS\/IT (or other disciplines) into your model if possible. <\/p>\n
Twint is an open-source Python library that is designed to collect tweets. It is a free tool that can be set up easily with no need for a Twitter account or the setting up of a Twitter API and it can collect almost all available tweets. Twint can collect data based on keywords, hashtags, dates, and location [14]. This research used the Twint tool with a combination of keywords and hashtags to collect two datasets of Arabic tweets about people\u2019s opinions on distance learning at each educational stage in Saudi Arabia.<\/p>\n
Cleaning & Preprocessing: remove irrelevant tweets, <\/p>\n
(Sentiment analysis classifier) Features Extraction and Selection: Natural language text cannot directly be processed by ML algorithms because text data is not computable. Therefore, a features extraction approach is implemented to convert text data into numerical vectors that the algorithms can process and work with. we did not choose how we really going to do it. For example: Term Frequency\/Inverse Document Frequency (TF-IDF). It is a numerical statistic that is used to measure the importance of each word. It is a simple, well-known feature extraction method used in natural language processing, classification, and recommendation tasks. This model is implemented through two main steps. Firstly, the number of occurrences or Term Frequency (TF) of each word in a tweet, is counted. Secondly, the frequency of each word occurring or Inverse Document Frequency (IDF) out of all tweets is calculated. The smaller TF-IDF values represent common words which indicates that they are not significant and verse versa.<\/p>\n
Sentiment analysis refers to identifying as well as classifying the sentiments that are expressed in the text source. Tweets are often useful in generating a vast amount of sentiment data upon analysis. These data are useful in understanding the opinion of the people about a variety of topics. Therefore, we need to develop an Automated Machine Learning Sentiment Analysis Model in order to compute the customer perception. Due to the presence of non-useful characters (collectively termed as the noise) along with useful data, it becomes difficult to implement models on them.<\/p>\n
Sensors | Free Full-Text | Sentiment Analysis of Arabic Tweets Regarding Distance Learning in Saudi Arabia during the COVID-19 Pandemic (mdpi.com)<\/p>\n
IJERPH | Free Full-Text | Understanding #WorldEnvironmentDay User Opinions in Twitter: A Topic-Based Sentiment Analysis Approach (mdpi.com)<\/p>\n","protected":false},"excerpt":{"rendered":"
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