Mohammad Ehsan Basiri; Shirin Habibi; Shahla Nemati
Abstract
With the spread of Covid-19 disease, quarantine, and social isolation, people are increasingly posting their opinions about the coronavirus on social networks such as Twitter. However, no study has yet been reported to analyze online opinions of individuals in order to understand their feelings about ...
Read More
With the spread of Covid-19 disease, quarantine, and social isolation, people are increasingly posting their opinions about the coronavirus on social networks such as Twitter. However, no study has yet been reported to analyze online opinions of individuals in order to understand their feelings about the Covid-19 epidemic in Iran. This study analyzes the emotions in the opinions of the Iranian people on the social network Twitter during the Corona crisis. For this purpose, a deep neural network model is presented. As there is no labeled dataset of Covid-19 tweets, the proposed model is first trained on the Stanford University Sentiment140 dataset, which contains 1.6 million tweets, and then used to classify the two classes of emotions contained in the collected corona-related tweets in Iran. The results show that the percentage of tweets with negative emotions is significantly higher than positive tweets. Also, the change in negative emotions of people in different months is proportional to the change in patient statistics.
majid kalantari; Seyed Rasoul Albourzi Gahroei; Elaheh Lotfizadeh Dehkurdi; Ahmad reza Kasraei
Abstract
The global crisis caused by the spread of the coronavirus has created new management scenarios in various economic and social sectors. In this study, by introducing smart water meters and examining their effectiveness in the process of remote reading of water consumption of subscribers, we seek to use ...
Read More
The global crisis caused by the spread of the coronavirus has created new management scenarios in various economic and social sectors. In this study, by introducing smart water meters and examining their effectiveness in the process of remote reading of water consumption of subscribers, we seek to use the benefits of information technology solutions in the water industry to reduce or eliminate the risks of future crises. To do so and for the first time in the country by implementing of data obtained from nationwide projects as well as using paired t test, we will examine changes in water use before and after the implementation of smart household water meters and during the outbreak of the virus, according to which the positive impact of the deployment of such smart measuring equipment in the face of the water shortage crisis caused by the deployment of the virus has been confirmed.
