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Analysis Of Public Sentiment Of Covid-19 Pandemic, Vaccines, And Lockdowns, Devinesh Singh
Analysis Of Public Sentiment Of Covid-19 Pandemic, Vaccines, And Lockdowns, Devinesh Singh
Master's Projects
CoV-2 pandemic prompted lockdown measures to be implemented worldwide; these directives were implemented nationwide to stunt the spread of the infection. Throughout the lockdowns, millions of individuals resorted to social media for entertainment, communicate with friends and family, and express their opinions about the pandemic. Simultaneously, social media aided in the dissemination of misinformation, which has proven to be a threat to global health. Sentiment analysis, a technique used to analyze textual data, can be used to gain an overview of public opinion behind CoV-2 from Twitter and TikTok. The primary focus of the project is to build a deep …
Analyzing Public Sentiment On Covid-19 Pandemic, Pradeepika Gedupudi
Analyzing Public Sentiment On Covid-19 Pandemic, Pradeepika Gedupudi
Master's Projects
Sentiment analysis is a method of understanding the user sentiment expressed in the form of text. Social media is the best place to capture the public's opinion regarding how they feel about current events. The Corona Virus Disease-2019 (COVID-19) is one of the worst pandemics we have experienced so far. An important observation is that this pandemic has not only affected the public's physical health but also took a toll on their mental health. Reddit is a social news discussion site where people discuss topics around current affairs in smaller groups called subreddits. The project's primary focus is to build …
Fake News Analysis And Graph Classification On A Covid-19 Twitter Dataset, Kriti Gupta
Fake News Analysis And Graph Classification On A Covid-19 Twitter Dataset, Kriti Gupta
Master's Projects
Earlier researches have showed that the spread of fake news through social media can have a huge impact to society and also to individuals in an extremely negative way. In this work we aim to study the spread of fake news compared to real news in a social network. We do that by performing classical social network analysis to discover various characteristics, and formulate the problem as a binary classification, where we have graphs modeling the spread of fake and real news. For our experiments we rely on how news are propagated through a popular social media services such as …