  The coronavirus disease, also known as the COVID-19, is an ongoing pandemic
of a severe acute respiratory syndrome. The pandemic has led to the
cancellation of many religious, political, and cultural events around the
world. A huge number of people have been stuck within their homes because of
unprecedented lockdown measures taken globally. This paper examines the
reaction of individuals to the virus outbreak-through the analytical lens of
specific hashtags on the Instagram platform. The Instagram posts are analyzed
in an attempt to surface commonalities in the way that individuals use visual
social media when reacting to this crisis. After collecting the data, the posts
containing the location data are selected. A portion of these data are chosen
randomly and are categorized into five different categories. We perform several
manual analyses to get insights into our collected dataset. Afterward, we use
the ResNet-50 convolutional neural network for classifying the images
associated with the posts, and attention-based LSTM networks for performing the
caption classification. This paper discovers a range of emerging norms on
social media in global crisis moments. The obtained results indicate that our
proposed methodology can be used to automate the sentiment analysis of mass
people using Instagram data.
