The goal of ConronaVis is to use tweets as the information shared by the people to visualize topic modeling, study subjectivity and to model the human emotions during the COVID-19 pandemic. The main objective is to explore the psychology and behavior of the societies at large which can assist in managing the economic and social crisis during the ongoing pandemic as well as the after-effects of it. The novel coronavirus (COVID-19) pandemic forced people to stay at home to reduce the spread of the virus by maintaining the social distancing. However, social media is keeping people connected both locally and globally. People are sharing information (e.g. personal opinions, some facts, news, status, etc.) on social media platforms which can be helpful to understand the various public behavior such as emotions, sentiments, and mobility during the ongoing pandemic. In this paper, we describe the CoronaVis Twitter dataset (focused on the United States) that we have been collecting from early March 2020. The dataset is available to the research community at https://github.com/mykabir/COVID19. We would like to share this data with the hope that it will enable the community to find out more useful insights and create different applications and models to fight with COVID-19 pandemic and the future pandemics as well.