In this paper, we try to examine the relationship between the Bitcoin price, social media metrics and the intensity of Covid-19 pandemic. We also attempt to investigate the behavior of Bitcoin volatility during such pandemic. For this end, we use the error correction model, Co-integration processing tool and vector error correction model to detect potential transmission mechanisms among different variables and the dynamic coupling between them. We also apply the GARCH-type models to better apprehend the behavior of Bitcoin volatility. Our results clearly display the short- and long term evidences of the relationshipbetween the Bitcoin price, severity of the Covid-19 health crisis and social media metrics. Moreover, there is strong evidence related to the information content of social media during turbulent phases. We also report some distinctive and salient features of Bitcoin volatility. The information spillover from pandemic-related news to the Bitcoin prices is well-documented. Using the Covid-19 deaths and confirmed cases can be considered as measure of pandemic severity. As well, the information transmission mechanism is well-documented through social media which seems to have an added value during the stressful periods. Such analysis could have insightful implications for investors in crypto-currency market.