In this study, we investigate whether public awareness of positive or negative possible incidents pertaining to the bitcoin ecosystem are related to bitcoin price and we model bitcoin price volatility taking into consideration public awareness. We take a middle-of-the-road approach, by using a simpler – and thus less data demanding - proxy for public awareness compared to studies that have used complex models that include many parameters to capture the relationships and factors in the ecosystem, but at the same time, a richer approach compared to approaches that simply use the volume of searches for “bitcoin” and its “price” as a proxy in their models. Specifically, we use six different Google Trends queries as proxies in our models: three searches for positive incidents, and three for negative ones. We employ a dataset with monthly price data that covers the time period from September 1st 2011 to December 31st 2019 and we use GARCH and EGARCH models to test whether public awareness of positive or negative possible incidents pertaining to the bitcoin ecosystem is related to bitcoin price and to model price volatility. Results show that majority of our proxies of public awareness are significantly related to price. Moreover, our EGARCH model has detected an asymmetry pertaining to the price volatility’s reaction to price news, specifically an “anti-leverage effect”, that is, the price volatility is more sensitive to good financial news rather to bad news. In addition, we detected a significant effect of both old and novel news.