Twitter analyses for posts without weather terms.

<p>Panel (a) depicts the relationship between daily maximum temperatures and the rates of expressed sentiment for non-weather posts, aggregated to the city-level. It draws from the estimation of <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0195750#pone.0195750.e001" target="_blank">Eq 1</a> and plots the predicted change in expressed sentiment associated with each maximum temperature bin. Panel (b) depicts the relationship between daily precipitation and the rates of sentiment expression of non-weather posts, also drawing on estimation of <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0195750#pone.0195750.e001" target="_blank">Eq 1</a>. Shaded error bounds represent 95% confidence intervals calculated using heteroskedasticity-robust standard errors clustered on both city-year-month and day.