  Food choice is a complex phenomenon shaped by factors such as taste,
ambience, culture or weather. In this paper, we explore food-related tweeting
in different weather conditions. We inspect a Latvian food tweet dataset
spanning the past decade in conjunction with a weather observation dataset
consisting of average temperature, precipitation, and other phenomena. We find
which weather conditions lead to specific food information sharing;
automatically classify tweet sentiment and discuss how it changes depending on
the weather. This research contributes to the growing area of large-scale
social network data understanding of food consumers' choices and perceptions.
