att_abstract={{Emotions influence people's behavior in a profound way. Feelings like happiness, hope, fear, boredom, anger, anxiety or relaxation affect the way people behave and interact with one another. However, there is often a strong correlation between the environment and the way people feel, e.g., the emotions associated with a hospital are typically very different from those associated with an amusement park or a promenade. The aim of an {em emotion map/} is to represent and depict interrelationships between emotions and geographic locations. Such maps can provide answers to various questions about how people feel at various places or at different times of the day. They can facilitate a search for places where people express a certain emotion. In this paper, we introduce a new approach of creating emotion maps from a large collection of geotagged social-media posts. We discuss potential usages of such maps. We describe a preliminary study, to illustrate some of the challenges in the creation of emotion maps. We present a model to query and utilize emotion maps, and we demonstrate creation of emotion maps by applying emotion analysis to millions of geotagged tweets. }},
	att_copyright_notice={{(c) ACM, 2017. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in SIGSPATIAL workshop {{, 2017-11-07}}.
	att_tags={Emotion analysis,  sentiment analysis,  emotion maps,  geosocial data,  emotional contagion,  social media,  geotagged tweets},
	author={Yaron Kanza and Yerach Doytsher and Ben Galon},
	institution={{SIGSPATIAL workshop}},
	title={{Emotion Maps based on Geotagged Posts in the Social Media}},