Toponym-based geotagging for observing precipitation from social and scientific data streams

Abstract

Weather is a typical topic of daily conversations, so it is a natural idea to use social data to observe weather. Geotagging is a key to use social data for weather applications because weather is a highly localized phenomenon on the earth. Hence we developed software called GeoNLP for toponym-based geotagging, and applied it to Twitter data stream to find toponyms (place names) from Japanese tweets talking about precipitation events. We observed that less than 10 percent of the tweets contain toponym information, but it can capture precipitation events for each place. We also show temporal relationship between rain events and tweets. A case study shows that the relative number of tweets about rain and snow indicates the status of weather. In a few months, we collected almost million tweets about precipitation events with toponyms, but bias of tweets toward highly populated area is a big problem for applying the method to rural areas. The result indicates that social data streams can be used as complementary data source to scientific data streams.