Home Location Estimation Using Weather Observation Data
This addresses the need for more accurate home location estimation from social media data, which is incremental as it builds on existing methods by incorporating weather data.
The paper tackles the problem of estimating Twitter users' home locations by using weather observation data from AMeDAS, achieving effective results with improved accuracy under certain conditions.
We can extract useful information from social media data by adding the user's home location. However, since the user's home location is generally not publicly available, many researchers have been attempting to develop a more accurate home location estimation. In this study, we propose a method to estimate a Twitter user's home location by using weather observation data from AMeDAS. In our method, we first estimate the weather of the area posted by an estimation target user by using the tweet, Next, we check out the estimated weather against weather observation data, and narrow down the area posted by the user. Finally, the user's home location is estimated as which areas the user frequently posts from. In our experiments, the results indicate that our method functions effectively and also demonstrate that accuracy improves under certain conditions.