Home Location Estimation Using Weather Observation Data

TL;DR

This paper presents a novel method for estimating Twitter users' home locations by correlating their tweet content with local weather observation data, improving accuracy through weather-based filtering.

Contribution

It introduces a weather-based approach to home location estimation using social media data, enhancing accuracy over previous methods.

Findings

Method effectively estimates home locations from tweets.

Accuracy improves with specific weather conditions.

Demonstrates practical applicability of weather data in social media analysis.

Abstract

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.