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View all- Hironaka SYoshida MUmemura K(2021)Cross-Country Analysis of User Profiles for Graph-Based Location EstimationIEEE Access10.1109/ACCESS.2021.30865239(168831-168839)Online publication date: 2021
User’s Centrality Analysis for Home Location Estimation
Pages 59 - 63
Abstract
User attributes, such as home location, are useful for many applications. Many researchers have been tackling how to estimate users’ home locations using relationships among users. It is known that the home locations of certain users, such as celebrities, are hard to estimate using relationships. However, because estimating the home locations of all celebrities is not actually hard, it is important to clarify the characteristics of users whose home locations are hard to estimate. We analyze whether centralities, which represent users’ characteristics, and the tendency to have the same home locations as friends are related. The results indicate that PageRank and HITS scores are related to whether users have the same home location as friends, and that users with higher HITS scores have the same home location as their friends less often. This result indicates that there are two types of users whose home locations are difficult to estimate: hub users who follow many celebrities and authority users who are celebrities.
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October 2019
326 pages
ISBN:9781450369886
DOI:10.1145/3358695
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Published: 14 October 2019
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WI '19
WI '19: IEEE/WIC/ACM International Conference on Web Intelligence
October 14 - 17, 2019
Thessaloniki, Greece
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View all- Hironaka SYoshida MUmemura K(2021)Cross-Country Analysis of User Profiles for Graph-Based Location EstimationIEEE Access10.1109/ACCESS.2021.30865239(168831-168839)Online publication date: 2021
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