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Wireless Networks
Erschienen in: Wireless Networks 3/2022

09.01.2019

A multilayer recognition model for twitter user geolocation

verfasst von: Haina Tang, Xiangpeng Zhao, Yongmao Ren

Erschienen in: Wireless Networks | Ausgabe 3/2022

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Abstract

Geolocation is important for many emerging applications such as disaster management and recommendation system. In this paper, we propose a multilayer recognition model (MRM) to predict the city-level location for social network users, solely based on the user’s tweet content. Through a series of optimizations such as entity selection, spatial clustering and outlier filtering, suitable features are extracted to model the geographic coordinates of tweet users. Then, the Multinomial Naive Bayes is applied to classify the datasets into different groups. The model is evaluated by comparing with an existing algorithm on twitter datasets. The experimental results reveal that our method achieves a better prediction accuracy of 54.82% on the test set, and the average error is reduced to 400.97 miles at best.
Vorheriger Artikel Birds of prey: identifying lexical irregularities in spam on Twitter
Nächster Artikel Cost effective, rule based, big data analytical aggregation engine for investment portfolios

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Metadaten
Titel
A multilayer recognition model for twitter user geolocation
verfasst von
Haina Tang
Xiangpeng Zhao
Yongmao Ren
Publikationsdatum
09.01.2019
Verlag
Springer US
Erschienen in
Wireless Networks / Ausgabe 3/2022
Print ISSN: 1022-0038
Elektronische ISSN: 1572-8196
DOI
https://doi.org/10.1007/s11276-018-01897-1

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