<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Social media networks are an attractive and hot research area in the big data community because of their numerous active users. One of the most widely studied topics in social networks is the prediction from the public available data. Recently, researchers have successfully predicted many statistical and human properties from social media networks using different machine learning algorithms. In this paper, a new efficient and accurate algorithm is proposed to predict the country location of a Twitter user using his or her public information only. The proposed algorithm employs the public information of the Twitter user and that of his or her followers and friends to predict his or her location without using GPS data. A convenient data set of Twitter users is gathered and used to test our proposed algorithm using KNIME software. The proposed algorithm is compared with other state-of-the-art algorithms, and results showed that our proposed algorithm significantly outperforms other location detection algorithms by using Twitter users from different countries.</p>
</abstract>

Social media networks are an attractive and hot research area in the big data community because of their numerous active users. One of the most widely studied topics in social networks is the prediction from the public available data. Recently, researchers have successfully predicted many statistical and human properties from social media networks using different machine learning algorithms. In this paper, a new efficient and accurate algorithm is proposed to predict the country location of a Twitter user using his or her public information only. The proposed algorithm employs the public information of the Twitter user and that of his or her followers and friends to predict his or her location without using GPS data. A convenient data set of Twitter users is gathered and used to test our proposed algorithm using KNIME software. The proposed algorithm is compared with other state-of-the-art algorithms, and results showed that our proposed algorithm significantly outperforms other location detection algorithms by using Twitter users from different countries.

A novel algorithm for estimation of Twitter users location using public available information

International Journal on Smart Sensing and Intelligent Systems

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

running-head

Social media networks are an attractive and hot research area in the big data community because of their numerous active users. One of the most widely studied...

A novel algorithm for estimation of Twitter users location using public available information

Article Category: Research-Article

Publié en ligne: 09 juil. 2020

Pages: 1 - 10

Reçu: 10 déc. 2019

DOI: https://doi.org/10.21307/ijssis-2020-012

Mots clés
Twitter, Social media, KNIME, Followers, Time zone, Location, Friends

© 2020 Yasser Almadany et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

A novel algorithm for estimation of Twitter users location using public available information

Article Category: Research-Article

Publié en ligne: 09 juil. 2020

Pages: 1 - 10

Reçu: 10 déc. 2019

DOI: https://doi.org/10.21307/ijssis-2020-012

Mots clésTwitter, Social media, KNIME, Followers, Time zone, Location, Friends

© 2020 Yasser Almadany et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Mots clés
Twitter, Social media, KNIME, Followers, Time zone, Location, Friends