Features combination for gender recognition on Twitter users

被引：0

作者：

Fernandez, Daniela ^{[1
]}

Moctezuma, Daniela ^{[1
]}

Siordia, Oscar S. ^{[1
]}

机构：

[1] Ctr Invest Geog & Geomat Ing Jorge L Tamayo AC, Aguascalientes, Mexico

来源：

2016 IEEE INTERNATIONAL AUTUMN MEETING ON POWER, ELECTRONICS AND COMPUTING (ROPEC) | 2016年

关键词：

Gender recognition; Twitter; social networks;

D O I：

暂无

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

Gender classification in social platforms and social media has become a relevant topic for the industry because of its impact in making decision process. Gender recognition in Twitter is a business intelligence tool focused on twitter data acquisition, analysis, and process, and it can be used in many ways to transform it into valuable business intelligence data. In this paper, a method for gender recognition in Twitter users is proposed. This method employs several features related to user profile picture, screen name and profile description. This method was evaluated in a dataset with 574 users acquired from Twitter API, these users are located in Aguascalientes City at Mexico and they were manually labelled. The experimental results show an accuracy of 89.5%

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页数：6

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