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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