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%
引用
收藏
页数：6
相关论文
共 50 条
  • [1] A Turkish Dataset for Gender Identification of Twitter Users
    Sezerer, Erhan
    Polatbilek, Ozan
    Tekir, Selma
    13TH LINGUISTIC ANNOTATION WORKSHOP (LAW XIII), 2019, : 203 - 207
  • [2] Creating Extended Gender Labelled Datasets of Twitter Users
    Vicente, Marco
    Batista, Fernando
    Carvalho, Joao Paulo
    INFORMATION PROCESSING AND MANAGEMENT OF UNCERTAINTY IN KNOWLEDGE-BASED SYSTEMS, IPMU 2016, PT II, 2016, 611 : 690 - 702
  • [3] Prediction of Personality Traits in Twitter Users with Latent Features
    Jaimes Moreno, Daniel Ricardo
    Gomez, Juan Carlos
    Almanza-Ojeda, Dora-Luz
    Ibarra-Manzano, Mario-Alberto
    2019 INTERNATIONAL CONFERENCE ON ELECTRONICS, COMMUNICATIONS AND COMPUTERS (CONIELECOMP), 2019, : 176 - 181
  • [4] Features combination for the detection of malicious Twitter accounts
    David, Isaac
    Siordia, Oscar S.
    Moctezuma, Daniela
    2016 IEEE INTERNATIONAL AUTUMN MEETING ON POWER, ELECTRONICS AND COMPUTING (ROPEC), 2016,
  • [5] Pattern Recognition of Twitter Users Using Semantic Topic Modelling
    Srinivasan, R.
    Senthilraja, M.
    Iniyan, S.
    2017 IEEE INTERNATIONAL CONFERENCE ON IOT AND ITS APPLICATIONS (IEEE ICIOT), 2017,
  • [6] Users Intention Based on Twitter Features Using Text Analytics
    Mishael, Qadri
    Ayesh, Aladdin
    Yevseyeva, Iryna
    INTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING - IDEAL 2019, PT I, 2019, 11871 : 121 - 128
  • [7] Twitter-based gender recognition using transformers
    Nia, Zahra Movahedi
    Ahmadi, Ali
    Mellado, Bruce
    Wu, Jianhong
    Orbinski, James
    Asgary, Ali
    Kong, Jude D.
    MATHEMATICAL BIOSCIENCES AND ENGINEERING, 2023, 20 (09) : 15962 - 15981
  • [8] Bots and Gender Detection on Twitter Using Stylistic Features
    Ouni, Sarra
    Fkih, Fethi
    Omri, Mohamed Nazih
    ADVANCES IN COMPUTATIONAL COLLECTIVE INTELLIGENCE, ICCCI 2022, 2022, 1653 : 650 - 660
  • [9] Facial Features for Gender Recognition
    Liao Guangjun
    Chen Wei
    Wu Yaoxin
    PROCEEDINGS OF THE 35TH CHINESE CONTROL CONFERENCE 2016, 2016, : 4161 - 4165
  • [10] Analyzing Features of Passive Twitter's Users to Estimate Passive Twitter-User's Interests
    Hayama, Tessai
    2021 IEEE/WIC/ACM INTERNATIONAL CONFERENCE ON WEB INTELLIGENCE AND INTELLIGENT AGENT TECHNOLOGY (WI-IAT 2021), 2021, : 476 - 481
12345