research-article

Identifying Audience Attributes: Predicting Age, Gender and Personality for Enhanced Article Writing

Authors:

Raad Bin Tareaf,

Philipp Berger,

Patrick Hennig,

Christoph MeinelAuthors Info & Claims

ICCBDC '17: Proceedings of the 2017 International Conference on Cloud and Big Data Computing

Pages 79 - 88

https://doi.org/10.1145/3141128.3141129

Published: 17 September 2017 Publication History

Abstract

In order to create an effective article, having great content is essential. However, to achieve this, the writer needs to target a specific audience. A target audience refers to a group of readers that a writer intends to reach with his content. Defining a target audience is substantial because it has a direct effect on adjusting writing style and content of the article. Nowadays, writers rely solely on annotated attributes of articles, such as location and language to understand his/her audience.

The aim of this work is to identify the audience attributes of articles, especially not-annotated attributes. Among others, this work focuses on the detection of three key audience attributes of related articles: age, gender, and personality.We compare between multiple machine learning classifiers to detect these attributes. Finally, we demonstrate a prototypical application that enables writers to run existing algorithms such as trend detection and showing related articles that are specific to a defined target audience based on the newly detected attributes.

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Cited By

Shafiloo RKaedi MPourmiri A(2024)Predicting user demographics based on interest analysis in movie datasetMultimedia Tools and Applications10.1007/s11042-024-18422-683:27(69973-69987)Online publication date: 3-Feb-2024
https://doi.org/10.1007/s11042-024-18422-6
Bhagat HSingh M(2022)Machine‐Learning and Deep‐Learning Techniques in Social SciencesMachine Learning Algorithms for Signal and Image Processing10.1002/9781119861850.ch23(409-428)Online publication date: 18-Nov-2022
https://doi.org/10.1002/9781119861850.ch23
Panhalkar ADoye D(2021)A novel approach to build accurate and diverse decision tree forestEvolutionary Intelligence10.1007/s12065-020-00519-015:1(439-453)Online publication date: 3-Jan-2021
https://doi.org/10.1007/s12065-020-00519-0
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Index Terms

Identifying Audience Attributes: Predicting Age, Gender and Personality for Enhanced Article Writing
1. Information systems
  1. Information systems applications
    1. Collaborative and social computing systems and tools
      1. Blogs

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cover image ACM Other conferences

ICCBDC '17: Proceedings of the 2017 International Conference on Cloud and Big Data Computing

September 2017

135 pages

ISBN:9781450353434

DOI:10.1145/3141128

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Northumbria University: University of Northumbria at Newcastle

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 September 2017

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ICCBDC 2017

ICCBDC 2017: 2017 International Conference on Cloud and Big Data Computing

September 17 - 19, 2017

London, United Kingdom

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Cited By

Shafiloo RKaedi MPourmiri A(2024)Predicting user demographics based on interest analysis in movie datasetMultimedia Tools and Applications10.1007/s11042-024-18422-683:27(69973-69987)Online publication date: 3-Feb-2024
https://doi.org/10.1007/s11042-024-18422-6
Bhagat HSingh M(2022)Machine‐Learning and Deep‐Learning Techniques in Social SciencesMachine Learning Algorithms for Signal and Image Processing10.1002/9781119861850.ch23(409-428)Online publication date: 18-Nov-2022
https://doi.org/10.1002/9781119861850.ch23
Panhalkar ADoye D(2021)A novel approach to build accurate and diverse decision tree forestEvolutionary Intelligence10.1007/s12065-020-00519-015:1(439-453)Online publication date: 3-Jan-2021
https://doi.org/10.1007/s12065-020-00519-0
Bin Tareaf RBerger PHennig PMeinel C(2020)Cross-platform personality exploration system for online social networks: Facebook vs. TwitterWeb Intelligence10.3233/WEB-20042718:1(35-51)Online publication date: 9-Mar-2020
https://doi.org/10.3233/WEB-200427
Tareaf RAlhosseini SMeinel C(2020)Does Personality Evolve? A Ten-Years Longitudinal Study from Social Media Platforms2020 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom)10.1109/ISPA-BDCloud-SocialCom-SustainCom51426.2020.00179(1205-1213)Online publication date: Dec-2020
https://doi.org/10.1109/ISPA-BDCloud-SocialCom-SustainCom51426.2020.00179
Choi JLim K(2020)Identifying machine learning techniques for classification of target advertisingICT Express10.1016/j.icte.2020.04.0126:3(175-180)Online publication date: Sep-2020
https://doi.org/10.1016/j.icte.2020.04.012
Bin Tareaf RAlhosseini SMeinel C(2019)Facial-Based Personality Prediction Models for Estimating Individuals Private Traits2019 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom)10.1109/ISPA-BDCloud-SustainCom-SocialCom48970.2019.00233(1586-1594)Online publication date: Dec-2019
https://doi.org/10.1109/ISPA-BDCloud-SustainCom-SocialCom48970.2019.00233
Tareaf RAlhosseini SBerger PHennig PMeinel C(2019)Towards Automatic Personality Prediction Using Facebook Likes Metadata2019 IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)10.1109/ISKE47853.2019.9170375(714-719)Online publication date: Nov-2019
https://doi.org/10.1109/ISKE47853.2019.9170375
Wang ZGuo YLi ZTang MQi TWang J(2019)Research on Microblog Rumor Events Detection via Dynamic Time Series Based GRU ModelICC 2019 - 2019 IEEE International Conference on Communications (ICC)10.1109/ICC.2019.8761457(1-6)Online publication date: May-2019
https://doi.org/10.1109/ICC.2019.8761457
Wang JZhang HFang BWang XYin GYu X(2019)EDCleaner: Data Cleaning for Entity Information in Social NetworkICC 2019 - 2019 IEEE International Conference on Communications (ICC)10.1109/ICC.2019.8761127(1-7)Online publication date: May-2019
https://doi.org/10.1109/ICC.2019.8761127
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