research-article

Interest classification of Twitter users using Wikipedia

Authors:

Kwan Hui Lim,

Amitava DattaAuthors Info & Claims

WikiSym '13: Proceedings of the 9th International Symposium on Open Collaboration

Article No.: 22, Pages 1 - 2

https://doi.org/10.1145/2491055.2491078

Published: 05 August 2013 Publication History

Get Access

Abstract

We present a framework for (automatically) classifying the relative interests of Twitter users using information from Wikipedia. Our proposed framework first uses Wikipedia to automatically classify a user's celebrity followings into various interest categories, followed by determining the relative interests of the user with a weighting compared to his/her other interests. Our preliminary evaluation on Twitter shows that this framework is able to correctly classify users' interests and that these users frequently converse about topics that reflect both their (detected) interest and a related real-life event.

References

[1]

K. H. Lim and A. Datta. Finding Twitter communities with common interests using following links of celebrities. In Proceedings of the 3rd International Workshop on Modeling Social Media, pages 25--32, Jun 2012.

Digital Library

Google Scholar

[2]

K. H. Lim and A. Datta. Tweets beget propinquity: Detecting highly interactive communities on twitter using tweeting links. In Proceedings of the 2012 IEEE/WIC/ACM International Conference on Web Intelligence, pages 214--221, Dec 2012.

Digital Library

Google Scholar

[3]

M. Michelson and S. A. Macskassy. Discovering users' topics of interest on twitter: A first look. In Proceedings of the 4th Workshop on Analytics for Noisy Unstructured Text Data, pages 73--80, Oct 2010.

Digital Library

Google Scholar

[4]

P. Siehndel and R. Kawase. Twikime! - User profiles that make sense. In Proceedings of the 11th International Semantic Web Conference (Posters and Demos), Nov 2012.

Google Scholar

Cited By

View all

Hoi NQue T(2024)Discovering User Interest in Social Media Based on CorrelationAdvances in Information and Communication Technology10.1007/978-3-031-50818-9_43(403-413)Online publication date: 4-Jan-2024
https://doi.org/10.1007/978-3-031-50818-9_43
Maekawa SSaeyor SSakaki TOnizuka M(2021)Effective Candidate Selection and Interpretable Interest Extraction for Follower Prediction on Social MediaIEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology10.1145/3486622.3493954(120-127)Online publication date: 14-Dec-2021
https://dl.acm.org/doi/10.1145/3486622.3493954
Hossen MAfrose TGhosh AAnwar M(2021)Classification of Social Media Users Based on Temporal Behaviors and InterestsCommunication and Intelligent Systems10.1007/978-981-16-1089-9_72(935-944)Online publication date: 29-Jun-2021
https://doi.org/10.1007/978-981-16-1089-9_72
Show More Cited By

Index Terms

Interest classification of Twitter users using Wikipedia
1. Applied computing
  1. Law, social and behavioral sciences

Recommendations

#Wikipedia on Twitter: analyzing tweets about Wikipedia
OpenSym '15: Proceedings of the 11th International Symposium on Open Collaboration

Wikipedia has long become a standard source of information on the web and as such is widely referenced on the web and in social media. This paper analyzes the usage of Wikipedia on Twitter by looking into languages used on both platforms, content ...
A sentiment analysis of audiences on twitter: who is the positive or negative audience of popular twitterers?
ICHIT'11: Proceedings of the 5th international conference on Convergence and hybrid information technology

Microblogging is a new informal communication medium of blogging that differs from a traditional blog in which content is much shorter. Microbloggers post about topics that describe their current status. Twitter is a popular microblogging service and ...
Disinformation Warfare: Understanding State-Sponsored Trolls on Twitter and Their Influence on the Web
WWW '19: Companion Proceedings of The 2019 World Wide Web Conference

Over the past couple of years, anecdotal evidence has emerged linking coordinated campaigns by state-sponsored actors with efforts to manipulate public opinion on the Web, often around major political events, through dedicated accounts, or “trolls.” ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

WikiSym '13: Proceedings of the 9th International Symposium on Open Collaboration

August 2013

248 pages

ISBN:9781450318525

DOI:10.1145/2491055

General Chairs:
Ademar Aguiar
Universidade do Porto
,
Dirk Riehle
Friedrich-Alexander University Erlangen-Nürnberg

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

In-Cooperation

SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 05 August 2013

Check for updates

Author Tags

Qualifiers

Research-article

Conference

WikiSym '13

Sponsor:

WikiSym '13: The 9th International Symposium on Wikis and Open Collaboration

August 5 - 7, 2013

Hong Kong, China

Acceptance Rates

WikiSym '13 Paper Acceptance Rate 22 of 43 submissions, 51%;

Overall Acceptance Rate 69 of 145 submissions, 48%

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

22
Total Citations
View Citations
346
Total Downloads

Downloads (Last 12 months)5
Downloads (Last 6 weeks)1

Reflects downloads up to 19 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Hoi NQue T(2024)Discovering User Interest in Social Media Based on CorrelationAdvances in Information and Communication Technology10.1007/978-3-031-50818-9_43(403-413)Online publication date: 4-Jan-2024
https://doi.org/10.1007/978-3-031-50818-9_43
Maekawa SSaeyor SSakaki TOnizuka M(2021)Effective Candidate Selection and Interpretable Interest Extraction for Follower Prediction on Social MediaIEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology10.1145/3486622.3493954(120-127)Online publication date: 14-Dec-2021
https://dl.acm.org/doi/10.1145/3486622.3493954
Hossen MAfrose TGhosh AAnwar M(2021)Classification of Social Media Users Based on Temporal Behaviors and InterestsCommunication and Intelligent Systems10.1007/978-981-16-1089-9_72(935-944)Online publication date: 29-Jun-2021
https://doi.org/10.1007/978-981-16-1089-9_72
AlSomaikhi NAlzamil Z(2020)Twitter Users' Classification Based on InterestInternational Journal of Information Retrieval Research10.4018/IJIRR.202001010110:1(1-12)Online publication date: 1-Jan-2020
https://doi.org/10.4018/IJIRR.2020010101
Tiwari SSaini APaliwal VSingh AGupta RMattoo R(2020)Implicit Preferences Discovery for Biography Recommender System Using TwitterProcedia Computer Science10.1016/j.procs.2020.03.352167(1411-1420)Online publication date: 2020
https://doi.org/10.1016/j.procs.2020.03.352
Safari RRahmani AAlizadeh S(2019)User behavior mining on social media: a systematic literature reviewMultimedia Tools and Applications10.1007/s11042-019-08046-678:23(33747-33804)Online publication date: 17-Aug-2019
https://doi.org/10.1007/s11042-019-08046-6
Piao GBreslin J(2018)Inferring user interests in microblogging social networksUser Modeling and User-Adapted Interaction10.1007/s11257-018-9207-828:3(277-329)Online publication date: 1-Aug-2018
https://dl.acm.org/doi/10.1007/s11257-018-9207-8
Zhu JMa SZhang HHu CLi X(2018)Incorporating User Grouping into Retweeting Behavior ModelingDatabase Systems for Advanced Applications10.1007/978-3-319-91452-7_31(474-490)Online publication date: 13-May-2018
https://doi.org/10.1007/978-3-319-91452-7_31
Kesorn KJuraphanthong WSalaiwarakul A(2017)Personalized Attraction Recommendation System for Tourists Through Check-In DataIEEE Access10.1109/ACCESS.2017.27782935(26703-26721)Online publication date: 2017
https://doi.org/10.1109/ACCESS.2017.2778293
Shahzad BLali INawaz MAslam WMustafa RMashkoor A(2017)Discovery and classification of user interests on social mediaInformation Discovery and Delivery10.1108/IDD-03-2017-002345:3(130-138)Online publication date: 21-Aug-2017
https://doi.org/10.1108/IDD-03-2017-0023
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

#Wikipedia on Twitter: analyzing tweets about Wikipedia

A sentiment analysis of audiences on twitter: who is the positive or negative audience of popular twitterers?

Disinformation Warfare: Understanding State-Sponsored Trolls on Twitter and Their Influence on the Web