Concept Drift Detection for Social Media: A Survey

Title

Concept Drift Detection for Social Media: A Survey

Creator

Patil M.A.; Kumar S.; Kumar S.; Garg M.

Description

The research over information retrieval from social media data has progressed for streaming data since the last decade. Recently, academic researchers have witnessed users' changing topics, trends, and intent on social media. This change of information with time takes into account the temporal attribute for real-time data, and thus, advances in this domain are exponentially growing. Although concept drift is still not explored due to a shortage of available datasets, concept drift for social media is minimally explored. This manuscript makes attempts to identify the types of concept drift for social media data, discuss the historical perspective of concept drift on social media, and enlist the possible research directions. 2021 IEEE.

Source

Proceedings - 2021 3rd International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2021, pp. 12-16.

Date

2021-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

real-time data; streaming data; temporal data; Twitter

Coverage

Patil M.A., Amity University Rajasthan, Amity School of Engineering Technology, Jaipur, India; Kumar S., Amity University Rajasthan, Amity School of Engineering Technology, Jaipur, India; Kumar S., CHRIST (Deemed to Be University), Karnataka, Bangalore, 560029, India; Garg M., Amity University Rajasthan, Amity School of Engineering Technology, Jaipur, India

Rights

Restricted Access

Relation

ISBN: 978-166543811-7

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/ICAC3N53548.2021.9725548

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126983671&doi=10.1109%2fICAC3N53548.2021.9725548&partnerID=40&md5=a6790049bf2d2a26a22e0caba697de7c