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Bringing order to episodes: Mining timeline in social media.

Authors :
Wang, Shang
Yang, Zhiwei
Chang, Yi
Source :
Neurocomputing. Aug2021, Vol. 450, p80-90. 11p.
Publication Year :
2021

Abstract

Social media is growing at an explosive rate and it becomes increasingly difficult for users to locate useful information from massive and high-velocity social media data. Recently a few social media sites have employed timelines to organize historical data of entities, which greatly improve user experiences in rediscovering important timeline episodes and understanding their order and trends. However, timelines of entities are not explicitly available in most social media sites. In other words, a gap exists between the importance of timelines and their availability in social media. In this paper, we investigate the problem of mining timelines of entities in social media. We delineate its challenges and opportunities, and propose a principled framework Timeliner, which can automatically generate timelines for entities by exploiting their historical social media data. We conduct experiments on real-world datasets, and the experimental results demonstrate that Timeliner can accurately mine timelines of entities in social media. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09252312
Volume :
450
Database :
Academic Search Index
Journal :
Neurocomputing
Publication Type :
Academic Journal
Accession number :
150696789
Full Text :
https://doi.org/10.1016/j.neucom.2021.04.020