Review on event detection techniques in social multimedia. Issue 3 (13th June 2016)

• Record Type: Journal Article
• Authors: Garg, Muskan; Kumar, Mukesh
• Is Part Of: Online information review. Volume 40:Issue 3(2016)
• Page Start: 347
• Page End: 361
• Publication Date: 2016-06-13
• Subjects: Social media analysis -- Event detection and prediction -- Micro-blog latent pattern -- Twitter data stream; 025.04
• DOI: 10.1108/OIR-08-2015-0281
• Languages: English
• ISSNs: 1468-4527

Abstract

Abstract : Purpose: – Social Media is one of the largest platforms to voluntarily communicate thoughts. With increase in multimedia data on social networking websites, information about human behaviour is increasing. This user-generated data are present on the internet in different modalities including text, images, audio, video, gesture, etc. The purpose of this paper is to consider multiple variables for event detection and analysis including weather data, temporal data, geo-location data, traffic data, weekday's data, etc. Design/methodology/approach: – In this paper, evolution of different approaches have been studied and explored for multivariate event analysis of uncertain social media data. Findings: – Based on burst of outbreak information from social media including natural disasters, contagious disease spread, etc. can be controlled. This can be path breaking input for instant emergency management resources. This has received much attention from academic researchers and practitioners to study the latent patterns for event detection from social media signals. Originality/value: – This paper provides useful insights into existing methodologies and recommendations for future attempts in this area of research. An overview of architecture of event analysis and statistical approaches are used to determine the events in social media which need attention.