Open AccessChallenges of event detection from social media streams
Author(s) -
Wafa Zubair Al-Dyani,
Adnan Hussein,
Farzana Kabir Ahmad
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.15.11217
Subject(s) - social media , computer science , event (particle physics) , task (project management) , data science , process (computing) , big data , internet privacy , data collection , world wide web , sociology , data mining , engineering , systems engineering , quantum mechanics , physics , operating system , social science
The area of Event Detection (ED) has attracted researchers' attention over the last few years because of the wide use of social media. Many studies have examined the problem of ED in various social media platforms, like Twitter, Facebook, YouTube, etc. The ED task for social networks involves many issues, including the processing of huge volumes of data with a high level of noise, data collection and privacy issues, etc. Hence, this article discusses and presents the wide range of challenges encountered in the ED process from unstructured text data for the most popular Social Networks (SNs), such as Facebook and Twitter. The main goal is to aid the researchers to understand the main challenges and to discuss the future directions in the ED area.