Open AccessAn Overview on the Use of Data Mining and Linguistics Techniques for Building Microblog-Based Early Detection Systems in the Healthcare Sector
Author(s) -
Haider M. Habeeb,
Nabeel H. Al-A’araji
Publication year - 2015
Publication title -
international journal of computer science and information technology/international journal of computer science and information technology (chennai. print)
Language(s) - English
Resource type - Journals
eISSN - 0975-4660
pISSN - 0975-3826
DOI - 10.5121/ijcsit.2015.7511
Subject(s) - computer science , microblogging , social media , data science , health care , world wide web , economics , economic growth
The usage of Online Social Networks (OSN), such as Facebook and Twitter are becoming more and more\udpopular in order to exchange and disseminate news and information in real-time. Twitter in particular\udallows the instant dissemination of short messages in the form of microblogs to followers. This Survey\udreviews literature to explore and examine the usage of how OSNs, such as the microblogging tool Twitter,\udcan help in the detection of spreading epidemics. The paper highlights significant challenges in the field of\udNatural Language Processing (NLP) when using microblog based Early Disease Detection Systems. For\udinstance, microblogging data is an unstructured collection of short messages (140 characters in Twitter),\udwith noise and non-standard use of the English language. Hence, research is currently exploring the field\udof linguistics in order to determine the semantics of the text and uses data mining techniques in order to\udextract useful information for disease spread detection. Furthermore, the survey discusses applications and\udexisting early disease detection systems based on OSNs and outlines directions for future research on\udimproving such systems based on a combination of linguistics methods, data mining techniques and\udrecommendation systems