Title :
DOM: A big data analytics framework for mining Thai public opinions
Author :
Prom-on, Santitham ; Ranong, Sirapop Na ; Jenviriyakul, Patcharaporn ; Wongkaew, Thepparit ; Saetiew, Nareerat ; Achalakul, Tiranee
Author_Institution :
Dept. of Comput. Eng., King Mongkut´s Univ. of Technol. Thonburi, Bangkok, Thailand
Abstract :
This paper presents the development of DOM, a mobile big data analytics engine for mining Thai public opinions. The engine takes in data from multiple well-known social network sources, and then processes them using MapReduce, a keyword-based sentiment analysis technique, and an influencer analysis algorithm to determine public opinions and sentiments of certain topics. The system was evaluated its sentiment prediction accuracy by matching the predicted result with the human sentiment and tested on various case studies. The effectiveness of the approach demonstrates the practical applications of the engine.
Keywords :
Big Data; data mining; mobile computing; natural language processing; parallel processing; social networking (online); Big Data analytics framework; DOM; MapReduce; Thai public opinion mining; influencer analysis algorithm; keyword-based sentiment analysis technique; mobile Big Data analytics engine; sentiment prediction accuracy; social network sources; Accuracy; Big data; Data mining; Engines; Facebook; Twitter; MapReduce; big data analytics; opinion mining; public sentiment;
Conference_Titel :
Computer, Control, Informatics and Its Applications (IC3INA), 2014 International Conference on
Conference_Location :
Bandung
Print_ISBN :
978-1-4799-4577-1
DOI :
10.1109/IC3INA.2014.7042591