International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 183 - Number 28 |
Year of Publication: 2021 |
Authors: Farha Naaz, Rajesh Boghey, Sandeep Rai |
10.5120/ijca2021921665 |
Farha Naaz, Rajesh Boghey, Sandeep Rai . Location Wise Opinion Mining of Real-Time Twitter Data using Hadoop. International Journal of Computer Applications. 183, 28 ( Sep 2021), 24-30. DOI=10.5120/ijca2021921665
Opinion Mining is the process of detecting the contextual polarity of text. In other words, it reflects a piece of writing that is positive, negative, or neutral. The opinions of others seem to be crucial in decision making. Compressing out the usable content from these opinion sources becomes a perplexing task. Today social networking data is the best and accurate source for gathering public opinions. A large volume of data is generated everyday online which is not easy to handle and processed by traditional methods. In this research, a methodology is discussed which allows interpretation of real-time Twitter data in opinion mining. We take Twitter data because on Twitter huge opinions are shared. The analysis was done on tweets about iphone8. For this, we can fetch real-time Twitter data by using flume and storingit in HDFS. Hadoop is a best open-source solution for storing and processing a large amount of data. Hadoop has two separate components HDFS for storage and MapReduce for processing. We can integrate Apache Pig with Flume for analyzing the sentiment on the basis of location because opinions are changing from location to location. Apache Pig is used for analysis as it is best suited for both structured and unstructured data.