Sentiment Analysis using Big Data (CASE STUDY: Peoples Opinions on Facebook About Governor’s Ortom Handling of the Farmer/Herder Crisis in Benue State)
Sentiment Analysis is the process of determining whether a piece of writing is positive, negative or neutral. A sentiment analysis system for text analysis combines natural language processing (NLP) and machine learning techniques to assign weighted sentiment scores to the entities, topics, themes and categories within a sentence or phrase.
Big Data refers to extremely large data sets that may be analysed computationally to reveal patterns, trends, and associations, especially relating to human behaviour and interactions.
The goal of this research will to analyse the views shared by individuals concerning the handling of the farmers/herders crisis in Benue State by the state Governor.
Facebook: The dataset will be composed of facebook posts made relating to the farmes/herders crisis
from different individuals from May 30, 2016 till date, after Governor Samuel Ortom assumed office as the Governor of Benue State.
In the era of the Internet, social media has become an integral part of modern society. People use social media to share their opinions and to have an up-to-date knowledge about the current trends on a daily basis. Facebook is one of the renowned social media that gets a huge amount of posts each day. This information can be used for economic, industrial, social or government approaches by arranging and analyzing the pots as per our demand. Since Facebook contains a huge volumeof data, storing and processing this data is a complex problem. Hadoop is a big data storage and processing tool for analyzing data with 3Vs, i.e. data with huge volume, variety and velocity. Hadoop is a framework which deals with Big data and it has its own family which supports processing of different things which are tied up in one umbrella called the Hadoop Ecosystem