Header menu link for other important links
Twitter Sentiment Analysis Using Elasticsearch, LOGSTASH and KIBANA
Published in Institute of Electrical and Electronics Engineers Inc.
In the era of technology, where for almost everything we are dependent on the internet, has been successful enough to dominate our social lives too. So, with excess usage of internet, creating huge log files containing hidden valuable information in it. Hence efforts have been made to overcome the shortcomings of log management and perform effective search to extract the real crux from pool of data which is needed for analysis. Further we require an efficient graphical visualizer which can completely express any shape of data. This paper demonstrates the working of open source tools i.e. elasticsearch, logstash, and kibana which has been clubbed together to have complete insight and visualization of data. Elastic search is used for searching and indexing, Logstash for slicing and dicing the raw data, maintaining and managing events whereas kibana is a graphical front end for data held in elasticsearch. By implementing these tools we are performing sentiment analysis of data taken from social networking blogging service like twitter. © 2020 IEEE.