Business Improvement Approach Based on Sentiment Twitter Analysis: Case Study

Noori, Mohebollah and Maktoubian, Jamal (2019) Business Improvement Approach Based on Sentiment Twitter Analysis: Case Study. EAI Endorsed Transactions on Cloud Systems, 5 (14): e3. ISSN 2410-6895

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Abstract

Recently, everyday large amount of data continuously is generating from different sources such as social medias, social networks, Internet of things (IoT) devices, online games, healthcare data, and etc. This provide various challenges and opportunities for different businesses and sectors. Apart from challenges, shortage of storages and processing facilities, lack of management platforms to handle such a great volume of data, security and privacy issues, and to name but a few. On the other hand, analysing these data which is called “Big Data” could provide new insight into better understanding the hidden patterns. Big Data technologies and tools would be the appropriate solution to provide data scalability, availability and solve the problem of variety, volume and velocity (3Vs) of data. Twitter is a microblogging website which has been popular amount people to share their thought and idea between other users. Analysing such a valuable data, we are able to find out people’s opinion about particular issue. Mining customer opinions from their tweets could help to find strengths and weaknesses about a company’s products and services, features, and businesses. There are a number of studies in the respect of twitter sentiment analysis and opinion mining. However, the number of tweets have been used were small, and in term of using such a data in practice, the research are rare. In this paper, we first briefly demonstrate the reason why big data technologies need to be adopted, and then by giving an example, we presented different steps require to collect, store, process and analyse twitter data in large scale using different big data platforms and software.

Item Type: Article
Uncontrolled Keywords: Sentiment Analysis, Twitter, Big Data Analytics, Opinion mining, Business improvement
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
QA75 Electronic computers. Computer science
Depositing User: EAI Editor II.
Date Deposited: 10 Sep 2020 12:36
Last Modified: 10 Sep 2020 12:36
URI: https://eprints.eudl.eu/id/eprint/173

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