Open AccessReal Time Data Pipeline for Twitter Trends Analysis
Author(s) -
Rishabh Sharma Amritpal Singh Mukesh Kumar Sah.
Publication year - 2021
Publication title -
international journal of modern trends in science and technology
Language(s) - English
Resource type - Journals
ISSN - 2455-3778
DOI - 10.46501/ijmtst0705006
Subject(s) - social media , social media analytics , pipeline (software) , computer science , field (mathematics) , sentiment analysis , data science , product (mathematics) , analytics , world wide web , service (business) , business , marketing , artificial intelligence , geometry , mathematics , pure mathematics , programming language
In social media, Information is present in enormous amount. Extracting data from processed information fromsocial media gives us diverse usages in various fields. In the field of Business Analytics, HealthCare,Technologies and Trending Topics in Social Media posted by the user. Extracting information from socialmedia is providing number of benefits such as knowledge about the latest Technology, Medical field,Business Decisions, etc. Twitter is solitary of the social media which allows the user post tweets of limitednumber of characters and share the tweet to their followers. Twitter allows application developer to accessthe tweets for their motive. In the implemented methodology, Tweets are collected, and sentiment analysis isperformed on them. Based on the results of sentimental analysis of Trending Topics in Twitter, suggestionscan be provided to the user. In this way, the implemented system can help in improving the growth ofbusiness, healthcare, technologies and alsoNegative or Positive mentions of a product or service can bedetermined.