Abstract
Twitter monitoring enables firms to consider their market, stay on track of what is being said regarding their company and contenders, and uncover emerging market trends. Twego Trending is a platform where data will be viewed and structured by an automated procedure of analyzing and processing tweets data and classifying it into various hash statistics and visualizations. Implementing Twego forecasting analysis on Twitter data using various technologies may help businesses know how consumers talk about their product. Twitter has more than 340 million active users and almost 500 millions tweets are posted every day. This social media platform helps companies to reach a large audience and communicate without intermediaries with consumers. The aim is to build a Search Engine in which , when someone will type in a query , it will return back tweets as well as do data analytics on the results and provide visualizations.
Highlights
IntroductionMood, or perception and Opinion mining is studying people’s sentiments
Opinion is an emotion, mood, or perception and Opinion mining is studying people’s sentiments
Internet is an ingenious place in regards to sentiment data
Summary
Mood, or perception and Opinion mining is studying people’s sentiments. Data from Twitter is special than data shared by most other social networks because it represents data that people want to share publicly In this Proposed System, A highly scalable Data Analytics Based Search Engine will be designed for Twitter’s trending Data Sets. Elasticsearch is an open source search engine which works with all kinds of data. Elasticsearch is the prime integrant of the ELK (Elastic Stack), a collection of softwares for data analysis, storing and visualization. It is regarded as one of the best search engines able to deal with structured and unstructured data (Bhatnagar, Suba Lakshmi & Vanmathi C, 2020). It’s an opensource product; it’s always been supported and developed by programmers and engineers
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