take decisions in order to minimize reprodubcibility issues with Twitter data and to comply with the policies.

apply a selection of pre-processing steps to these tweets.

crawl tweets using customized queries based on the R package academictwitteR (Barrie and Ho 2021).

complete the academic research track application process for the Twitter API.

In this Methods Bites Tutorial, Andreas Küpfer (Technical University of Darmstadt & MZES) presents a walkthrough of the collection, management, and analysis of Twitter data.Īfter reading this blog post and engaging with the applied exercises, readers will be able to: As of 01/2021, Twitter renewed its API, which now includes access to the full history of tweets for academic usage. The developed tool 1.5 times faster than that of traditional database to Hadoop cluster and also the accuracy is nearly 80 %, which helps the user in computing, analyzing and interpreting interaction and associations between people, topics and ideas.As a highly relevant platform for political and social online interactions, researchers increasingly analyze Twitter data. The result shows that applied sentimental analysis with unsupervised clustering of data into specific domains and supervised machine learning techniques handle large amounts of twitter data in an efficient way.

The methodology devised an algorithm based on sentimental analysis using customers review classification, which dealt with prepossessing the datasets, clustering of the data based on the specific domains, feature vector using n-gram models and tf-idf vectors extracts synonyms and classification sentiment analysis.

The objective of the research work was to develop big data technology used for gathering and handling large unstructured data from real time social media for sentiment analysis for identifying the brand and services.

Social media analytics gathering structure and unstructured Big-Data from various social sites and analyzing to make business decisions using Apache Hadoop and Apache Hive respectively. In social media, micro-blogging is a common routine of most people around the world.

Tools for data analysis for tweets