Social Media Intelligence for Brand Analysis
Parth Nagarkar, Lavin Amarnani, Dharmik Doshi · 2021
With the rise of social media users, the amount of data being generated every day from the social media websites is increasing. Social media web sites like Instagram, Twitter, Snapchat, etc. are allowing the users to express their opinions on any subject and share their opinion with people sitting in any corner of the world. Numerous posts are also posted about various brands belonging to multiple domains like technology, sports, fashion, etc. These posts, when analysed, can provide valuable insights about the social media users' opinion and prove to be an untapped gold mine for the brands. These insights can in turn help the brands to make better business decisions based on the insights that are extracted from the posts. This paper aims to provide a real-time solution to stream the tweets from Twitter related to a specific brand and analyse them in real-time in order to extract insights from the tweet data that allows the brands to know what exactly are the social media users' perceptions about them. This solution consists of multiple stages where scripts are deployed on servers and run around the clock to process the raw streamed tweet data using artificial intelligence techniques in order to extract location, sentiments, named entities, date and time to further categorise the information based on numerous factors mentioned in the paper and present the data in the form of charts displayed on a webpage which will enable the end user to gain insights and uncover hidden patterns from the data.