Social Media Sentiment Analysis - Twitter - MOHAMED SHAHID, AFIQA (Universiti Teknologi PETRONAS, 2020)
This project gives a method for sentiment analysis specifically aimed to work with Twitter data (tweets), to consider their length, structure and specific language. The method employed makes it able to process tweets in near real time. A large amount of online data, rich web resources are highly unstructured plus such natural language are not resolvable via machine straightforwardly. The increased demand to capture opinions of the public concerning sales of a product has led to study of the field sentiment analysis and opinion mining. Opinion refers to the extraction of lines in raw data which expresses an opinion. Sentiment analysis classifies polarity of extracted sentiments into positive, negative and neutral. This type of analysis commonly applies to analyze the service or product reviews, voice of the purchaser, survey responses from social media feeds and online to analyze the attitude of the client. A dashboard has been created to know the opinion regarding sales of the product whether it has more positive, negative or neutral number. This project will help the product owner to know opinion and thoughts of the social media user about their product.