Project : Sentiment Data Analytics
We completed this project in 4 steps.
Step 1 : We collected data. In our project, we worked on data from a Squide game that you will find in our branches. Don't forget to fill in the data in python file.
Step 2 : is the data exploration and preprocessing stage. We conducted a study on the data, did some visualization, cleaned the data, specifically the tweet columns. We removed mentions, emojis, URLs, hashtags, special characters, converted phrases to lowercase, etc.
Step 3 : involved translating the language of the tweets into English. This was done according to our discretion. involved using the 'translate' library in Googletrans.
Step 4 focused on sentiment analysis. In this part, we needed to understand users' opinions on the Squid Game movie. We used the TextBlob model to classify tweets as neutral, negative, or positive.
Step 5 involved visualization in Power BI. I visualized the data using various graphs