TwitterSA

Sentimental analysis integrated with twitter api • This project was made on Python using twitter API.
• I split this project into 2 parts to start off, sentimental analysis and twitter api integration.
• The sentimental analysis used cambridge dictionary terms for both positive and negative wording.
• It would then hypothetically go through a tweet or a passage of text and determine if the overall sentiment was positive or negative.
• Once I had suceeded in doing this task and tested it on as many edge cases as I could find online with a pass rate of 85% I started on integrating twitter api.
• I soon found out that it is infact quite a lengthy process to get developer permissions and had to wait about a month and various reasioning forms to get granted all the permissions I required for this project.
• In the end I successfully applied this to twitter api and could apply sentimental analysis to hashtags.
• Applications of this project could be in the product launches or overall company sentiment to determine if a business or product has a happy consumer base.
• I started off this project thinking that it would be an easy task, but I steadily found out how complex english wording actually was and had to determine which words often would flip the meaning of a sentence. I am very happy with the result I achieved.