{"id":248930,"date":"2023-01-11T11:57:57","date_gmt":"2023-01-11T11:57:57","guid":{"rendered":"https:\/\/imarticus.org\/?p=248930"},"modified":"2023-01-11T12:01:33","modified_gmt":"2023-01-11T12:01:33","slug":"how-to-build-a-twitter-sentiment-analyser-using-natural-language-processing","status":"publish","type":"post","link":"https:\/\/imarticus.org\/blog\/how-to-build-a-twitter-sentiment-analyser-using-natural-language-processing\/","title":{"rendered":"How To Build a Twitter Sentiment Analyser Using Natural Language Processing"},"content":{"rendered":"

Natural language processing<\/b>\u00a0is the capability of the computer program to comprehend the human language, both verbally and manually and then use it for communication. Computer systems use linguistics, computer science and artificial intelligence for this complex operation. After understanding the context of the textual or verbal content, they can use it to infer, analyse, and make something of their own. In simpler terms, they are trying to understand and use language just like a human.\u00a0<\/span><\/p>\n

Building a Twitter sentiment analyser<\/b><\/h2>\n

NLP is a part of a\u00a0<\/span>machine learning course with placement<\/b><\/a>. You are trained to develop code for activities like these, where you will be building a Machine Learning model that will try to understand the sentiment behind a tweet. Using this Twitter sentiment analyser, you can try to understand which tweets have hate speech or objectionable speech in them. It could also be used to filter sexist and racist tweets as well. It is an activity that is related to supervised learning.<\/span><\/p>\n

For this activity, you would need the following:<\/strong><\/p>\n

    \n
  1. Coding knowledge of Python.<\/span><\/li>\n
  2. You will need to use various libraries of Python and natural language processing.\u00a0\u00a0<\/span><\/li>\n
  3. A dataset consisting of tweets. This dataset can be downloaded from the Twitter API.<\/span><\/li>\n
  4. Knowledge of three classifiers – logistic reasoning, Bernoulli Na\u00efve Bayes and Support Vector Machine (SVM)<\/span><\/li>\n<\/ol>\n

    Coming to the dataset will contain various fields like:<\/strong><\/p>\n