AI Twitter Sentiment Analysis API

25 Nov,2019
User Guide Document


Understand the social sentiment of your marketing campaign on Twitter automatically!

Use AI for sentiment analysis to keep track of how your clients are perceiving your website or brand and SNS marketing campaigns without hiring a Data Analysis expert. Save money and make your systems smarter.  Don't have a Python system? No problem, just host this API and use call it from your preferred programming language as a RestFul API. 

Sentiment analysis is an AI process from Natural Language processing aiming to identify positive, negative and neutral options from a text. It is a machine learning method of classification where the output is the polarity of the text which will allow us to classify it as positive, negative or neutral. 

This product is an API that will analyze the text from a line of text or tweet, searching by hashtag or username within a range of dates retiring a Json response containing the polarity, classification of the sentiment (positive, negative, neural) and the subjectivity. Additional functionality for getting Tweets by Username without a Twitter Developer Account*.  You can repurpose it to analyze other sources of texts by editing the code. 

With the following project you will be able to: 

  • Extract tweets using your Twitter account credentials by date
  • Extract tweets by hashtags or usernames 
  • Analyze the sentiment (positive, negative, neutral) of several tweets 
  • Analyze the subjectivity of the text 

External sources:  textblob 

Add in the comments some features you might be interested in so I might release an update.

Please note: ML  is not 100% accurate and the quality of the text plays a role as well. Please read the documentation first.  The language for Natural Language processing is English. *This functionality depends on the current UI implementation of Twitter. Please notice that change from the UI of Twitter may or may not remove this function. This was tested on November 25th 2019. 

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