helpfn

+, − or Neutral: Sentiment Analysis of Tweets on Twitter∗

Nifty Assignment

Robert Lutz and Evelyn Brannock Georgia Gwinnett College

1000 University Center Lane Lawrenceville, Ga 30043 {rlutz,ebrannoc}@ggc.edu

1 Introduction

Sentiment Analysis is a popular application of Natural Language Processing (NLP). This exercise offers the capability to perform opinion mining in the political arena by feeding data into a cloud natural language processor, without in-depth proficiency in machine learning (ML) algorithms. It is an engaging mechanism for interesting students in using ML to extract information from voluminous amounts of text found in Twitter to understand the structure and meaning of text.

∗Copyright is held by the author/owner.

133

2 Materials

• Educational codes for access to Google Cloud Platform (GCP) • Credentials to access API • Jupyter Notebook

3 Summary

Students are asked to provide an app that provides results of a sentiment analy- sis of tweets on some current “hot” political subject, such as the Mueller report or tweets from President Trump as shown below.

Step 1: Load required libraries by running the install commands.

Step 2: Provide credentials to access APIs.

134

Step 3: Establish calling endpoint, call parameters and make the request.

Step 4: Coerce the response into a list of messages.

Step 5: Create a (reusable) function for sentiment analysis using Google’s Natural Language Processing.

135

4 Metadata

136