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Information Technology - Describing and Classifying Tweets Case Study - Report Writing Assessment Answer
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Describing and Classifying Tweets Case Study Assessment Answer
Assignment Task: Case: Describing and Classifying Tweets Many companies monitor social media posts in order to gauge how customers feel about their company and their competitors. For this question, imagine that you have been hired as a consultant by one of the major American airline companies to analyze tweets about airlines. They want to find out how people talk about airlines on Twitter and then build a predictive tool that can classify tweets in future into ‘negative’ or ‘positive’ sentiment toward airlines, to help them respond better to their customers in real time. They have provided you with a dataset of 11,541 tweets about airlines that have been labeled as ‘negative’ or ‘positive’ by their staff. The dataset also identifies which airline each tweet is talking about. Your task is to prepare a brief report that describes the tweets and recommends a classification method for future tweets. You need to:- Use appropriate tools to describe the tweets. In particular, what words are associated with negative or positive sentiment? How does word usage differ across different airlines?
- Use your analysis from (1) to build a short dictionary of negative and positive words describing airlines, then use it to classify tweets as ‘negative’ if they contain more negative than positive language, and ‘positive’ otherwise [code for creating your own dictionary is provided below]
- Use an appropriate supervised machine-learning method to classify the tweets into ‘negative’ and ‘positive’
- Compare the performance of your classifiers from (2) and (3), and use this analysis to decide which one would be the better classifier for the company to use for future tweets
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