The assignment describes Neuro-linguistic programming (NLP). Besides, there is an Analysis of Airline Sentiment Social Media. So, identify appropriate data sets for sentiment analysis.
Neuro-linguistic programming (NLP) – Airline Sentiment Social Media Analysis
The aim of this is to conduct sentiment analysis on airline social media.
Firstly, to conduct an appropriate critical analysis on literature belonging to sentiment analysis, data analytics and data mining. Secondly, to use data surveying methods. Thirdly, to identify appropriate data sets for sentiment analysis. Also, pre-process clean and format data files ready for sentiment analysis.
- Perform sentiment analysis on selected data.
- Evaluate the results.
Neuro-linguistic programming (NLP) – Airline Sentiment Social Media Analysis
Social media (e.g., Twitter, Facebook) is becoming a valuable source of timely information on the internet. It attracts a growing number of people, sharing, communicating, connecting, and creating user-generated data. However, information is not knowledge. How to discover knowledge from such a large amount of social media data becomes utterly essential. With such a large number of tweets from the customers who comment on their airline experience, the companies would like to find out how the customers rate their service.
Neuro-linguistic programming (NLP) – Airline Sentiment Social Media Analysis
In this project, the sentiment analysis will be performed on Twitter data, discovering the opinions/views underlying in tweets. Neuro-linguistic programming (NLP) techniques and various classification algorithms in machine learning will be explored, compared, and analysed for this task.
Airlines are one of the fastest means of transport in the world, which brings about direct linkage to international boundaries. This mode of transport helps people from various countries in the world to travel to other places for different reasons e.g., medical, personal, as well as tourism activities. Another aspect of air transport is the passengers’ level of comfort and facilities even though it is the fastest means of transport by saving time.
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