assignment need 20 ppt slides. data sets can be dowloaded from the link
https://drive.google.com/drive/folders/1wOCa2i1czYEk4LW-u7qNi4nFVUlUJE8H?usp=sharing
Data Analytics Assignment: Text analytics for AirBnB You have recently got a fantastic job opportunity to be part of AirBnB data analytics team. As a key member of the team, you’ll be responsible for building the AirBnB brand and getting, keeping, and developing customers by creating social media contents. You’re using your expertise in social media. This includes everything from understanding the voice of customers and creating contents relevant for the company brand to promote in the digital space and create better customer experience. At the moment, your team and direct manager do not expect a lot from you. However, you’re quite ambitious to actively engage and contribute to the team within the limited budget. One day, you remembered the text analytics lecture from the IMC. As a starting point, you are going to apply the text analytics technique using Python. The company has never used such a systemic approach to understanding the voice of customers. Now, you are about to apply text analytics and theme classification. Further, you want to upgrade the analysis technique by learning more from the internet. The success of this project is how much C-level managers can be impressed and persuaded. Most of all, exciting story-telling using unique text analytics is the key. The C- level managers have the interest to promote better customer outcomes such as getting, keeping, and developing relationships with customers, and creating better customer experiences. The key is that your analysis and proposal must provide clear recommendations to help managers achieve these outcomes. Also, excellent written and visual communication is essential. Finally, be creative and insightful! Enjoy your project! To do list 1. Apply sentiment analysis and train a classification model to predict polarity of reviews. 2. Find the most frequent words, show word cloud and visualize the frequent words in positive and negative reviews separately. 3. Apply sentiment analysis and train a classification model to predict polarity of reviews. 4. Apply topic modelling and present the list of topics. 5. Discuss the importance of each topic based on the counts and proportions of the topic out of the entire dataset. In other words, how much does each topic cover the comments from the dataset? 6. What are the most important issues, opportunities, or insights for the given data? What are your recommendations to achieve better customer outcomes? List the recommendations in order of importance. 7. Provide results in PPT slides and focus on storytelling and visualization. Leaving a good impression using the PPT slide is important to appeal your idea within a given short time. Make an interesting and impactful visualization on your slide, also extract interesting key findings using various analyses. 8. Submit/Upload both PPT slides and Python-files. Evaluation criteria 1. Impressive, interesting, and informative visualization on PPT slides. (30%) 2. Text analytics capability, depth of analysis & upgraded text analytics technique. (30%) 3. The quality of recommendations (How interesting/unique/actionable/logical/ persuasive are the recommendations?) (30%) 4. Outstanding overall quality of the report compared to other students. (10%) Format • Please use power point (PPT) format (not MS words), because many business managers prefer to use the PPT to share/communicate ideas. • Font and size: choose based on your preference. • Word counts: no limits (please balance between visualization and written information). • No animated slides and no video clips. • PPT page limit: Up to 20 pages including everything. Please note that you’re going to report to the C-level management team and they won’t read long pages. • First page contains the Company’s brand name and your name. • Second page contains executive summary page, which includes key findings and recommendations.