Chat with us, powered by LiveChat Research Paper Write a 5-page research paper (cover and reference page inclusive) on the topic ‘ The Impact of Data Mining in the Healthcare Sector.’Research Paper Requirements - Wridemy Essaydoers

Research Paper Write a 5-page research paper (cover and reference page inclusive) on the topic ‘ The Impact of Data Mining in the Healthcare Sector.’Research Paper Requirements

 

Research Paper

Write a 5-page research paper (cover and reference page inclusive) on the topic " The Impact of Data Mining in the Healthcare Sector."Research Paper Requirements:1. Five pages long. The cover page and reference page included.2. Use Times New Roman font, size 12 and double-spaced.3. Include a cover page and a reference page.4. Use section headers for good readership.5. Use figures and tables if needed (not mandatory).6. Use Safe-Assign to check your research paper. A similarity score greater than 30% shows poor originality.7. Use APA for in-text citations and references (in-text citations must match reference list)8. Provide at least three scholarly references.9. AVOID PLAGIARISM 

Topics :(pick any one to solve a problem)

  

•Sentiment Analysis

•Data Mining/Reports – Dashboard

•Machine Learning

•Neural Networks

•Genetic Algorithm

•Robo Advisors

•Natural Language Processing

Group XXX Residency Project

Team Members

John Max

Vincent Ray

Carl Max

Executive Summary

Airbnb is an online vacation rental company based in San Francisco, California. Customers can rent vacation houses across the United States. To become a host, you will need to register online and provide details about your property.

Problem Statement

Airbnb continues to see significant loss in revenue due to COVID-19 pandemic. Since February 2020, Airbnb has lost approximately 60% of its revenue and looking for ways to increase its sales and customer satisfaction/trust.

Definition of terms

Sentiment Analysis: The process of using text analysis, natural processing language, computational linguistics and biometric to deduce context to gauge public opinion, conduct market research, monitor brand or product reputation, and understand customer experience. (Sharda, Delen, & Turban, 2021)

MonkeyLearn: a sentiment analysis tool used to gain insight from unstructured data (MonkeyLearn, n.d.)

Twitter: “an American microblogging and social networking service on which users post and interact with messages known as "tweets". (Twitter, 2021)

Project Scope

This project will review Airbnb sales in all states in the United States beginning from January 2020 to December 2020 and corresponding Tweeter Feeds for each month. A sentiment analysis will be conducted on the Tweeter feed for each state and results from the sentiment analysis will be presented to executive management with recommendations.

Project Requirements

Sales data from January 2019 to December 2019

Sales data from January 2020 to December 2020

Tweet feeds from January 2019 to December 2020

Comparative analysis to determine % loss in revenue

Sentiment analysis tool (MonkeyLearn)

Project ANALYSIS

Review Sales data from January 2019 to December 2019

Review Sales data from January 2020 to December 2020

Tweet feeds from January 2020 to December 2020

Prepare Tweets for Analysis

Project Steps

Step 1: Training the Classifiers

Project Steps – cont.

Step 2: Preprocess Tweets

Project Steps – cont.

Step 3: Extract Feature Vectors

Project design

Crawl Tweets Against Hash Tags

To have access to the Twitter API, you’ll need to login the Twitter Developer website and create an application. Enter your desired Application Name, Description and your website address making sure to enter the full address including the http://. You can leave the callback URL empty.

Project design – cont.

After registering, create an access token and grab your application’s Consumer Key, Consumer Secret, Access token and Access token secret from Keys and Access Tokens tab.

Project design – cont.

Enter Your Access Token (Do Not Share Your Access Token Secret With Anyone)

Project design – cont.

put this information into the variables defined in the Python code. The Twitter Crawler allows you to scrape tweets against hash tags and store the tweets into a csv.

Project design – cont.

put this information into the variables defined in the Python code. The Twitter Crawler allows you to scrape tweets against hash tags and store the tweets into a csv. I scraped all the tweets containing #Airbnb from January 1, 2020, to December 30, 2020.

Project design – cont.

Put this information into the variables defined in the Python code. The Twitter Crawler allows you to scrape tweets against hash tags and store the tweets into a csv. I scraped all the tweets containing #Airbnb from January 1, 2020, to December 30, 2020.

Project implementation

Analyzing Tweets for Sentiments:

MonkeyLearn has a built-in module “English tweets airlines sentiment analysis” that analyzes sentiments for tweets about airline reviews. This module can classify airline tweets into positive, negative and neutral with an accuracy of 81%.

Project implementation – cont.

When uploading the .csv file that contains Airbnb tweets in MonkeyLearn, we need to discard the first row and ignore the time column:

Project implementation – cont.

In this built-in module, text data is automatically preprocessed and stop words are filtered out before applying the support vector machine algorithm:

Project implementation – cont.

In this built-in module, text data is automatically preprocessed and stop words are filtered out before applying the support vector machine algorithm:

Project results

Visualize Results:

Project results – cont.

Percentage of Negative Tweets – 2019:

Project results – cont.

Percentage of Negative Tweets – 2020:

Project results – cont.

Frequency of positive, negative & neutral tweets:

Project result analysis

Based on the sentiment analysis:

There was more positive feedback in 2019 with corresponding revenue generation.

There was more negative feedback in 2020 with corresponding revenue generation.

The most negative tweet frequency is “COVID-19”

The second most frequent negative tweet is “Dirty Accommodation”

The third most frequent negative tweet frequency is “Poor Customer Service”

Flight cancellation is the fourth most frequent negative tweet, and “Airline Restriction” is the fifth most frequent negative tweet.

Project recommendation

Based on the sentiment analysis:

Increase COVID-19 CDC recommendation on company website.

Create company-wide SLA with Airbnb host accommodations that require home inspection before guest arrives.

Review customer services practices and restructure department to enhance top notch customer experience.

Questions

Suggested topics for residency projects

Sentiment Analysis

Data Mining/Reports – Dashboard

Machine Learning

Neural Networks

Genetic Algorithm

Robo Advisors

Natural Language Processing

references

MonkeyLearn. (2021). Create new value from your data. https://monkeylearn.com/

Qian, V. (2020). Step-by-step twitter sentiment analysis: Visualizing multiple airlines’ PR crisis. https://ipullrank.com/step-step-twitter-sentiment-analysis-visualizing-united-airlines-pr-crisis

Qian, V. (2020). Twitter crawler.txt https://gist.github.com/vickyqian/f70e9ab3910c7c290d9d715491cde44c

Sharda, R., Delen, D., & Turban, E. (2021). Analytics, Data Science, & Artificial Intelligence. Harlow, Essex: Pearson

Twitter. (2021). Happening now. https://twitter.com/

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