Developing a Web Dashboard for analyzing Amazon's Laptop sales data

How to scrape Amazon Reviews using Python:

• https://www.scrapehero.com/how-to-scrape-amazon-product-reviews/
• https://blog.datahut.co/scraping-amazon-reviews-python-scrapy/

Sentiment analysis on Amazon Reviews using Python

• https://github.com/Maha41/Sentiment-analysis-on-Amazon-Reviews-using-Python
• https://github.com/JagruthiSPrabhudev/Sentiment-Analysis-of-Amazon-review-data

Sentiment Analysis Applications/Dashboards

• https://www.youtube.com/watch?v=R5HkXyAUUII

• http://endemo.finereport.com:8080/webroot/decision#directory

• https://www.csc2.ncsu.edu/faculty/healey/tweet_viz/tweet_app/

• https://vimeo.com/andreitr

• https://www.softwareadvice.com/resources/free-twitter-sentiment-analysis-tools/

• https://blog.flexmr.net/making-sense-of-big-qual-7-of-the-best-text-and-sentiment-analysis-tools

Interactive Python Dashboards with Plotly and Dash

• https://dash-gallery.plotly.host/Portal/?search=%20

• https://www.udemy.com/course/interactive-python-dashboards-with-plotly-and-dash/

• https://dash.plot.ly/react-for-python-developers
• https://dash.plot.ly/plugins
• https://www.youtube.com/watch?v=wifoPPRgG_I

Sentiment analysis with Python

• https://www.udemy.com/course/data-science-natural-language-processing-in-python/

• https://www.udemy.com/course/sentiment-analysis-deep-learning-keras-python/

• https://www.udemy.com/course/natural-language-processing-with-deep-learning-in-python/

Back-end - Flask - DJango

• https://towardsdatascience.com/create-a-complete-machine-learning-web-application-using-react-and-flask-859340bddb33

• https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/

• https://www.udemy.com/course/python-rest-apis-with-flask-docker-mongodb-and-aws-devops/

• https://www.udemy.com/course/rest-api-flask-and-python/

• https://www.udemy.com/course/react-django-full-stack/

• https://www.udemy.com/course/introduction-to-tweepy-python-twitter-library/

• https://www.udemy.com/course/introduction-to-tweepy-python-twitter-library-part-2/

• https://www.udemy.com/course/python-bot-development/

Predicting elections with sentiment analysis

• https://en.wikipedia.org/wiki/List_of_elections_in_2020

• https://medium.com/@stefanobosisio1/sentiment-analysis-to-predict-political-elections-outcome-506284890132

• https://ricochet.com/565273/archives/predicting-elections-using-a-i-and-machine-learning/

• https://link.springer.com/article/10.1007/s40092-017-0238-2

• https://pdfs.semanticscholar.org/fd8b/8e5d4ae127afc71437d39881d69d963ed80a.pdf

• https://medium.com/analytics-vidhya/twitter-sentiment-analysis-for-the-2019-election-8f7d52af1887

• https://www.researchgate.net/publication/280623314_The_machine_learning_in_the_prediction_of_elections

Mapas

• https://www.amcharts.com/demos/multi-series-map/

Researh

Data Analysis Web Dashboard for Amazon online reviews

In marketing and business intelligence, it is crucial to know what customers think about target products. Customer opinions, reviews or any data that reflect the experience of the customer, represents an important information that companies can use to enhances their marketing and business strategies.

Traditionally, this kind of data have been collected using method such as face to face or telephone surveys.

Recently, the huge amount of data generated every day in social network and online retailer, is being used to perform analysis that allow to gain a better understanding of the market and, in particular, about customer opinions.

Sentiment Analysys, is a method that uses natural language processing and text analysis thecniques to extract key indicators from text data. It is widely used in reviews and survey analysis.

Most important comments mencioned in class

Comentarios más importante mencionados en las clases. Grahan said the most important points in the Research part and that we need to include in the project at the end of this semester are:

• Research

• Problem / Innovation
• Technologies

• Plan - Timeline