Brand Sentiment Analysis on Social Media and the Internet for 20 Keywords

We are looking for experienced programmers in data analysis to perform a brand sentiment analysis across social media and the internet for 20 specific keywords. The goal of this project is to measure the perception and sentiment around these keywords, as well as track their frequency, user reviews, and other relevant indicators.

Project Requirements:

Sentiment Analysis:

Implement a system that analyzes the sentiment (positive, negative, or neutral) of mentions on social media, blogs, forums, and other online platforms.
Filter relevant mentions for the 20 provided keywords.
Data Collection:

Identify and count how often the keywords appear on various platforms (Twitter, Facebook, Instagram, blogs, etc.).
Gather and analyze user reviews from platforms like Google, Amazon, Yelp, and others related to the keywords.
Reports:

Generate detailed reports that include the sentiment associated with each keyword (percentage of positive, negative, neutral).
Include statistics on the frequency of mentions and main trends.
Present a list of key sources where these keywords are discussed (media outlets, social networks, forums, etc.).
Required Skills:

Programming in Python or R (knowledge of libraries like TextBlob, NLTK, or any other sentiment analysis tools).
Experience in social media analysis using APIs (Twitter, Facebook, etc.).
Knowledge in web scraping.
Ability to create visual reports (Excel, Google Sheets, Tableau, PowerBI, or other data visualization tools).
Project Duration:
DESIRED: 1 week
Budget:
Please provide an estimated rate for the full analysis.

Extras:

Prior experience in similar projects is highly valued.
If available, share examples or a portfolio of past work related to sentiment analysis or social media monitoring.