I want prototype for this project with presentation please give me :InsightU A Sentiment Analysis Ecosystem forUniversity Reputation ManagementBrief Overview"InsightU" is a groundbreaking project designed to explore the dynamics of sentimentanalysis within the realm of higher education. By aggregating and analyzing socialmedia data, this initiative aims to provide universities with a comprehensiveunderstanding of public sentiment$,$ enabling them to tailor their branding strategieseffectively. In a competitive educational environment, grasping the pulse of stakeholderperceptions is vital for fostering a strong institutional identity.Problem Statement & DescriptionGeneral Problem: Universities often lack real$-$time insights into how their brand isperceived online. Traditional feedback methods, such as focus groups and surveys, areoften reactive and fail to capture the immediate sentiments of their audience.Specific Problem: Current sentiment analysis tools are often generic and do notaddress the unique language and themes relevant to higher education, such as studentexperiences, academic programs, and community involvement. This limitation can leadto misinterpretations of public perception and missed opportunities for improvement. High$-$Level Functionalities:$1.$ Diverse Data Integration: Collect data from various social media platforms,forums, and blogs related to universities$\mathrm{.}2.$ Advanced Sentiment Analysis: Employ NLP techniques to dissect sentimentsaround specific themes relevant to higher education$\mathrm{.}3.$ Interactive Visualization Tools: Create dashboards that display sentimenttrends$,$ emerging topics, and comparative analyses with peer institutions$\mathrm{.}4.$ Strategic Recommendations: Provide actionable insights to help universitiesimprove their branding and communication strategies.Solution $($Initial Ideas Only$)"$InsightU$"$ will be developed as an intuitive web$-$based platform that combinessophisticated NLP and machine learning methodologies to analyze sentiment in realtime. Key features will include: A customizable dashboard for monitoring sentiment across multiple themes. Tools for segmenting data by demographics and geographic regions. Automated alerts to inform university administrators of significant changes inpublic sentiment$.$Scope: Included: Data collection, thematic sentiment analysis, visualization tools, andstrategic insight generation. Excluded: Detailed user management and engagement tools in the initialrelease phase.DataSource for Data: Data will be sourced from public APIs of social media platforms,education blogs, and community forums discussing university$-$related topics.Size and Scope: The project aims to gather approximately $500,000$ social media postsand interactions over a one$-$year timeframe, focusing on a diverse range of universitiesacross different regions. ImplementationProgramming Languages: Primary: Python, leveraging libraries such as TensorFlow for machine learning,NLTK for natural language processing, and Dash for creating interactivevisualizations.Platform: Development will occur on a Unix$/$Linux environment, with deployment on ascalable cloud platform like AWS.Other Technologies: Database Management: Utilize PostgreSQL for efficient data storage and querycapabilities. Containerization: Implement Docker for creating a consistent developmentenvironment.Challenges to Address: Adapting sentiment analysis to understand informal language and slangcommonly found in social media. Ensuring compliance with data privacy regulations while scraping public data.Algorithms: Initial approaches may include: Using BERT or other transformer$-$based models for sentiment classification,combined with clustering algorithms to identify emerging topics.Proposed Project Details and TimelineSteps to Implement:$1.$ Initial Research and Requirement Gathering: Conduct a comprehensivereview of existing tools and define project specifications $(3$ weeks$)\mathrm{.}2.$ Data Collection Setup: Develop scripts for efficient social media data scrapingand aggregation $(4$ weeks$)\mathrm{.}3.$ Data Cleaning and Preparation: Prepare the collected data for analysis throughpreprocessing techniques $(3$ weeks$)\mathrm{.}4.$ Model Development and Testing: Train and validate sentiment analysis models$(4$ weeks$)\mathrm{.}5.$ Application Development: Build the user interface and visualizationcomponents of the platform $(4$ weeks$)6.$ User Testing and Feedback: Engage with university staff for testing andincorporate feedback into the application $(3$ weeks$)\mathrm{.}7.$ Final Documentation and Presentation: Prepare detailed documentation and apresentation for stakeholders $(2$ weeks$).$Individual or Team Project: This will be a collaborative project involving a team of $5$members, each contributing their expertise in data science, software development, andhigher education marketing.Infrastructure: The project will utilize cloud resources from AWS for data storage andprocessing needs.