ProjectName: Rapid Analyzer Description Rapid Analyzer is a project that utilizes various powerful applications to perform in-depth analysis of user sentiments on the Play Store. The goal of this project is to categorize reviews as positive, negative, or neutral, providing insights into user satisfaction levels and identifying patterns. By leveraging the capabilities of the following applications, Rapid Analyzer enables users to visualize complex data in a descriptive manner:
-
Microsoft Azure Text Analytics API: Integrate the cloud-based services of Microsoft Azure Text Analytics API to perform advanced text mining and analysis. This API offers Natural Language Processing (NLP) features, including sentiment analysis, text summarization, key phrase extraction, language detection, and named entity recognition. Utilizing this API will enhance the sentiment analysis capabilities of Rapid Analyzer.
-
Amplitude: Leverage the robust quantitative analytics tool, Amplitude, to gain valuable insights into user behavior and optimize app performance. Through features such as retention rate detection, real-time app analytics, scalable analytics, retroactive funnels, and user segmentation, Amplitude provides comprehensive analytics capabilities to enhance the analysis performed by Rapid Analyzer.
-
Interceptd: Incorporate Interceptd, an ad fraud solution, into Rapid Analyzer to ensure the exclusion of fraudulent installs and optimize clean traffic. With features like blocking fraudulent clicks, installs, and in-app actions, access to accurate and clean data, in-app event tracking and analytics with graphs and flowcharts, customizable reports for tracking fraud and key performance indicators (KPIs), and comprehensive metrics like effective return on ad spend (ROAs), customizable cohorts, and revenue events, Interceptd enhances the accuracy and reliability of the analysis conducted by Rapid Analyzer.
-
Mixpanel: Utilize Mixpanel, a leading business analytics service company, to track user interactions with web and mobile applications. By integrating Mixpanel into Rapid Analyzer, you can measure user engagement and retention, and build custom reports to gain insights into user behavior. Mixpanel supports web applications and mobile apps, making it a versatile tool for analyzing user sentiments across platforms.
-
UXCam: Integrate UXCam, a software solution for user experience analysis, into Rapid Analyzer to gain qualitative and quantitative insights into user interactions with mobile apps. By understanding how users interact with your product through UXCam, you can identify pain points and areas for improvement, enabling you to enhance the user experience and optimize app performance.
CONTENT
DashboardInformation:
• NumberofPosts:This is the total count of posts from the selected data source. • Number of Users: The total number of unique users who have contributed tothedata. • Engagements: The overall count of interactions such as likes, comments,shares, or retweets. • Reach:Theestimatednumberofuniqueuserswhohaveseentheposts. • Impressions:Thetotalnumberoftimesthepostshavebeendisplayedtousers.
InfluentialUsers:
Top 5 Influential Users: Identifying the users who have the most impact or followingwithin the analyzeddata. With the unique approach
SentimentAnalysis:
Sentiment (Positive, Negative, Neutral): Categorizing posts based on their sentiment,whethertheyexpresspositive,negative, or neutralemotions.
LocationInformation:
Top5Countries:Identifying the countries or locations where the posts are originating.
Demographics:
Gender:
Analyzing and displaying the gender distribution of users who contributed to thedata.
DevicesandApps:
Top 5 Devices and Apps: Highlighting the devices or applications most commonly usedbyusersfor posting content.
LinkedWebsites:
Most Linked Websites: Identifying and displaying the websites or domains mostfrequentlysharedinthe data.
SocialMediaPostTypes:
Post Types (Original, Reply, etc.): Categorizing posts into types, such as original posts,replies,orretweets, tounderstand the natureofinteractions.
Note: This comprehensive dashboard will provide users with a rich and informativeexperience, allowing them to explore and gain insights into the sentiment andcharacteristics of X’s data. Users can use this information for various purposes,including understanding trends, tracking engagement, and identifying influential usersandtopics.
TECHNOLOGY FrontendTechnologies:
• JavaScript(JS):For creating dynamic and interactive user interfaces. • HTML:For structuring webpages and content. • React.js:A JavaScript framework for building user interfaces with components. • ECharts: A data visualization library for creating interactive charts and graphs.BackendTechnologies: • Python:Asthebackendprogramminglanguage. • Flask: A Python web framework for building web applications and APIs.Libraries: • AntVECharts: A visualization library for creating interactive charts and graphson the frontend. • NumPy:A library for numerical operations and data manipulation in Python. • Pandas:AdataanalysisandmanipulationlibraryinPython. • NLTK (Natural Language Toolkit): A Python library for natural languageprocessing, whichcanbeusedfor sentimentanalysis.
RESPONSIBILITY Instead of splitting tasks, we decided to work in each area together. Thus we candevelop our skills and knowledge in each of them. As well as, we will learn how tooperateasa team.
PLAN LEARNINGPLAN:
Objective: The learning plan aims to ensure that each team member acquires thenecessary skills and knowledge to contribute effectively to the project. The planincludesabreakdownoflearning objectives, resources, andtimelines.
TeamMembers:
Nosirov Jamoliddin Jabborov Sherzod Tokhirov Saydullo Md Abirul Islam
LearningObjectives:
FrontendDevelopment(Vue.jsandECharts):
Week 1-2: Learn the fundamentals of React.js, including components, routing, and statemanagement.
Week 3-4: Explore ECharts and understand how to create interactive charts andgraphs.
Week5-6:Combine React.jsandEChartsfordatavisualization.
BackendDevelopment(Flask):
Week 1-2: Study Flask, focusing on routing and creating RESTful APIs.Week 3-4: Learn database integration and data retrieval using Flask.Week5-6:Developthe backend forthe webapplication. DataCollectionandSentimentAnalysis:
Week 1-2: Understand data collection methods (e.g., Twitter API) and retrieve sampledata.
Week3-4:ExploreNLTKforsentimentanalysisandsentimentcategorization.
Week5-6:Codesentimentanalysiscomponentsandintegratethemintotheproject.
CollaborativeCodingandCodeReviews:
Ongoing: Collaborate on coding tasks, conduct regular pair programming sessions,andparticipate incodereviewsformutual learning.
DocumentationandKnowledgeSharing:
Ongoing: Document what you learn and share it with the team during knowledgesharingsessions.
Resources:
- Onlinetutorialsandcourses(e.g.,React.js,Flask, NLTK)
- OfficialdocumentationforReact.js,Flask,ECharts,andotherlibraries
- Textbooksandreferencematerials
- Codereviewtools(e.g.,GitHub)
PROJECTPLAN:
Objective:The project plan outlines the tasks, timeline, and responsibilities for eachphase of the sentiment analysis web application project over 15 weeks. It ensures thattheprojectiswell-structuredand thatteammemberscollaborateeffectively.
ProjectTimeline:
Week1-2:ProjectPlanningandDesignWeek3-5:DataCollectionandPreprocessing Week6-7:BackendandFrontendDevelopment
Week 8-9: Sentiment Analysis IntegrationWeek 10-11: Data Visualization ImplementationWeek12: Testing andQualityAssurance Week 13-14: Documentation and Knowledge SharingWeek 15: Final Testing, Bug Fixes, and DeploymentTasksand Responsibilities:
- Project Planning and Design: All team members collaborate to define projectgoals,datasource,userinterfacedesign, anddatavisualization strategy.
- Data Collection and Preprocessing: Team members collaborate on datacollection and preprocessing tasks.
- Backend and Frontend Development: All team members participate in bothbackendand frontend developmenttasks.
- Sentiment Analysis Integration: Team members work together to integratesentimentanalysiscomponents.
- Data Visualization Implementation: Team members collaborate on creatingdatavisualizations.
- Testing and Quality Assurance: All team members participate in testing andqualityassurance.
- Documentation and Knowledge Sharing: All team members contribute tocreatingprojectdocumentation andknowledgesharing sessions. Note: Throughout the project, regular meetings should be held to discuss progress,addresschallenges, and facilitate knowledgesharing.