Sentiment Analysis

Oluwatomisin Bamidele

(0)

Starting at

$

500

About this service

Summary

Specialized sentiment analysis to help you understand the emotions and opinions expressed in your textual data. Using advanced natural language processing (NLP) techniques, I analyze customer reviews, social media posts, and other textual data sources to extract sentiment scores and insights. This service includes a detailed report with sentiment trends, key themes, and actionable recommendations. Additionally, I provide interactive visualizations and the complete code base used for the analysis.

Process

Initial Consultation and Requirement Gathering: After the purchase, we will schedule a call to discuss the project objectives, data sources, specific needs, and overall scope. This session will help define the expected deliverables and set clear expectations for the project.
Data Collection and Preparation: I will collect the necessary text data either from the client or relevant sources. The data will be cleaned and preprocessed to remove noise, handle missing values, and prepare it for analysis. This step ensures the data is in optimal condition for accurate sentiment analysis.
Sentiment Analysis: Using advanced NLP techniques and sentiment analysis models (such as BERT, VADER, TextBlob, or custom-built models), I will analyze the sentiment of the text data. Multiple models may be implemented to determine which one works best for the specific data type, ensuring the highest accuracy.
Thematic Analysis: Identify key themes and topics within the text data using techniques like LDA (Latent Dirichlet Allocation) topic modeling. This process includes categorizing feedback, detecting common issues, and extracting important keywords to provide deeper insights.
Model Training and Testing: Training sentiment analysis models using machine learning algorithms and testing their performance. This includes providing metrics such as accuracy, precision, recall, and F1-score.
Visualization: Create both interactive or static visualizations to clearly represent the sentiment analysis results. These visualizations will be developed using tools like PowerPoint for static images and interactive dashboards for dynamic exploration of the data
Review and Feedback(2x): I will present the findings and deliverables, walk my client through the report, visualizations, and code base. This review and feedback process will be iterated twice to ensure complete client satisfaction.
Code Base Documentation: Organize and document the code used for sentiment analysis. Ensure the code is well-commented and structured for reproducibility.
Delivery and Handover: Finalize and deliver all project deliverables to the client, including the cleaned dataset, sentiment scores, thematic analysis report, model training and testing results, visualizations, comprehensive report, and the complete code base. Ensuring the client has all necessary materials in one consolidated package.

FAQs

  • What types of data can be analyzed?

    I can analyze various types of textual data, including customer reviews, social media posts, survey responses, emails, and more. If you have a specific type of text data, please reach out to discuss its suitability for sentiment analysis.

  • What is included in the sentiment analysis service?

    The service includes data cleaning and preparation, sentiment scoring, thematic analysis, model training and testing, interactive visualizations, a comprehensive report, and the complete code base used for the analysis. Additionally, I provide a review and feedback session, and a post-project support plan.

  • How do you ensure the accuracy of the sentiment analysis?

    I use advanced natural language processing (NLP) techniques and machine learning models to analyze the text data. The models are trained and tested to ensure high accuracy, and I provide evaluation metrics such as accuracy, precision, recall, and F1-score in the final report.

  • Can you handle data in multiple languages?

    Yes, sentiment analysis can be performed on text data in multiple languages. However, the accuracy of the analysis may vary depending on the language. Please specify the languages involved when discussing the project

  • How long does the sentiment analysis process take?

    The duration of the project depends on the volume of data and the complexity of the analysis. Typically, a sentiment analysis project can take anywhere from a few days to a few weeks. I will provide a detailed timeline after understanding the scope of your project, but my standard timeline is 3 weeks.

  • Can I request custom visualizations or specific analyses?

    Absolutely. I tailor the analysis and visualizations to meet your specific needs. If you have any particular requirements or preferences, please let me know during the initial consultation.

  • Do you offer post-project support?

    Yes, I offer a post-project support plan that provides ongoing assistance for a defined period. This includes addressing any questions, providing further clarifications, and ensuring your continued success with the project deliverables.

  • What if I don’t have my own data?

    If you don’t have your own data, I can assist with data collection from various sources relevant to your needs. This will be discussed during the initial consultation to ensure we gather the most appropriate data for your analysis.

What's included

  • Cleaned dataset

    A dataset that has been cleaned and preprocessed to remove noise, handle missing values.

  • Comprehensive Report

    A detailed report summarizing the methodologies used, sentiment analysis results, key insights, and actionable recommendations. This report will include visualizations and supporting documentation to provide a clear understanding of the findings. Formats: PDF or PowerPoint.

  • Complete Code Base

    The complete, well-documented code base used for the sentiment analysis, organized and structured for transparency and reproducibility. This will allow the client to understand the analysis process and make modifications if necessary. Formats: Code repository (GitHub link, ZIP file).

  • Final Project Package

    A consolidated package of all final deliverables, including the cleaned dataset, sentiment scores, thematic analysis report, model training and testing results, interactive visualizations, comprehensive report, and code base. Formats: Digital package (ZIP file, drive link).

Duration

1 week

Skills and tools

Data Scientist
Data Analyst
Microsoft PowerPoint
NLTK
Python

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