OCEL.AI
No Result
View All Result
Monday, April 19, 2021
  • Login
  • Home
  • Story Telling
  • Data Sharing
    • Data Sharing
    • Data Searching
    • Data Integration
  • ML Experience
  • Applications
    • Applications
    • Data Visualization
    • ML Applications
  • Ethics
  • Courses
    • University Of Missouri Kansas City
      • Python/DL Programming
      • Big Data Programming
      • Web/Mobile Programing
      • Big Data Analysis and Application
      • Interactive and Social Media Advertising
    • University of Florida
      • ADV 3500 Digital Insights
    • Essex County College
      • CSC 231 Database Design
      • CSC 232 Advanced Database Management
    • Eastern Michigan University
      • JRNL453: Advanced Reporting
  • News/Events
  • Resources
    • Demo Projects
    • Documentation
    • Setup Tableau
    • Tools
Forum
OCEL.AI
  • Home
  • Story Telling
  • Data Sharing
    • Data Sharing
    • Data Searching
    • Data Integration
  • ML Experience
  • Applications
    • Applications
    • Data Visualization
    • ML Applications
  • Ethics
  • Courses
    • University Of Missouri Kansas City
      • Python/DL Programming
      • Big Data Programming
      • Web/Mobile Programing
      • Big Data Analysis and Application
      • Interactive and Social Media Advertising
    • University of Florida
      • ADV 3500 Digital Insights
    • Essex County College
      • CSC 231 Database Design
      • CSC 232 Advanced Database Management
    • Eastern Michigan University
      • JRNL453: Advanced Reporting
  • News/Events
  • Resources
    • Demo Projects
    • Documentation
    • Setup Tableau
    • Tools
No Result
View All Result
OCEL.AI
No Result
View All Result
Home Demo Projects

Human In the Loop: Digital Humanities

by Digital Humanity
August 7, 2020
in Demo Projects
2 min read
159
VIEWS
FacebookTwitterPinterestLinkedIn

Story Telling Data Sharing ML Experience Applications Ethics

Navigate with the buttons above to other sections:

Define your scope or domain where the use case is relevant or prevalent?

The purpose of the study is to understand the perception of sentiment in the content of Greek tragedy essays. The study questions the ability for existing sentiment analysis tools (typically trained on modern social media data) to capture complex and layered sentiment displayed in the domain of translated ancient Greek tragedy.

What is your main story?

Sentiment Analysis of Greek tragedy helps the students and literature readers understand more about the Greek tragedy. So we have a goal to find the sentiment of the Greek tragedy with existing sentiment tools. However, existing tools failed to identify the sentiment of Greek tragedy. Here, we want to discuss the flaws of the current tools and propose a new solution that helps to identify the sentiment of the Greek tragedy.

Who are the characters or people in the main story?

Students and literature readers.

What happens?

It is hard to find the sentiment of the Greek tragedy on the whole for students and literature readers with a limited period of what they have. Sentiment analysis of Greek tragedy helps them to choose which parts to read and explore.

Where?

In classrooms, libraries, and book reading groups.

When?

During teaching, during exams, etc.

Why?

Usually, literature is very lengthy and hard to read it entirely without a break. When students and literature readers are about to finish, they may tend to lose track of the start of the Greek tragedy literature.

How?

To address this issue, we have to collect the sentiment of the Greek tragedy literature by experts in it and apply existing sentiment analysis models. After that, by evaluating existing tools performance, we can decide whether we can proceed with existing tools or create a new one, especially for Greek tragedy literature.

 

Example: EduKC
ShareTweetSendShareShareSendShare
Previous Post

AI-Dentistry

Next Post

Teeth Segmentation

Next Post
Teeth Segmentation

Teeth Segmentation

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

This work was partially sponsored by NSF.

NSF IUSE #1935076
CUE Ethics: Collaborative Research: Open Collaborative Experiential Learning (OCEL.AI): Bridging Digital Divides in Undergraduate Education of Data Science

01/01/2020 – 6/30/2021, $ 350,000

Copyright © 2020 OCEL.AI.

 

Quick Links

  • Documentation
  • Faculty/TA Registation 
  • Student Course Registration
No Result
View All Result
  • Home
  • Story Telling
  • Data Sharing
    • Data Sharing
    • Data Searching
    • Data Integration
  • ML Experience
  • Applications
    • Applications
    • Data Visualization
    • ML Applications
  • Ethics
  • Courses
    • University Of Missouri Kansas City
      • Python/DL Programming
      • Big Data Programming
      • Web/Mobile Programing
      • Big Data Analysis and Application
      • Interactive and Social Media Advertising
    • University of Florida
      • ADV 3500 Digital Insights
    • Essex County College
      • CSC 231 Database Design
      • CSC 232 Advanced Database Management
    • Eastern Michigan University
      • JRNL453: Advanced Reporting
  • News/Events
  • Resources
    • Demo Projects
    • Documentation
    • Setup Tableau
    • Tools

Welcome Back!

OR

Login to your account below

Forgotten Password?

Create New Account!

Fill the forms bellow to register

All fields are required. Log In

Retrieve your password

Please enter your username or email address to reset your password.

Log In