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SLIDESHARE . NET {}

  1. Analyzed Page
  2. Matching Content Categories
  3. CMS
  4. Monthly Traffic Estimate
  5. How Does Slideshare.net Make Money
  6. How Much Does Slideshare.net Make
  7. Keywords
  8. Topics
  9. Questions
  10. Schema
  11. Social Networks
  12. External Links
  13. Analytics And Tracking
  14. Libraries
  15. Hosting Providers
  16. CDN Services

We are analyzing https://www.slideshare.net/slideshow/exploring-chatgpt-for-toxicity-detection-in-github/269590071.

Title:
Exploring ChatGPT for Toxicity Detection in GitHub | PPT
Description:
The document explores the effectiveness of OpenAI
Website Age:
19 years and 3 months (reg. 2006-04-04).

Matching Content Categories {πŸ“š}

  • Technology & Computing
  • Education
  • Mobile Technology & AI

Content Management System {πŸ“}

What CMS is slideshare.net built with?

Custom-built

No common CMS systems were detected on Slideshare.net, but we identified it was custom coded using Next.js (JavaScript).

Traffic Estimate {πŸ“ˆ}

What is the average monthly size of slideshare.net audience?

🌠 Phenomenal Traffic: 5M - 10M visitors per month


Based on our best estimate, this website will receive around 5,010,169 visitors per month in the current month.

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How Does Slideshare.net Make Money? {πŸ’Έ}


Display Ads {🎯}


The website utilizes display ads within its content to generate revenue. Check the next section for further revenue estimates.

Ads are managed by ascendeum.com. Particular relationships are as follows:

Direct Advertisers (58)
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Reseller Advertisers (71)
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How Much Does Slideshare.net Make? {πŸ’°}


Display Ads {🎯}

$63,200 per month
Our estimates place Slideshare.net's monthly online earnings from display ads at $42,127 to $115,850.

Keywords {πŸ”}

software, pdf, chatgpt, pptx, toxic, toxicity, github, preetha, chatterjee, prompt, search, data, state, free, exploring, detection, comments, developer, tech, world, discussion, dataset, engineering, workflows, download, mulesoft, mcp, model, book, industry, nation, forum, booknet, canada, crack, josanj, cifdaq, safe, report, content, marketing, storytelling, trends, aienhanced, detecting, types, misclassified, annotated, integration, trust,

Topics {βœ’οΈ}

concurrency real-world patterns large-scale data migrations includes personal attacks book industry state tech field fme safe software open source projects software engineering workflows software developer conversation software developer communication automated toxicity detection successful job search model context protocol social media age pptx drrajdeepmadavi mitigating unhealthy interactions identifying toxic behaviors irony nuanced toxicity developer chats improving emotion recognition european business wallet forecasting inflection points manual testing 2024 trend updates hubspot marius sescu teenage engineerings pixeldarts gender shape attitudes open source bleeding-edge build informative code world comprehensive annotated dataset github pull requ github shyamal mishra io/files/icse_nier_24 fine-tuning llms pdf dataset april 2024 preetha marketing report highlight specific types detecting toxic text software engineering leave chatgpt output detecting toxic comments paid search se workflows toxicity detection integrate storytelling novice software software engineers

Questions {❓}

  • How effective is OpenAI ChatGPT in detecting toxic text on GitHub?
  • RQ1: How effective is OpenAI ChatGPT in detecting toxic text on GitHub?
  • RQ2: What types of toxic comments are misclassified by ChatGPT?
  • What types of toxic comments are misclassified by ChatGPT?

Schema {πŸ—ΊοΈ}

CreativeWork:
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      name:Exploring ChatGPT for Toxicity Detection in GitHub
      description:The document explores the effectiveness of OpenAI's ChatGPT in detecting toxic comments on GitHub, analyzing a dataset of 1,597 comments. Results indicate varying performance in identifying toxic behaviors and highlight specific types of toxicity that are often misclassified. It concludes that while ChatGPT is not perfect, it offers a viable method for automated toxicity detection without requiring extensive annotated datasets, with suggestions for further improvements and integration in software engineering workflows.
      url:https://www.slideshare.net/slideshow/exploring-chatgpt-for-toxicity-detection-in-github/269590071
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Organization:
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WebPage:
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Social Networks {πŸ‘}(1)

Analytics and Tracking {πŸ“Š}

  • Google Analytics
  • Google Analytics 4
  • Google Tag Manager

Libraries {πŸ“š}

  • Clipboard.js
  • Moment.js
  • Video.js
  • Zoom.js

Emails and Hosting {βœ‰οΈ}

Mail Servers:

  • smtp.google.com

Name Servers:

  • ns-1225.awsdns-25.org
  • ns-1650.awsdns-14.co.uk
  • ns-178.awsdns-22.com
  • ns-802.awsdns-36.net

CDN Services {πŸ“¦}

  • Slidesharecdn

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