Best Practices for Sentiment Analysis and CrowdControl
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An informative session on Amazon Mechanical Turk where you will learn how your company can leverage the human crowd for human sentiment analysis of content such as tweets, articles, RSS feeds and blog posts. This session digs into the details of getting started and provides information on how to be successful so you get accurate results. Additionally, FreedomOSS will share their experiences designing and managing sentiment tasks and demo's their CrowdControl crowdsourcing platform that is built on top of Mechanical Turk.
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Semelhante a Best Practices for Sentiment Analysis and CrowdControl
Semelhante a Best Practices for Sentiment Analysis and CrowdControl (20)
Best Practices for Sentiment Analysis and CrowdControl
- 1. Best Practices for Sentiment Analysis Presented by: John Hoskins Amazon Mechanical Turk Max Yankelevich Freedom OSS CrowdControl
- 6. How to properly analyze Sentiment.
- 12. How it Works
- 16. Implementing a Sentiment Analysis Workflow
- 20. What Can CrowdControl™ Do for Me? Manual Steps Mechanical Turk Portal Turkers Mechanical Turk Portal Turkers Customer IT Systems Customer IT Systems Complete Automation Quality Information
- 21. Sentiment Analysis Process Setup
- 22. Brand Sentiment Coding Template
- 24. John Hoskins, Amazon Web Services: [email_address] Max Yankelevich, FreedomOSS: [email_address] @amazonmturk Facebook.com/amazonmturk Mechanicalturk.typepad.com
Notas do Editor
- Hi, I want to welcome you all to the Webinar on how to apply Mechanical turk to a sentiment analysis solution. So, allow me to begin by introducing today’s speakers. My name is john Hoskins, I am the Senior Manager of Business Development for the Mechancial Turk team here at Amazon Web services. With me is Max Yankelevich, Chief Architect of the CrowdControl solution at FreedomOSS – a Mechanical Turk Solution Provider Partner.
- First just some logistics. At the end of the webinar we’ll be answering questions – to send us a question, please enter it in to the question panel on the GoToMeeting control panel. We’ll answer as many questions as possible. Today we’re going to briefly introduce sentiment analysis – how to derive it, how can you can apply human judgment on a scalable basis. Finally, we’ll introduce FreedomOSS, one of our partners that has experience at implementing large scale sentiment analysis solution using their CrowdControl platform with Mechanical Turk.
- How could you use Sentiment analysis? What advantage does sit bring to you? With the proliferation of reviews, ratings, recommendations and other forms of online expression, online opinion has turned into a kind of virtual currency for businesses looking to market their products, identify new opportunities and manage their reputations.
- Social media is dominated by people who often express complex emotions such as sarcasm, especially in Tweets and blog posts. Most platforms can't deal with wit, sarcasm and complex emotions which make them unsuitable for many of the questions Many “negative" statements online turn out to be positive while many social mentions consider to be positive turn out to be negative when a human examines them SPAM – relevance cleansing dirty data – not to mention the complexities of analyzing “text language” – the ever changing short cuts expressing
- So, to maintain the fast pace of posts online – is it possible to use human judgement?
- Amazon Mechanical Turk It is a marketplace for work. In a traditional marketplace, like the Amazon.com retail site that you’re probably already familiar with, there are buyers who spend money to purchase products and there are sellers who make money by selling their products. This is true in the Amazon Mechanical Turk Marketplace as well. Businesses, or Requesters as they are called on Mechanical Turk are buying work. Mechanical Turk Workers sell their work and earn money when the transaction is complete. And just like in the Amazon.com retail experience, Amazon Mechanical Turk takes care of all of the transaction details including getting the work “listed” on the site so Workers see it when they browse for Work as well as completing the payment transaction when work is approved by you, the Requester. Let’s talk in a bit more detail about how it works.
- Requesters design HITs, Human intelligence tasks. These HITs are composed of Assignments which are published to the Mechanical Turk Marketplace. Workers select tasks to complete and submit their assignments to Requesters. Requesters approve or reject the results and pay Workers.
- How can I automatically decide if I have the best answer? Plurality – ask more than one worker and compare responses. Train the worker population – pass competencies, show competencies, maintain competencies. Ongoing tests – gold standards, work elements for which you know the answer.
- At this point I am going to turn over the presentation to Max Yankelevich who will discuss how FreedomOSS implemented a sentiment analysis workflow using their platform CrowdControl and Mechanical turk.
- For more information, please feel free to reach out to Max and myself directly at these emails. We’ll be posting the webinar on our site and will send out a notification as soon as it’s available.