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To create the project, click the Create Project floating button to the left side of the Projects page. The Project Metadata tab associated with your new project appears.
2. Enter Twitter Post Analysis as the Project Name, Sentiment Identification as the Process Name, and Text Labeling as the Process.
3. Select Text-Based for Project Type.
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Either click the BROWSE INPUT FILE button to extract field names from the sample input file you’ve downloaded in the previous step, or
Click the CREATE INPUT FIELD button to create the input fields explicitly.
In this example, we’ve created two input fields, Sentence Tweet #and Word Tweet. Set Field Type to text, Mandatory to True, and Operational to True for both these fields.
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7. Click Next to move to the next step Execution.
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8. Click Next , add the to move to the next step, User counts , and Majority vote, and Consensus Percentage values by following these steps:
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a. Set the User counts to 3 if every task has to be allocated to 3 different users. Majority vote 2 indicates that out of 3 users, if at least 2 of them provide the same response, the task completes at level 1. If all 3 users provide different responses, the task moves to level 2.
b. Consensus Percentage: Percentage of total tasks imported that should be allocated to multiple users. The remaining tasks will follow the Maker-Checker or Maker-Editor model.
Creating the Process Logic
The Process Logic section lets you configure the logic based on which datasets are moved from one execution level to the next. For the current project, we enable the following rules:
In case of Majority Vote, do not create any rule from level 1 to level 2. All the tasks which do not have a majority output will automatically flow to level 2.
40% of the project datasets move from level 2 to level 3.
To set the Process Logic, follow these steps:
In the Process Logic section, click the +ADD PROCESS LOGIC button to create the logical flow based on which datasets are moved from one execution level to the next.
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2. In the ADD PROCESS LOGIN section, select L1 [TWITTER SENTIMENT LABELER] from the dropdown list for From Level, and L2 [TWITTER SENTIMENT QA] for To Level.
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3. Click the Add Rule icon to load the add rule UI.
4. Click the USE THE ADD BUTTON TO START ADDING RULES icon.
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7. Click the Percentage drop-down and select 40 %.
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8. Select Project for Percentage Scope and click Submit.
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9. Repeat the above steps to add any other rules by selecting the required options for Percentage Scope and Combinator. Your final Process Logic screen will look like the following:
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10. Click Next to move on to the next step which is managing users & roles.
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Managing Users and Roles
You must now add users to your project and assign the execution levels you just created to them.
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Click the Datasets tab. The Datasets page appears. Use this page to manage datasets for your project.
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2. Taskmonk organizes datasets into batches to simplify management and tracking. To add a new dataset, click Add Batch on the right side of the page. The Add Batch modal appears.
3. Enter Batch 1 as the name for the batch that you want to import in the Add New Batch field. You can ignore the other fields.
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4. Click Submit. This creates a new batch of data for your project and adds it to the Pending tab of the Datasets page.
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5. You can now upload datasets into the batch, as required. To add a dataset to the batch, click the Import button under the Tasks(Import/Export) column. The Import Task modal appears.
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6. Click Choose Files, select the sample input file from your computer and click Import.
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Log in as Analyst and click the My Tasks icon at the top of the page. The My Tasks page appears.
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2. Click the Get Tasks button adjacent to the Twitter Post Analysis project. The labeling UI associated with this project appears.
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